Saimm 201512 dec

VVOLUME 115 NO. 12 DECEMBER 2015

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Mike TekePresident, Chamber of Mines of South Africa

Mosebenzi ZwaneMinister of Mineral Resources, South Africa

Rob DaviesMinister of Trade and Industry, South Africa

Naledi PandorMinister of Science and Technology, South Africa

R.T. Jones

C. Musingwini

S. NdlovuA.S. Macfarlane

J.L. Porter

C. Musingwini

Z. Botha G. NjowaV.G. Duke A.G. SmithI.J. Geldenhuys M.H. SolomonM.F. Handley J.D. SteenkampW.C. Joughin M.R. TlalaM. Motuku D. TudorD.D. Munro D.J. van Niekerk

N.A. Barcza G.V.R. Landman R.D. Beck J.C. Ngoma J.R. Dixon S.J. Ramokgopa M. Dworzanowski M.H. Rogers F.M.G. Egerton G.L. Smith H.E. James W.H. van Niekerk

Botswana L.E. DimbunguDRC S. MalebaJohannesburg I. AshmoleNamibia N.M. NamateNorthern Cape C.A. van WykPretoria P. BredellWestern Cape A. MainzaZambia D. MumaZimbabwe S. NdiyambaZululand C.W. Mienie

Australia: I.J. Corrans, R.J. Dippenaar, A. Croll, C. Workman-Davies

Austria: H. WagnerBotswana: S.D. WilliamsUnited Kingdom: J.J.L. Cilliers, N.A. BarczaUSA: J-M.M. Rendu, P.C. Pistorius

The Southern African Institute of Mining and Metallurgy

*Deceased

* W. Bettel (1894–1895)* A.F. Crosse (1895–1896)* W.R. Feldtmann (1896–1897)* C. Butters (1897–1898)* J. Loevy (1898–1899)* J.R. Williams (1899–1903)* S.H. Pearce (1903–1904)* W.A. Caldecott (1904–1905)* W. Cullen (1905–1906)* E.H. Johnson (1906–1907)* J. Yates (1907–1908)* R.G. Bevington (1908–1909)* A. McA. Johnston (1909–1910)* J. Moir (1910–1911)* C.B. Saner (1911–1912)* W.R. Dowling (1912–1913)* A. Richardson (1913–1914)* G.H. Stanley (1914–1915)* J.E. Thomas (1915–1916)* J.A. Wilkinson (1916–1917)* G. Hildick-Smith (1917–1918)* H.S. Meyer (1918–1919)* J. Gray (1919–1920)* J. Chilton (1920–1921)* F. Wartenweiler (1921–1922)* G.A. Watermeyer (1922–1923)* F.W. Watson (1923–1924)* C.J. Gray (1924–1925)* H.A. White (1925–1926)* H.R. Adam (1926–1927)* Sir Robert Kotze (1927–1928)* J.A. Woodburn (1928–1929)* H. Pirow (1929–1930)* J. Henderson (1930–1931)* A. King (1931–1932)* V. Nimmo-Dewar (1932–1933)* P.N. Lategan (1933–1934)* E.C. Ranson (1934–1935)* R.A. Flugge-De-Smidt (1935–

1936)* T.K. Prentice (1936–1937)* R.S.G. Stokes (1937–1938)* P.E. Hall (1938–1939)* E.H.A. Joseph (1939–1940)* J.H. Dobson (1940–1941)* Theo Meyer (1941–1942)* John V. Muller (1942–1943)* C. Biccard Jeppe (1943–1944)* P.J. Louis Bok (1944–1945)* J.T. McIntyre (1945–1946)* M. Falcon (1946–1947)* A. Clemens (1947–1948)* F.G. Hill (1948–1949)* O.A.E. Jackson (1949–1950)* W.E. Gooday (1950–1951)* C.J. Irving (1951–1952)* D.D. Stitt (1952–1953)* M.C.G. Meyer (1953–1954)* L.A. Bushell (1954–1955)* H. Britten (1955–1956)* Wm. Bleloch (1956–1957)

* H. Simon (1957–1958)* M. Barcza (1958–1959)* R.J. Adamson (1959–1960)* W.S. Findlay (1960–1961)

D.G. Maxwell (1961–1962)* J. de V. Lambrechts (1962–1963)* J.F. Reid (1963–1964)* D.M. Jamieson (1964–1965)* H.E. Cross (1965–1966)* D. Gordon Jones (1966–1967)* P. Lambooy (1967–1968)* R.C.J. Goode (1968–1969)* J.K.E. Douglas (1969–1970)* V.C. Robinson (1970–1971)* D.D. Howat (1971–1972)

J.P. Hugo (1972–1973)* P.W.J. van Rensburg (1973–

1974)* R.P. Plewman (1974–1975)

R.E. Robinson (1975–1976)* M.D.G. Salamon (1976–1977)* P.A. Von Wielligh (1977–1978)* M.G. Atmore (1978–1979)* D.A. Viljoen (1979–1980)* P.R. Jochens (1980–1981)

G.Y. Nisbet (1981–1982)A.N. Brown (1982–1983)

* R.P. King (1983–1984)J.D. Austin (1984–1985)H.E. James (1985–1986)H. Wagner (1986–1987)

* B.C. Alberts (1987–1988)C.E. Fivaz (1988–1989)O.K.H. Steffen (1989–1990)

* H.G. Mosenthal (1990–1991)R.D. Beck (1991–1992)J.P. Hoffman (1992–1993)

* H. Scott-Russell (1993–1994)J.A. Cruise (1994–1995)D.A.J. Ross-Watt (1995–1996)N.A. Barcza (1996–1997)R.P. Mohring (1997–1998)J.R. Dixon (1998–1999)M.H. Rogers (1999–2000)L.A. Cramer (2000–2001)

* A.A.B. Douglas (2001–2002)S.J. Ramokgopa (2002-2003)T.R. Stacey (2003–2004)F.M.G. Egerton (2004–2005)W.H. van Niekerk (2005–2006)R.P.H. Willis (2006–2007)R.G.B. Pickering (2007–2008)A.M. Garbers-Craig (2008–2009)J.C. Ngoma (2009–2010)G.V.R. Landman (2010–2011)J.N. van der Merwe (2011–2012)G.L. Smith (2012–2013)M. Dworzanowski (2013–2014)J.L. Porter (2014–2015)

Van Hulsteyns Attorneys

Messrs R.H. Kitching

The Southern African Institute of Mining and Metallurgy

Fifth Floor, Chamber of Mines Building

5 Hollard Street, Johannesburg 2001 • P.O. Box 61127, Marshalltown 2107

Telephone (011) 834-1273/7 • Fax (011) 838-5923 or (011) 833-8156

E-mail: [email protected]

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ContentsJournal Comment—21 years of Chemical Engineering & Metallurgy at Witsby J.H. Potgieter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv-vPresident’s Cornerby R.T. Jones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi

Removal of heavy metals using cassava peel waste biomass in a multi-stage countercurrent batch operationby G.S. Simate, S. Ndlovu, and L. Seepe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1137Optimization of complex integrated water and membrane network systemsby M. Abass, E. Buabeng-Baidoo, D, Nezungai, N. Mafukidze, and T. Majozi . . . . . . . . . . . . 1143The impact of coal quality on the efficiency of a spreader stoker boilerby R.L. Taole, R.M.S. Falcon, and S.O. Bada. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1159Coal quality and uranium distribution in Springbok Flats Coalfield samplesby M. Ndhlalose, N. Malumbazo, and N. Wagner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1167Synthesis of sodium silicate from South African coal fly ash and its use as an extender in oil well cement applicationsby T. Kaduku, M.O. Daramola, F.O. Obazu, and S.E. Iyuke. . . . . . . . . . . . . . . . . . . . . . . . . . . 1175Mechanical behaviour of pack carburized AISI 316L austenitic stainless steel by D.E.P. Klenam, C. Polese, L.H. Chown, S. Kwofie, and L.A. Cornish. . . . . . . . . . . . . . . . . . 1183Making sense of our mining wastes: removal of heavy metals from AMD using sulphidation media derived from waste gypsumby J. Mulopo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1193Enhancing study practices: are first-year students ‘resistant to change’?by L. Woollacott, S. Booth, and A. Cameron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1199Recycling of cemented tungsten carbide mining tool scrap by C.S. Freemantle and N. Sacks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1207Titanium carbide–silicon nitride reactions at high temperatureby N. Can and R. Hurman Eric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1215Polyethersulphone-sodalite (PES-SOD) mixed-matrix membranes: prospects for acid mine drainage (AMD) treatmentby M.O. Daramola, B. Silinda, S. Masondo, and O.O. Oluwasina. . . . . . . . . . . . . . . . . . . . . . . 1221

The accuracy of calcium-carbonate-based saturation indices in predicting the corrosivity of hot brackish water towards mild steelby A. Palazzo, J. van der Merwe, and G. Combrink . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1229The effect of sodium carbonate on the dispersion behaviour and froth flotation of a nickel oreby B. Feng, Q.M. Feng, Y.P. Lu, and H.H. Wang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1239The influence of water quality on the flotation performance of complex sulphide ores: case study at Hajar Mine, Moroccoby K. Boujounoui, A. Abidi, A. Bacaoui, K.El Amari, and A. Yaacoubi . . . . . . . . . . . . . . . . . . 1243Development and optimization of mixed sulphide/oxide copper ore treatment at Kansanshiby F.X. Paquot and C. Ngulube . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1253

R. Dimitrakopoulos, McGill University, CanadaD. Dreisinger, University of British Columbia, CanadaE. Esterhuizen, NIOSH Research Organization, USAH. Mitri, McGill University, CanadaM.J. Nicol, Murdoch University, AustraliaE. Topal, Curtin University, Australia

VOLUME 115 NO. 12 DECEMBER 20 15

R.D. BeckJ. Beukes

P. den HoedM. Dworzanowski

B. GencM.F. Handley

R.T. JonesW.C. Joughin

J.A. LuckmannC. MusingwiniJ.H. PotgieterR.E. Robinson

T.R. Stacey

D. Tudor

The Southern African Institute ofMining and MetallurgyP.O. Box 61127Marshalltown 2107Telephone (011) 834-1273/7Fax (011) 838-5923E-mail: [email protected]

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THE INSTITUTE, AS A BODY, ISNOT RESPONSIBLE FOR THESTATEMENTS AND OPINIONSADVANCED IN ANY OF ITSPUBLICATIONS.Copyright© 1978 by The Southern AfricanInstitute of Mining and Metallurgy. All rightsreserved. Multiple copying of the contents ofthis publication or parts thereof withoutpermission is in breach of copyright, butpermission is hereby given for the copying oftitles and abstracts of papers and names ofauthors. Permission to copy illustrations andshort extracts from the text of individualcontributions is usually given upon writtenapplication to the Institute, provided that thesource (and where appropriate, the copyright)is acknowledged. Apart from any fair dealingfor the purposes of review or criticism underThe Copyright Act no. 98, 1978, Section 12,of the Republic of South Africa, a single copy ofan article may be supplied by a library for thepurposes of research or private study. No partof this publication may be reproduced, stored ina retrieval system, or transmitted in any form orby any means without the prior permission ofthe publishers. Multiple copying of thecontents of the publication withoutpermission is always illegal.

U.S. Copyright Law applicable to users In theU.S.A.The appearance of the statement of copyrightat the bottom of the first page of an articleappearing in this journal indicates that thecopyright holder consents to the making ofcopies of the article for personal or internaluse. This consent is given on condition that thecopier pays the stated fee for each copy of apaper beyond that permitted by Section 107 or108 of the U.S. Copyright Law. The fee is to bepaid through the Copyright Clearance Center,Inc., Operations Center, P.O. Box 765,Schenectady, New York 12301, U.S.A. Thisconsent does not extend to other kinds ofcopying, such as copying for generaldistribution, for advertising or promotionalpurposes, for creating new collective works, orfor resale.

VOLUME 115 NO. 12 DECEMBER 2015

PAPERS – CHEMICAL ENGINEERING & METALLURGY AT WITS

PAPERS OF GENERAL INTEREST

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Celebrating one’s 21 year of existence is indeed a mostjoyous occasion, and another milestone in the historyof Chemical and Metallurgical Engineering at the

University of the Witwatersrand. Since its formation in1995 through the merger of the departments of ChemicalEngineering and Metallurgy and Materials Engineering asthe School of Process and Materials Engineering, theSchool has gone from strength to strength. In 2005‘Chemical and Metallurgical Engineering’ became theofficial designation of the School after ratification of thename change by the University Council. The School hasbeen at the forefront of education and research inengineering and has contributed greatly to the demand forskilled manpower by the process, beneficiation, andmetallurgical industries in South Africa. The School pridesitself on its contribution in terms of human resourcestraining and development, knowledge generation, andcommunity involvement and contributions. A significantnumber of industry and academic leaders locally andworldwide are Wits Chemical and Metallurgical Engineeringgraduates and alumni.

Chemical Engineering at Wits can trace its origins backto the immediate predecessors of the University, i.e. theUniversity College Johannesburg (Transvaal) and prior tothat the South African School of Mines, both of whichoffered courses in Chemical Technology. When Wits wasestablished, Chemical Technology courses continued andthe first Bachelor of Science in Engineering (ChemicalTechnology) degrees were awarded in March 1922. After1926 the courses were revised and the degree awardedfrom 1928 onwards was Bachelor of Science in Engineering(Chemical Engineering). Although the ChemicalEngineering degrees have always been awarded in theFaculty of Engineering, responsibility for the courses laywith the Department of Chemistry and ChemicalTechnology from 1922–1927 and thereafter the Departmentof Chemistry and Chemical Engineering from 1928–1960.The first independent Department of Chemical Engineeringat Wits was established in 1961 with Professor O.B. Volckman as its first Head. Thereafter Professor DavidGlasser, Associate Professor Donald Williams and ProfessorTony Bryson acted as heads of department until 1995,when the School of Process and Materials Engineering wasformed. Professor Bryson was also the first Head of thenewly established school from 1995–1998. For a morecomplete history on Chemical Engineering at Wits, pleaseconsult Murray’s book ‘Wits: the Early Years’ (Murray,1982) and Harris’s ‘Chemical Engineering at the Universityof the Witwatersrand, Johannesburg’ (Harris, 1983).

Metallurgy at Wits has an even longer history thanChemical Engineering and can trace its roots to one of thethree founding departments of firstly the Kimberley Schoolof Mines and, after the second Anglo-Boer War, the SouthAfrican School of Mines, together with the departments ofMining Engineering and Geology. Both the latter are stillindependent Schools at Wits, and all three will celebratetheir 120th birthdays in 2016. The Department ofMetallurgy has grown substantially over the years since theappointment of Professor G.H. Stanley as the first Chair ofMetallurgy and Head in 1904. He held this position for 35years until his retirement in 1939 and was succeeded byProfessor L. Taverner from 1940 until 1959. Theestablishment of the Minerals Research Laboratory in1934, a joint venture between the State, the University,and the forerunner of the present-day Council for MineralTechnology (Mintek), gave research a strong boost. Boththe departments of Metallurgy and Chemical Engineeringbenefitted from the research focus on the recovery ofmetals and minerals from ores, and both presentedspecialized courses in minerals processing and extractivemetallurgy for third- and fourth-year students. While somecourses were jointly presented, each department awardedits own degree and it was only with the formation of theSchool in 1995 that the full strength and synergy betweenthe two departments in the field of minerals beneficiationcould be fully exploited.

Between 1959 and 1962 Professor C.E. Mavrocordatosled the Metallurgy Department, followed by Professor D.D. Howat who took over from the beginning of 1963until 1975. From then on the headship of the departmentbecame more of a rotating than a permanent position, with Professors G.G. Garrett, R.P King, P. Robinson, andR.H. Eric all acting as heads of department for selectedperiods of time. Professor Hürman Eric was the last Headof the Department of Metallurgy before its merger withChemical Engineering to form the current School. He wassubsequently also the second Head of the School of Processand Materials Engineering from 1999–2002. For moredetail on the history of Metallurgy at Wits, consult Eric’sdescriptions (Eric, 2004, 2006).

In 2002 Professor Wolter te Riele took over theheadship of the School until the end of 2003. Following ashort period of four months during which Professor Ericwas acting Head of School, Professor Herman Potgieterbecame the Head of the School and led the efforts tochange the name of the School to reflect the traditionaldisciplines from which it originated. Following hisdeparture in 2008, Mr Bob Tait acted as Head of Schooluntil June 2009 when Professor Sunny Iyuke took over the

Journal CommentThe School of Chemical and Metallurgical Engineering at the

University of the Witwatersrand

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reins. Professor Iyuke headed the School until 2014, when the process commenced again to find a new Head.Professor Thoko Majozi steered the ship as acting Head ofSchool in the last six months of 2014 until ProfessorHerman Potgieter returned in January 2015 as Head ofSchool again.

The School currently has a total staff complement of 54, made up of 14 Chemical Engineers, 14 Metallurgists, 5 visiting temporary lecturers, 4 workshop personnelmembers, a team of 9 administrative staff, and 8 technicians and laboratory assistants. There are 755 undergraduate students, 240 registered postgraduatestudents (part-time and full-time) and 5 postdoctoralfellows currently studying and working in the School. The School hosts no less than three South African ResearchChair Initiative candidates in the persons of ProfessorThoko Majozi (Sustainable Process Engineering), Professor Selo Ndlovu (Hydrometallurgy and SustainableDevelopment), and Professor Rosemary Falcon (Clean CoalTechnology) out of a total of 25 such chairs in the whole ofthe University of the Witwatersrand. In addition, ProfessorJack Sigalas (Chair in Ceramic Science) and Professor TonyPaterson (Welding and Fabrication Engineering) holdendowed chairs from Element 6 and the South AfricanInstitute of Welding, respectively.

The School presents fully ECSA-accreditedundergraduate programmes in Chemical and MetallurgicalEngineering, as well as postgraduate MSc degrees on a50% taught/50% research, or research-only basis in thespecialization areas of Coal Studies, Pyrometallurgy,Minerals Processing and Extractive Metallurgy, andAdvanced Chemical Engineering. The postgraduateprogramme in Oil and Gas Engineering (Petroleum) isunique in South Africa and cannot be followed at any otherlocal university, while the postgraduate program inWelding Engineering is internationally accredited andoffers a route to full registration as a Welding Engineer.PhD opportunities in all these areas are also available. TheSchool has excellent ties with industry and in addition itoffers consultation services over a wide spectrum forindustry. The School prides itself on always being sensitiveto the needs of industry and society in general, andupdates its curricula and research accordingly in order tostay relevant and provide the latest knowledge tograduates. Current areas of research strength includepyrometallurgy, hydrometallurgy (Metals and MineralsExtraction and Recovery Group – MMERG), physicalmetallurgy of steels, stainless steels, Wo-Co hard metals,ceramics, and thermodynamic modelling in the researchfocus areas of Hard Metals and Stainless Steels as part of

the Centre of Excellence in Strong Materials – CoE SM),welding, coal (Clean Coal Technologies Group), sustainableenergy and environmental research (SEERU), watertreatment, specifically acid mine drainage (AMD)(Industrial and Mine Water Treatment Research Unit –IMWaRU), nanotechnology, tribology, and processoptimization.

We are proud of our history and our significantcontribution to South Africa in terms of human resourcesdevelopment and delivering competent graduates forindustry, as well as supplying fundamental and appliedresearch to solve industrial problems and contribute torelevant technology. The School of Chemical andMetallurgical Engineering at Wits is well placed to continueat the forefront of teaching and research with a group ofenthusiastic, efficient and dynamic staff consisting of amixture of well-established and experienced academics anda group of young, developing academics. Despite difficultfinancial times and turmoil in the mining industry, we lookconfidently to the future in the knowledge that we shallcontinue to provide a home for future engineering leadersand inspiring innovation to give our graduates the edge!

References

1. MURRAY, B.K. 1982. Wits: The Early Years.Witwatersrand University Press, Johannesburg.

2. HARRIS, W.F. 1983. Chemical Engineering at theUniversity of the Witwatersrand. ChemSA, March 1983.

3. ERIC, R.H. 2004. A brief history of time in WitsMetallurgy. Journal of the South African Institute ofMining and Metallurgy, November 2004.

4. ERIC, R.H. 2006. A glimpse of Pyrometallurgy at WitsUniversity. Proceedings of Southern AfricanPyrometallurgy 2006. Jones, R.T. (ed.). South AfricanInstitute of Mining and Metallurgy, Johannesburg.pp. 101–104.

J.H. PotgieterProfessor and Head of School

Journal Comment (continued)

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Nelson Mandela said that ‘Education is the most powerful weapon which you can use to change the world’. SouthernAfrica suffers greatly from a shortage of well-educated people. However, it is a massive challenge to increase literacy,let alone to provide education for all people in the region, starting with early childhood education, through primary

and secondary schooling, and culminating with university studies. But this is a challenge to which we must rise, as educatedpeople are employable and have the capacity to build a better society, to create employment, and to reduce poverty.

The Universal Declaration of Human Rights (1948) says, in Article 26, ‘Everyone has the right to education. Educationshall be free, at least in the elementary and fundamental stages. Elementary education shall be compulsory. Technical andprofessional education shall be made generally available and higher education shall be equally accessible to all on the basisof merit.’ Some countries seem to have got this right, with examples of free education (even at university level) seen incountries including Cuba in the developing world (which spends 10 to 11% of its GDP on education), and Norway in thedeveloped world. Annual spending on education around the world exceeds five trillion US dollars, yet there are still around800 million people who are unable to read or write. There is clearly a pressing need for more professional, dedicated, well-trained teachers, and for society at large to confer a high social status on these important people (as is the case in the Nordiccountries).

In South Africa, the Freedom Charter of 1955 declared that ‘Education shall be free, compulsory, universal and equal forall children. Higher education and technical training shall be opened to all by means of state allowances and scholarshipsawarded on the basis of merit.’ More recently, Section 29 of the Bill of Rights in the Constitution of South Africa says that‘Everyone has the right to a basic education, including adult basic education; and to further education, which the state,through reasonable measures, must make progressively available and accessible’.

A report commissioned by the Department of Higher Education last year found that South Africa spends only 0.75% ofits GDP on tertiary education, which is less than the average in Africa, let alone the world average. Universities say thatgovernment funding has not kept up with inflation and the huge increase in student numbers in recent years. Rising fees atuniversities have made studying unaffordable for many potential students. There is no doubt that many students areeffectively excluded from a university education because of poverty.

Students at the University of the Witwatersrand started protesting around 14 October 2015, in response to anannouncement by the university that fees would be raised by 10.5% in the New Year. The ‘Fees Must Fall’ student protestsquickly spread to other universities across South Africa. University activities were significantly disrupted and access tocampuses was effectively blocked. By 17 October, Wits University agreed to suspend the fee increase, and declined to takedisciplinary action against participating students or staff members. Exams were postponed by a week. After a week ofnationwide protests, a mass rally of many thousands of protesting students was held outside the Union Buildings inPretoria. This resulted in the President of South Africa declaring that there will be a zero increase of university fees in 2016.A small group of demonstrators turned violent, setting fire to a portable toilet, and breaking down fences. The policeresponded with tear gas, stun grenades, and rubber bullets. The students themselves called for discipline, stressing that itwas a peaceful protest.

There seems to be a general consensus view that the protesting students managed to achieve a great deal in a relativelyshort space of time. Overall, the protests were disruptive but relatively peaceful (with a few exceptions). Many commentatorshold the view that these protests are historically significant for our country. Of course, it remains to be seen whether the zeroincrease in fees is altogether a good thing -- presumably good for students' finances, but not necessarily so for providing thefunds needed for quality education (unless the funds can be made up from somewhere else). The universities have arguedthat they need a greater income to keep up their standards.

The SAIMM’s Young Professionals Council responded promptly to the protests by presenting a very constructive option(by means of contributions to the SAIMM Scholarship Trust Fund) for people to contribute towards solving some of the veryreal problems faced by many students in South Africa. This fund makes a big difference to the lives of many students, andenables them to stay at university when they would otherwise have to drop out because of insufficient money for books oreven food. This is a very good example of the way in which the SAIMM shows that it cares.

There is a further dimension to the story of the mining and metallurgy students of 2015. Perhaps half of the studentswho have recently graduated will not find employment in the year ahead. The universities have done a great job in responseto the call to double the number of graduates in the past few years. However, in the current downturn, there are very fewjobs available. This is a tragedy for the individual student who might have come from a rural village where the communityhas raised funds for him or her to get an education, with the expectation of a well-paying job, and the student has to returnhome dejected and empty-handed. Has a proper survey been carried out to determine how many engineers the miningindustry actually needs in good times and in bad times?

As we approach the end of 2015, the mining industry is feeling rather battered and bruised after an exceptionally toughyear. Many observers have indicated that 2016 is likely to be tough too, but we know that the commodity business is acyclical one and the world we live in requires a variety of metals in order to function, so there is some optimism for themedium term. Best wishes to all for a good rest during the coming holiday season.

R.T. JonesPresident, SAIMM

A right to knowledgePresident’s

Corner

PAPERS IN THIS EDITIONThese papers have been refereed and edited according to internationally accepted standards and are

accredited for rating purposes by the South African Department of Higher Education and Training

These papers will be available on the SAIMM websitehttp://www.saimm.co.za

Papers — Chemical Engineering & Metallurgy at Wits Removal of heavy metals using cassava peel waste biomass in a multi-stage countercurrent batch operationby G.S. Simate, S. Ndlovu, and L. Seepe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1137A study is presented of the removal of cobalt (Co2+), chromium (Cr3+) and vanadium (V3+) from synthetic effluent solution using cassava waste biomass in a multi-stage counter current batch system. The target metal concentrations in the final outlet stream were measured against the South African Department of Water and Forestry standards.

Optimization of complex integrated water and membrane network systemsby M. Abass, E. Buabeng-Baidoo, D, Nezungai, N. Mafukidze, and T. Majozi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1143This work considers the synthesis and optimization of water networks through partial treatment of water (regeneration) before recycle/re-use. Four different compositions were studied and the developed models applied to a pulp and paper and petroleum case study to demonstrate their applicability.

The impact of coal quality on the efficiency of a spreader stoker boilerby R.L. Taole, R.M.S. Falcon, and S.O. Bada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1159This research established the combustion characteristics and efficiencies of South African coals of different qualities and their impact on the performance of a specific travelling grate spreader stoker boiler. The thermographic results led to the conclusion that South African low-grade Gondwana coals undergo delayed ignition and burn at unusually high temperatures.

Coal quality and uranium distribution in Springbok Flats Coalfield samplesby M. Ndhlalose, N. Malumbazo, and N. Wagner. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1167This investigation examines the deportment of uranium in the coal zones intersected by five boreholes that were drilled in the Springbok Flats Coalfield.

Synthesis of sodium silicate from South African coal fly ash and its use as an extender in oil well cement applicationsby T. Kaduku, M.O. Daramola, F.O. Obazu, and S.E. Iyuke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1175The use of sodium silicate derived from South African coal fly ash (CFA) as an oil well cement slurry extender was investigated. The physico-chemical properties of the material were found to be consistent with those of commercial sodium silicate, and a comparative study indicated that the slurries extended with CFA have slightly lower densities, lower viscosities, and higher compressive strength than those extended with commercial sodium silicate.

Mechanical behaviour of pack carburized AISI 316L austenitic stainless steel by D.E.P. Klenam, C. Polese, L.H. Chown, S. Kwofie, and L.A. Cornish . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1183The effect of surface hardening by pack carburizing on the mechanical properties of AISI 316L steel was studied. The results show that the process significantly reduces the ductility, ultimate tensile strength, and impact toughness.

Making sense of our mining wastes: removal of heavy metals from AMD using sulphidation media derived from waste gypsumby J. Mulopo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1193The recovery of water and the selective removal of valuable metals from acid mine drainage (AMD) was investigated using calcium sulphide produced by the carbothermal reduction of waste gypsum. It was found that although selective metal removal and recovery as metal sulphides can be achieved, the purity of the CaS and mass transfer limitations associated with the AMD-CaS system may be critical for process development.

Enhancing study practices: are first-year students ‘resistant to change’?by L. Woollacott, S. Booth, and A. Cameron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1199The claim that students are resistant to changing their study practices was investigated by interviewing chemical andmetallurgical engineering students in a South African university at the beginning and end of their first year. ‘Resistance to change’ appeared to be implicit in nature and to be more a consequence of overconfidence and the ‘momentum’ resulting from habit rather than an explicit attitudinal resistance.

Papers — Chemical Engineering & Metallurgy at Wits (continued)Recycling of cemented tungsten carbide mining tool scrap by C.S. Freemantle and N. Sacks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1207Two different techniques and processes – the zinc recycling process (PRZ) and acetic acid leaching – were used to recover and recycle cemented tungsten carbide mining tool scrap metal. It was found that the two processes could be used as complementary processes on an industrial scale.

Titanium carbide–silicon nitride reactions at high temperatureby N. Can and R. Hurman Eric. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1215The kinetics and mechanism of the chemical interaction between silicon nitride and titanium carbide under nitrogen and argon atmospheres were investigated using thermogravimetric analysis. The relevant activation energies, as well as rate constants and diffusion coefficients, were determined, and the mechanisms of reactions modelled.

Polyethersulphone-sodalite (PES-SOD) mixed-matrix membranes: prospects for acid mine drainage (AMD) treatmentby M.O. Daramola, B. Silinda, S. Masondo, and O.O. Oluwasina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1221Polyether sulfone (PES)-sodalite (SOD) mixed matrix membranes loaded with different amounts of SOD particles were fabricated and evaluated for the treatment of acid mine drainage. The results showed that the mechanical strength of the membrane, as well as the selectivity towards Mn2+, Pb2+, Cu2+, Al3+, and Mg2+, was enhanced by increasing the SOD loading. Optimization of the synthesis protocol and operational conditions is needed to improve the performance of the membrane.

Papers of General InterestThe accuracy of calcium-carbonate-based saturation indices in predicting the corrosivity of hot brackish water towards mild steelby A. Palazzo, J. van der Merwe, and G. Combrink . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1229An empirically derived nonlinear regression model was developed and compared with the existing indices for predicting the corrosivity of mild steel in contact with brackish water at 45ºC. The accuracy of the broader application and relevance of the indices are also discussed.

The effect of sodium carbonate on the dispersion behaviour and froth flotation of a nickel oreby B. Feng, Q.M. Feng, Y.P. Lu, and H.H. Wang. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1239The effect of sodium carbonate on the flotation performance of a nickel ore was studied. The flotation result show that the presence of lizardite minerals in the ore interferes with the flotation pentlandite. The addition of sodium carbonate improves pentlandite flotation recovery by changing the interparticle forces from attraction to repulsion, resulting in the removal of adhering slimes from pentlandite surfaces.

The influence of water quality on the flotation performance of complex sulphide ores: case study at Hajar Mine, Moroccoby K. Boujounoui, A. Abidi, A. Bacaoui, K.El Amari, and A. Yaacoubi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1243A preliminary study on the effect of water quality on the flotation of galena, sphalerite, chalcopyrite, and pyrrhotite was carried out using asymmetrical fractional factorial design. The results showed that the influence of process water on lead flotation depends on its composition and concentrations of constituents.

Development and optimization of mixed sulphide/oxide copper ore treatment at Kansanshiby F.X. Paquot and C. Ngulube . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1253The previously stockpiled mixed sulphide/oxide ores at Kansanshi are now treated by flotation using controlled potential sulphidization. This paper describes the development of the process and its optimization. The effect of the complex mineralogy on the flotation performance is discussed.

Wastewaters from many sources, such as themetallurgical, tannery, chemical manufac-turing, mining, and battery manufacturingindustries, contain toxic heavy metals. Theconcentrations of some of the toxic metals inthese effluents are sometimes higher thanpermissible discharge levels. Discharge of thecontaminated wastewater into the environmentwould, therefore, create a significant environ-mental hazard, including impacts on human,animal, and plant health (Matouq et al.,2005). According to the South AfricanDepartment of Water Affairs and Forestry(DWAF) (2005), the permissible dischargelimits for chromium, cobalt, and vanadium are0.1, 0.5, and 0.2 mg/L, respectively. Therefore,it becomes necessary to remove these heavymetals from wastewaters by an appropriatetreatment process before releasing them intothe environment (Meena et al., 2005).

Several conventional chemical and physicalmethods have been developed and used toremove high concentrations of heavy metalsfrom wastewater effluents, including (but not

limited to) precipitation, solvent extraction, ionexchange, reverse osmosis,oxidation/reduction, sedimentation, filtration,and electrochemical techniques (Volesky,2001; Feng et al., 2010; Nassar, 2010; Shen etal., 2009; Song et al., 2011; Ahmadi et al.,2014). However, most of these methods havehigh capital and operational costs, low metalremoval efficiency at low concentrations, andgenerate toxic sludge that requires additionaltreatment (Ahmadi et al., 2014; Motouq et al.,2015). Therefore, a lot of effort has beendirected at the development of economicalmethods for the removal of toxic heavy metalsfrom wastewater effluents.

The use of biological-based technologiessuch as biosorption for removal of heavymetals from wastewater effluents has recentlybecome the subject of considerable interestbecause of the low cost and high efficiencyassociated with the process (Arminia et al.,2015). Previous studies by the authors haveshown that cassava peel waste is a potentiallyuseful biosorbent for treating wastewatercontaminated with Co2+, V3+, and Cr3+ ions(Ndlovu et al., 2013; Simate and Ndlovu,2014; Seepe, 2014). Cassava is a perennialwoody shrub, grown as an annual crop, andserves as a major source of low-cost carbohy-drates for populations in the humid tropics(O’Hair, 1995; Simate et al., 2013; Adetunji etal., 2015). In the past, the largest producer ofcassava was Brazil, followed by Thailand,Nigeria, the DRC, and Indonesia (O’Hair, 1995;Adetunji et al., 2015), but today Nigeria is thelargest producer (Adetunji et al., 2015). So far,not much effort has been made to control ormanage the enormous quantities of wastesarising from processing cassava tuber into its

Removal of heavy metals using cassavapeel waste biomass in a multi-stagecountercurrent batch operationby G.S. Simate*, S. Ndlovu*, and L. Seepe*

This paper presents a study of the removal of cobalt (Co2+), chromium(Cr3+), and vanadium (V3+) from synthetic effluent solution using cassavawaste biomass. Test work was carried out in a multi-stage countercurrentbatch system. Single and ternary metal ion systems were studied. A feedinlet concentration of 100 mg/L for each metal ion system was contactedwith 0.5 g of cassava waste biomass. The target concentration in the finaloutlet stream was set against the South African Department of Water andForestry (DWAF) standards. The results showed that the adsorptioncapacity was slightly lower for ternary metal ion systems than for singlemetal ion systems. This was attributed to the greater competition amongthe metal ions for the occupancy of the binding surfaces on the cassavawaste in the ternary systems. Eight adsorption stages were required tomeet the targeted limit of 0.5 mg/L for Co2+ set by the DWAF. The Cr3+

system needed six stages to obtain the targeted limit of 0.1 mg/L, while theV3+ system required four stages to attain the target limit of 0.2 mg/L. Ingeneral, cassava waste biomass adsorbed the metal ions in the followingorder: V3+ > Cr3+ > Co2+.

heavy metals, wastewater, biosorption, cassava waste, biomass, multi-stage, countercurrent, batch.

* School of Chemical and Metallurgical Engineering,University of the Witwatersrand, Johannesburg.

© The Southern African Institute of Mining andMetallurgy, 2015. ISSN 2225-6253. Paper receivedMay 2015 and revised paper received Nov. 2015.

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Removal of heavy metals using cassava peel waste biomass

various products, which are abundant and available in allseasons (Seepe, 2014). Since cassava waste has no economicvalue, its conversion into biosorbents would ultimatelyeconomically benefit the millions of cassava producers.Indeed, the economic utilization of cassava waste would notonly provide a solution to the environmental nuisance that itposes, but would create employment and improve localeconomies (Ndlovu et al., 2013).

Since the manner in which the biomass contacts with thesolution to be treated is of particular significance for large-scaletreatment of water, initial studies by the authors involved,firstly, batch equilibrium relating to adsorbate, adsorbent, andoperating conditions (Ndlovu et al., 2013). This was followedby heavy metal removal studies in a column packed withimmobilized cassava waste pellets (Simate and Ndlovu, 2014).Column-type continuous flow operations have an advantageover batch-type operations because the rates of adsorptiondepend on the concentration of solute in the solution beingtreated. For column operation, the biomass is continuously incontact with a fresh solution. Consequently, the concentrationin the solution in contact with a given layer of biomass in acolumn changes very slowly. In batch treatment, the concen-tration of solute in contact with a specific quantity of biomassdecreases much more rapidly as adsorption proceeds, therebydecreasing the effectiveness of the adsorbent for removing thesolute (Zhou, 2013).

However, the main limitations of the two studies are: (1)batch systems are usually limited to the treatment of smallquantities of wastewater (Bharathi and Ramesh, 2013), anddata obtained from such systems may not be applicabledirectly to most treatment systems (such as columnoperations) where the contact time is not sufficient for theattainment of equilibrium (Zulfadhly et al., 2001; Vinodhiniand Das, 2010; Vimala et al., 2011; Bharathi and Ramesh,2013); and (2) fixed-bed column studies are characterized byclogging and subsequent release of adsorbent into the treatedwastewater (Amirnia et al., 2015), and immobilization ofbiomass also causes mass transfer limitations by hinderingthe access of the metals to the biosorbent sites compared tosuspended biosorbents (Tsezos, 1990; Cassidy et al., 1996).Furthermore, the regeneration capacity of immobilizedbiomass is limited, thus there is need for biomass to bereplaced frequently, which is a costly process (Amirnia et al.,2015). However, continuous operation is the only viable wayof treating large volumes of wastewater in a reasonable time,and this is where bench-scale batch biosorption studies arelimited in their scope (Amirnia et al., 2015).

Based on the authors’ earlier work on the removal ofCo2+, V3+, and Cr3+ ions using cassava waste biomass in abatch system (Ndlovu et al., 2013), metal adsorption using amulti-stage countercurrent batch system was investigated inthis study. Multi-stage countercurrent adsorption operations

are superior to both batch and fixed bed operations becausecountercurrent flow maximizes the average driving force formass transfer between the fluid and the adsorbent (Seepe,2014). This technique involved contacting the metal ionsolution with the cassava waste biomass in a series of gentlyagitated tanks for a sufficient retention time. The cassava andmetal ion solution were transferred in a countecurrent flowarrangement. The schematic diagram for multi-stage batchadsorption is shown in Figure 1. In multi-stage counter-current batch adsorption, the solution to be treated contains L dm3 solution and the concentration of heavy metals isreduced in each stage from Cn-1 to Cn mg/dm3. The amount ofbiomass added is B g and the heavy metal concentration onthe biomass is increased from qn+1 to qn mg/g of biomass.

The cassava tubers were obtained from local wholesalers inSouth Africa and were prepared as described by Ndlovu et al.(2013). In summary, cassava tubers were carefully peeledand the dried cassava peel waste was ground to 100 μmusing a blender. Subsequently, the ground cassava peel wastewas treated with nitric acid. Finally, sulphhydryl groups (orthiol groups) were introduced onto the cassava biomassusing thioglycolic acid solution in the presence of hydroxy-lamine.

As illustrated in Figure 1, the multi-stage countercurrentbiosorption was operated batchwise. About 0.5 g of cassavawaste biomass was contacted with 100 mL of the influentsolution in each reactor. The concentration of each metal ionin the inlet solution stream was 100 mg/L. Tests wereconducted for single and ternary metal ion systems. Mixingwas provided by agitation at 150 r/min. After 30 minutes,agitation was stopped and the biosorbent separated frommetal ion solution by filtration. The biosorbent and effluentsolutions were then transferred to the next respective reactorsin a countercurrent manner. This procedure was followeduntil the final effluent was transferred to the discharge tankfrom reactor n. The saturated spent biomass emerging fromthe first reactor was transferred to the regenerator, in whichthe adsorbed metals were removed, and the biomass wassubsequently reactivated and then returned to the adsorptioncircuit. The main advantage of this process is that theadsorbent can be regenerated as soon as its role in theadsorption step has been completed. Thus, in theory at least,the inventory of the adsorbent can be kept to a minimum.The quantity of adsorbent required for a given separation canalso be reduced by increasing the number of stages.However, the possibility of regeneration and re-use of the

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cassava biomass was beyond the scope of this study. Inpractice, the heavy metals eluted from the cassava biomasscould be further concentrated and/or used as an input inother hydrometallurgical processes.

Fourier transform infrared (FTIR) spectroscopy was used toidentify the presence or absence of functional groups on thesurface of cassava peel waste biomass before and afterthiolation. Figure 2 shows the obtained FTIR spectra. As canbe seen from Figure 2(a) and (b), the major differencebetween the two biomasses is the presence of thesulphhydryl group (-SH), which proves that thiolationprocess adds sulphhydryl functional groups on the cassavapeel biomass (Ndlovu et al., 2013; Simate and Ndlovu,2015). Other differences between treated and untreatedcassava biomass were reported by Ndlovu et al. (2013). Forexample, the BET surface areas obtained were in thefollowing order: untreated < 0.5 M acid treated < 1 M treated,and both the pore volume and pore size were in the followingorder: untreated > 0.5 M acid treated > 1 M treated. The pointof zero charge (pzc) for the untreated and treated cassavapeel biomass was determined as 4.9 and 3.1, respectively.This shows that the functional groups on untreated cassava

peel biomass are weakly acidic (or more basic) than thefunctional groups on treated cassava peel biomass. Therefore,the pzc results confirm that more acidic functional groupswere incorporated into the cassava peel biomass duringthiolation. These results concurr well with the results shownin Figure 2(b), which shows the introduction of an acidicsulphhydryl group after thiolation.

Tables I–VI show the results of a series of adsorptiontests, and the number of stages required to reduce the heavymetals in this study to acceptable drinking water standardsas set by the DWAF. Tables I and II show the adsorption ofCo2+ in single and ternary systems, respectively. Eight stagesof Co2+ removal were needed to meet the targeted limit of 0.5mg/L in the effluent discharge. The effluent solution obtainedafter the 8th stage contained 0.04 and 0.05 mg/L Co2+ forsingle and ternary systems, respectively. Tables III and IVshow that the adsorption of Cr3+ needed six stages to obtainthe targeted limit of 0.1 mg/L. For single system and ternarysystem, 0.04 and 0.05 mg/L were obtained, respectively. ForV3+, the effluent solution at the end of the 4th stagecontained 0.01 and 0.02 mg/L for single and ternarysystems, respectively (see Tables V and VI), with a targetlimit of 0.2 mg/L. In all cases, the adsorption capacity wasslightly lower for the ternary metal ion system as comparedto the single metal ion system. This may be attributed to thegreater competition between the metal ions for the occupancyof the binding surfaces on the cassava waste biomass(Ndlovu et al., 2013). Generally, the biosorption efficiencyincreased in the order Co2+ < Cr3+ < V3+. These results are inagreement with our previous batch studies (Ndlovu et al.,2013) and column studies (Simate and Ndlovu, 2014). Thedifferences (or variations) are attributed to the metal ions’affinity towards the biosorbent (Mohan and Sreelakshmi,2008), and this depends on the ionic radius andelectropositive charges on the ions (Reddad et al., 2002).

This study showed that the adsorption efficiency obtainedin the multi-stage countercurrent system is higher than thatobtained in our study of the batch system, implying thatthere is a limited number of active binding sites on the


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Tank 1 exit 43.02 11.40 19.89 56.97Tank 2 exit 30.58 2.49 19.21 28.93Tank 3 exit 25.42 1.03 18.32 16.89Tank 4 exit 19.91 1.10 17.30 21.66Tank 5 exit 10.99 1.78 15.92 34.71Tank 6 exit 7.89 0.62 14.78 39.31Tank 7 exit 3.46 0.89 13.78 56.17Tank 8 exit 0.04 0.68 11.40 98.84


adsorbent for metal adsorption in a batch system. However,in the multi-stage system, a somewhat weak solution is incontact with a biomass that has more active binding sites asit moves up the train from last stage to the first stage, hencehigher recoveries were obtained.

The required discharge limits were obtained for all metalsusing multi-stage countercurrent batch adsorption systemwith cassava peel waste biomass as biosorbent. The minimalaccepted limits for Co2+, Cr3+ and V3+ discharge were reachedin 8, 6, and 4 stages, respectively. Thus, in general, cassavawaste biomass adsorbed the metal ions in the followingorder: V3+> Cr3+ > Co2+. The adsorption efficiency obtained inthe multi-stage countercurrent system was higher than thatachieved previously in a batch process.

The authors are thankful to all those who provided financial[NRF Scholarship (South Africa) and Friedel Sellschop award(University of the Witwatersrand, South Africa)] or technicalsupport in the course of this research work. The work is partof the MSc (Eng) dissertation submitted by Ms Lizzy Seepe in2014 to the University of the Witwatersrand, Johannesburg.

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Tank 1 exit 45.32 10.94 20.04 54.68Tank 2 exit 35.13 2.04 19.26 22.50Tank 3 exit 26.15 1.80 18.37 20.52Tank 4 exit 20.78 1.07 17.20 32.3Tank 5 exit 11.67 1.82 15.84 41.74Tank 6 exit 8.17 0.70 14.77 54.74Tank 7 exit 3.69 0.90 12.96 54.77Tank 8 exit 0.05 0.73 10.94 98.64

Tank 1 exit 38.15 12.37 19.99 61.86Tank 2 exit 28.01 2.03 18.98 26.54Tank 3 exit 20.01 1.60 17.62 28.52Tank 4 exit 10.18 1.97 16.00 40.58Tank 5 exit 5.13 1.01 14.40 56.89Tank 6 exit 0.04 1.02 12.37 99.24

Tank 1 exit 40.16 11.97 20.28 59.84Tank 2 exit 32.50 1.53 19.08 19.81Tank 3 exit 21.74 2.15 17.65 33.10Tank 4 exit 13.26 1.70 15.95 39.02Tank 5 exit 6.13 1.43 13.80 53.78Tank 6 exit 0.05 1.22 11.97 99.35

Tank 1 exit 34.71 13.06 20.00 65.29Tank 2 exit 18.13 3.32 18.98 47.78Tank 3 exit 5.13 2.60 16.38 71.75Tank 4 exit 0.01 1.02 13.06 99.90

Tank 1 exit 38.85 12.23 20.00 61.15Tank 2 exit 21.61 3.448 18.60 44.30Tank 3 exit 6.99 2.924 15.67 67.71Tank 4 exit 0.02 1.394 12.23 99.74

The contents of this paper reflect the views of the authors,who are responsible for the facts and accuracy of the datapresented herein and do not necessarily reflect the officialviews or policies of any agency or institute. This paper doesnot constitute a standard or specification, nor is it intendedfor design, construction, bidding, or permit purposes. Tradenames were used solely for information and not for productendorsement.

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VOLESKY, B. 2001. Detoxification of metal-bearing effluents: biosorption for thenext century. Hydrometallurgy, vol. 59. pp. 203–216.

ZHOU, Y. 2013. XXIVth International Congress of Pure and Applied Chemistry.Oxford, Butterworth-Heinemann.

ZULFADHLY, Z., MASHITAH, M.D., and BHATIA, S. 2001. Heavy metal removal infixed bed column by the macrofungus Pycnoporus sanguineus.Environmental Pollution, vol. 112. pp. 463–470. ◆


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For further information contact: Ms Ntokozo DubeTel: (011) 717-7521 • E-mail: [email protected] or [email protected]

Water and energy are important resources forthe development and wellbeing of humanity.They are key components in both the processand the mining industry, and great amounts ofeach resource are consumed to produce theother. Process integration is often employed inorder to establish a holistic water networksuperstructure for minimizing theconsumption of water and energy. This is donethrough an integrated water network that isopen for direct re-use, recycle, andregeneration re-use/recycle for sustainable,cost-effective water and energy usage.

Water pinch techniques and mathematical-based optimization techniques are the twomain approaches used for optimal synthesis ofwater networks in the process industries.Wang and Smith (1994, a, b) presented the

seminal work in water pinch analysis whichsets to target the re-use, regeneration, and re-use/recycle of waste water in order to reducefresh water consumption. That work has sincedeveloped into advanced graphical, tabular,and heuristic methods for water networksynthesis. The insight-based techniques do notinvolve computational algorithms ingenerating solutions. They do, however,require significant problem simplifications andassumptions, and are inherently limited tomass-transfer-based operations (Manan et al.,2004; Bandyopadyay and Cormos, 2008; Tanet al., 2009).

Takama et al. (1980) presented asuperstructure optimization approach for waterminimization in a petrochemical refinery basedon a fixed mass load. The work was laterextended by several other researchers(Rossiter and Nath, 1995; Doyle and Smith,1997; Huang et al., 1999; Karrupiah andGrossmann, 2006; Ahmetovic and Grossmann,2010). Quesada and Grossmann (1995),Karrupiah and Grossmann (2006), and Fariaand Bagajewicz (2011) presented algorithmsto obtain feasible solution in cases of the morecomplex nonlinear programming (NLP) andmixed integer nonlinear programming(MINLP) problems that are in many cases achallenge to solve. Mathematical optimizationallows water network synthesis problems to betreated in their full complexity by consideringrepresentative cost functions, multiple contam-inants, and various topological constraints(Takama, et al., 1980; Savelski andBagajewicz, 2000; Bagajewicz and Savelski,2001; Grossman and Lee, 2003; Gunaratmanet al., 2005). Mathematical optimizationapproaches also have an added advantage of

Optimization of complex integratedwater and membrane network systemsby M. Abass*, E. Buabeng-Baidoo*, D, Nezungai*, N. Mafukidze*, and T. Majozi*

Water and energy are key resources in the process and mining industries.Increasing environmental and social pressures have made it necessary todevelop processes that minimize the consumption of both these resources.This work considers the synthesis and optimization of water networksthrough partial treatment of water (regeneration) before recycle/re-use.Two types of membrane regenerators are considered, namely electro-dialysis and reverse osmosis. For each of the membrane regenerators, adetailed design model is developed and incorporated into the waternetwork model in order to minimize water and energy consumption, andoperating and capital costs. This represents a rigorous design and accuratecost representation as compared to the ‘black-box’ approach. The presenceof continuous and integer variables, as well as nonlinear constraints,renders the problem a mixed integer nonlinear programming (MINLP)problem. Four cases are presented. The first case looks at the incorporationof multiple electrodialysis regenerators with single contaminant streamswithin a water network (WN), while the second considers the multiplecontaminant scenario. Case 3 examines the incorporation of a reverseosmosis network superstructure within a WN, and case 4 looks at bothelectrodialysis and reverse osmosis membranes. The developed models areapplied to a pulp and paper and a petroleum case study to demonstratetheir applicability, assuming both a single and multiple contaminantscenario. The model was solved in GAMS using BARON and DICOPT. Theresults indicate a wastewater reduction of up to 80% and savings of up to44% in fresh water intake, 82% in energy, and 45% in the total annualizedcost.

sustainable, synthesis, optimization, reverse osmosis, electrodialysis.

* School of Chemical and Metallurgical Engineering,University of Witwatersrand, Johannesburg

© The Southern African Institute of Mining andMetallurgy, 2015. ISSN 2225-6253. Paper receivedMay 2015.

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Optimization of complex integrated water and membrane network systems

simulating the water network into a desired networkstructure and operational condition (Chew et al., 2008).

Tan et al. (2009) presented a water networksuperstructure with a single membrane partitioningregenerator which allows for possible re-use/recycle. Thework considered the ‘black-box’ approach, which uses linearcost functions for the membrane regenerators. This does notgive an accurate cost representation of the water network.Khor et al. (2011) addressed this deficiency by developing adetailed model representation for water network regenerationsynthesis using a MINLP optimization framework. This workof was, however, limited to a single regenerator with a fixeddesign. In a more recent development, Yang et al. (2014)proposed a unifying approach by combining multiple watertreatment technologies capable of treating all major contam-inants. The work focused on unit-specific short-cut costfunctions in order to gain detailed understanding of trade-offs between efficiency of treatment units and the cost of theunits, as well as the impact on the unit design. To date, allthe work on water and membrane regeneration has focusedon minimizing water usage and the cost functions of thewater networks. No effort has been devoted to thesimultaneous synthesis of the membrane regeneration unitsand water network for water and energy minimization.

The membrane technologies adopted in the current workare electrodialysis (ED) and reverse osmosis (RO).Electrodialysis is based on the electromigration of ionsthrough cation and anion exchange permselective membranesby means of an electrical current (Korngold, 1982; Tsiakisand Papageorgiou, 2005; Strathmann, 2010). Industrialapplications of ED include brackish water desalination, boilerfeed and process water, and wastewater treatment(Strathmann, 2010). The current work employs insights onthe mathematical relations in the work of Lee et al. (2002)and Tsiakis and Papageorgiou (2005).

RO is a pressure-driven membrane separation processthat selectively allows the passage of one or more speciesthrough the membrane unit. Industrial applications of ROinclude municipal and industrial water and wastewatertreatment. It has also gained widespread industrial usage inpartitioning regenerators to enhance water quality for re-use/recycle (Garud et al., 2011). A detailed mathematicalmodel of an RO unit that allows for process simulation andoptimization has been developed by El-Halwagi (1997).

In the application of membrane systems as regeneratorsin water network optimization for wastewater reduction, anenormous amount of energy is used. Most published work,however, uses linear cost functions and ’black-box’ represen-tation for membrane partitioning regenerators (Alva-Argáezet al., 1998; Tan et al., 2009; Khor et al., 2012). This doesnot result in an accurate cost representation of the membranesystems. There is thus an opportunity for energyminimization through detailed synthesis of membraneregeneration systems in order to obtain optimal variables thataffect the operation and economics of the regenerator unit.

The main objective of the current work is to develop anintegrated water and membrane regeneration networksuperstructure that incorporates possibilities for water andenergy minimization. The membrane regenerators in thisrepresentation are ED and RO. The choice of regenerators ismotivated by the increasing use of membrane technology for

water treatment in the process and mining industries, andalso the potential of different membrane systems to treatspecific ranges of waste. A detailed synthesis of themembrane regeneration systems is conducted to determineoptimal operating conditions for efficient energy usage interms of costs. The detailed model of the regenerators isincorporated in the overall water network objective functionin order to minimize fresh water and energy consumption,and also give a true representation of costs as compared tothe ‘black-box’ method. The idea of using variable removalratios to describe the performance of regenerators is alsoexplored.

The main aim of this study is to develop a water networksuperstructure for the synthesis of a combined water andmembrane network for water and energy minimization basedon the following data:

➤ A set of water sources, J, with known flow rates andcontaminant concentrations

➤ A set of water sinks, I, with known flow rates andknown maximum allowable contaminant concen-trations

➤ A set of membrane regeneration units, R, with thepotential for parallel/series connection for partialtreatment of wastewater from sources for re-use/recycle

➤ A fresh water source, FW, with known concentration,and variable and unlimited flow rate

➤ A wastewater sink, WW, with maximum allowablecontaminant concentration, and variable and unlimitedflow rate.

The following outputs are required:➤ The minimum fresh water intake and wastewater

generation, the energy consumed in the ED and ROunits, and the total annualized costs for ED (TACe) andRO (TACr)

➤ Optimal water network configuration➤ Optimum design variables of the regenerators.

Based on the problem statement, the water networksuperstructure in Figure 1 is developed. The superstructurerepresentation is an extension of the work by Khor et al.(2011). The superstructure in this work incorporates multipleregenerators which are open for parallel and seriesconnection as well as recycle and re-use of both permeate andreject streams from the regenerators. The fixed flow rateapproach adopted in this work considers water-usingprocesses in terms of sources and sinks that generate orconsume a fixed amount of water respectively. Total fixedflow rate is adopted because it presents a general represen-tation of water-using operations based on both mass transferand non-mass transfer (Khor et al., 2012).

This work considers four different cases, all of which arebased on the superstructure given in Figure 1.

➤ Single contaminant, multiple ED units➤ Multiple contaminants, single ED unit➤ Multiple contaminants, multiple RO units

▲

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➤ Single contaminant, ED and RO unitsFor each of the cases considered the model is applied to a

case study. For comparison, different modelling scenarios arepresented for each case.

This case considers the synthesis of an optimal waternetwork with multiple ED regenerators using a singlecontaminant framework. The model is made up of waterbalances of the entire network and the mechanistic model ofthe regeneration network. The detailed model of theregeneration subnetwork incorporated in the network allowsfor the design of the subsystem.

To ensure connectivity between the regeneration network, thesources, and the sinks, water balances are established basedon the superstructure presented in Figure 1. The flow balancefor the source is modelled as:

[1]

The balance for the fresh water source is modelled in asimilar way. Material balances on the regeneration networkshow the connectivity between individual regenerators andthe rest of the water network. The water balance around themixer preceding each regenerator can be modelled as:

[2]

Depending on the design of the regenerator, eachregenerator has a limit to the amount of contaminant that it

can tolerate. In this regard, the corresponding contaminantbalance for the regenerator feed was modelled as:

[3]

Similarly, the water balances for the two splittersconnected to the regenerator diluate and concentrate streamsare given by the constraints in Equations [4] and [5] respec-tively.

[4]

[5]

The flow balance for the sink is modelled as:

[6]

The balance for the wastewater sink is modelled in asimilar way. The maximum allowable load that each sinktolerates has to be taken into account. As such, thecorresponding contaminant balance for each sink can bemodelled as:

[7]

The model formulation for the detailed design of the EDregeneration unit is based on the work by Tsiakis and


1145 ▲


Papageorgiou (1995) and Lee et al. (2002). Figure 2 is aschematic representation of a typical ED unit. For computa-tional simplicity, one stage per regenerator is assumed.

The following assumptions are made in order to describethe plant using a set of mathematical equations describing itsoperation.

➤ The fluids considered are Newtonian and have steady,fully developed, incompressible laminar flow

➤ The unit is operated under a co-current set-up➤ Concentrate and diluate cells have identical geometry

and flow patterns and changes in the ohmic resistanceof the solutions are negligible (Tsiakis andPapageorgiou, 1995)

➤ The concentrations of the salt species are operatedusing molar equivalents

➤ Water transportation across the membrane is negligiblecompared to the concentrate and diluate stream flowrates (Tsiakis and Papageorgiou, 1995)

➤ To avoid the collapse of the membrane system due topressure differences it is assumed that the immediatediluate and concentrate streams have the same flowrate.

Water balances as well as corresponding contaminantbalances for each regenerator were conducted in accordancewith Figure 2. With regard to the design aspect of EDregenerator, important variables and physical parameters ofthe ED are incorporated in the mathematical relations thatdescribe the performance of the regenerator. The electricalcurrent required to drive the ED process is given by:

[8]

The extent of desalination obtained by an ED unit isdependent on the membrane area, Ar, which based on Tsiakisand Papageorgiou (1995), and given by:

[9]

where, Cr is the concentration difference across a stage(Cf

r – Cdilr). F

pr is the diluate stream flow rate from the

regenerator, r, which is expressed by Equation [10].

[10]

where α is the spacer shadow factor. The required processpath length for the ED stack can be expressed in terms of themembrane area, Ar, the cell width, w, and the number of cellpairs, Nr, as follows:

[11]

The direct energy required for the process is dependentupon the voltage and current applied on each stack. Thevoltage applied can be expressed as follows:

[12]

The specific energy required for desalination is definedby:

[13]

The specific pumping energy, Erpump, required for the

process is directly linked to the pressure drop, Pr, forlaminar flow across the unit and is given by:

[14]

where

[15]

The regeneration subnetwork involves both capital andoperational costs. The representative total annualized cost(TAC) function for the regeneration network is given byEquation [16]. This function is included in the overallobjective function of the water network, such that the energyconsumption and subsequent cost of regeneration areminimized in conjunction with water consumption. Themodel is enabled to select only the necessary regeneratorsthat result in an optimal solution by prefixing the TACfunction with a binary variable, yr

ED , which becomes zerowhen the respective unit is not activated.

[16]

The objective is to minimize the total annualized cost of thewater network, which comprises the fresh water cost,wastewater treatment cost, annualized regeneration cost, aswell as the capital and operating cost of piping. Theformulation of the objective function is expressed in Equation[17].

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1146

[17]

where

is an annualization factor. It is assumed that all the pipesshare the same p and q parameter properties, stream velocityv, and 1-norm Manhattan distance. The resultingmathematical model is a MINLP problem that was solvedusing GAMS/DICOPT with CPLEX as the MILP solver andCONOPT 3 as the NLP solver. BARON was used to solve theRMINLP problem.

The mathematical model developed is applied to a literature-based pulp and paper plant case study (Chew et al., 2008). Theindustry produces a lot of ionic effluent and also involvesmiscible water networks, whereby the mixing streams losetheir identities as they mix. This renders the fixed flow rateframework adopted in the model ideal for this particular plant(Poplewski et al., 2010). The limiting data is shown in Table I.

Three scenarios are considered. Scenario 1.1 is waterintegration without regeneration. Scenario 1.2 considers awater network with one detailed ED regenerator withcapabilities of recycle within the regeneration subnetwork.

Note that within this scenario two cases were considered; thatis, the case where the removal ratio of the regenerator isfixed at 0.733 and the case where it is variable. For the casewhere the removal ratio is fixed, an arbitrary value is chosen.Scenario 1.3 is similar to scenario 1.2 except that it has thecapability of using two regenerators. Fixed removal ratios of0.733 and 0.950 for the first and second regenerators,respectively, are chosen for the fixed removal ratio case.

Comparisons of the presented cases show that Scenario1.3 is the most preferable, since the largest amount of waterwas treated at the lowest total cost, thereby minimizing thefresh water intake and wastewater generation. It is evidentfrom Table II that by allowing the solver to choose theoptimal configuration within the regeneration subnetwork interms of recycles, series and parallel connections, as well asmaking the removal ratio and number of regeneratorsrequired variable, there is the possibility of obtaining bettersolutions rather than fixing them arbitrarily beforehand. Inthis way the designer gains more control of the unitperformance by being able to stipulate the requiredmembrane characteristics to the manufacturer.

The results also show that incorporating multipleregenerators can increase the chances of a better optimalsolution, as long as the regenerators are not forced into thesystem. In this case this situation was handled by the binaryvariable yr

ED that represented the existence of a regeneratorwhich allowed the optimization tool to decide on the optimumnumber of regenerators. Figure 3 shows the optimal networkconfiguration and flow rates for the best-case scenario. Allflowrates are reported in kg/s.

With this configuration in place, the plant is capable ofgenerating savings of up to 12.7% in fresh water intake,


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1 247.3 0.000003 1 388.75 0.0342 40.3 0.2696 2 40.28 03 28.4 0.000014 3 160.06 0.000 3704 860.8 0.4998 4 860.8 0FW ∞ 0 WW ∞ 0.3983

Fresh water intake (kg/s) 1134 1055 1023 1006 989Wastewater generation (kg/s) 861 782 750 733 716Total water regenerated (kg/s) 0 596 217 699 586Total cost (million $) 56.9 52.7 50.8 50.2 48.9Optimal RR* - - r1= 0.867 - r1= 0.779

r2= 0.770CPU time (s) 0 8 72 6129 17 230*RR:-removal ratio


reduction of up to 16.2% in wastewater generation, and a14.1% saving in the total annualized cost compared to theworst-case scenario. The optimal regenerator design suggestsan installation of two regenerators, r1 and r2, one with 2880cell pairs and the other with 4356, amounting to a totalmembrane area of 3837 m2 and 3921 m2 respectively. It isnoteworthy that the CPU time incurred was high for scenario1.3, due to the nature and complexity of the model.

In this case, it is necessary to develop a multicontaminantmodel for ED design. This requires the consideration of theionic interaction between the different components within theED unit, and the impact of these interactions on the unitdesign. In the following formulation, the subscript r isomitted from the notation because only a single regeneratoris considered.

The individual concentrations of the contaminants feedinginto the ED unit are combined using an equivalent concen-tration expression, as defined in Equation [18],wheresubscripts c, a, and s denote the cation, anion, and saltrespectively. All calculations pertaining to the ED unit wereperformed using an equivalent concentration. However, thesubscript eq has been omitted for clarity.

[18]

The calculation of equivalent concentration must beperformed in all streams entering and exiting the ED unit asfollows:

[19]

[20]

[21]

The solution conductivity is a fundamental property ofthe fluid that plays an integral part in determining the EDdesign. It must, therefore, be determined based on the actualconcentration of the contaminants that enter the unit. Thiscan be done empirically or analytically by the use of conduc-tivity-concentration relationships such as the Deybe-Hückel-Onsager. The latter approach is adopted in this work. It isimportant to note that as the complexity of the electrolytesincreases, such relationships become less accurate, andexperimental determination of the dependence of solutionconductivity on salt concentration is advised. The Deybe-Hückel-Onsager equation is given by Equation [22]:

[22]

where Λ° is the electrolyte conductivity at infinitedilution. This value can be obtained from the literature. Theconstants A and B are dependent on temperature, valence,and viscosity, and for dilute solutions at 25°C it can beassumed that A = 60.58z3 and B = 0.22293z3, where z is thevalence of the salt (Wright, 2007). Once the conductivities ofthe individual salts are known, they are then combined toresult in the solution conductivity using the mixingrelationship for binary systems.

[23]

In this expression, a refers to the fraction of the salt inthe solution and κ is the specific conductance of the solutionor the individual components. In order to relate the specificconductance to the solution conductivity, the followingrelationship is employed

[24]

▲

1148

This expression can be applied to both the individualelectrolytes and the overall solution. The combination ofthese three equations allows one to calculate the conductivityof a solution given the individual concentrations and theirinfinite conductivities.

The following ED energy minimization model was developedfor a single-stage process. The electrical current is determinedusing a modified form of Faraday’s law. This expressionrelates the driving force with the physical characteristics ofthe plant, the required capacity and the degree of desali-nation. Either the cationic or anionic valence and stoichio-metric coefficients may be used in Equation [25].

[25]

The practically applied limiting current density, beyondwhich the ED must not operate, is given by the empiricallydetermined relationship:

[26]

Coefficients σ and φ are experimentally determinedconstants, u is the fluid velocity, and ε is a practicality factorthat relates the limiting current density to the unit’s flowpatterns.

While many of the design constraints are similar to the singlecontaminant case as described above, some modificationsmust be made to incorporate the equivalent concentrationsfor the multicontaminant case. The total length of the EDstack is given by the following relationship:

[27]

The conductivity, Λ, is determined using the constraintsin Equations [22]–[24]. The corresponding requiredmembrane area is determined as a function of the path lengthand the cell width. A correction factor, β, is introduced toaccount for the effect of the spacers.

[28]

The energy consumption in an ED unit can be attributed tothe migration of electrons across the membranes as well asthe energy required to pump fluids through the unit.Assuming that operation is ohmic, i.e. current density doesnot exceed limiting current density, the voltage across theunit is given by:

[29]

The specific energy for desalination and pumping energyare subsequently calculated using Equations [13] and [14].

The water network and ED model culminate in an overall costfunction to be minimized, given by Equation [30]. All pipesare assumed to operate at the same fluid velocity, up, and usethe same costing coefficients p and q. The piping cost iscalculated as a function of the Manhattan distance, D,between any two units.

[30]

The above model is applied to a pulp mill and bleached paperplant adapted from Chew et al. (2008). In the originalscenario, shown in Figure 4, four separate fresh water feedsare used, with a total consumption of 8500 t/d, and fourseparate effluent streams are produced, totalling 10 500 t/d.

Two contaminants were identified, namely NaCl andMgCl2. The flow rates and contaminant concentrations of thesources and sinks are detailed in Table III. Two processintegration scenarios were compared. In both cases, themodel was solved using GAMS/BARON.

➤ Scenario 2.1: a ‘black-box’ model is used and thecosting of the actual required ED unit is performedseparately, i.e. water minimization only

➤ Scenario 2.2: simultaneous minimization of water andenergy, using the developed model. Input data for theED units was kept constant for comparison between thetwo scenarios.

In this scenario, the objective is water minimization. The waterregeneration is represented only by a constant removal ratioand a linear cost expression. The actual ED cost is determinedbased solely on the throughput. The results from the WNS arethen input to a standalone ED model in order to determine thetrue cost of regeneration under these conditions.

A full range of results is given in Table IV. Simple waterminimization results in a 36% saving in fresh water and 60%reduction in wastewater generated, compared to the originalplant. A comparison between the estimated and true costs ofregeneration highlights the inaccuracies involved when alinear cost function is applied to a nonlinear membraneprocess. The linear cost function considers only the flow rateof feed to the ED; the true cost is determined by all aspects ofthe units design. Table IV shows that there is an 85%discrepancy between the ‘black-box’ estimate of regenerationcost and the cost of the actual required ED unit under thesame conditions. The ‘black-box’ approach presents the riskof misrepresenting the water network, resulting insuboptimal solutions.

In the water and energy minimization case, the entire model,including the detailed ED, was used, with the same inputs asin the first scenario. The final plant configuration is shown inFigure 5.


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▲

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Stripper 1 2.07 0 0 Washer 3.26 0.0046 0.0004Screening 0.34 0.046 0.035 Screening 0.34 0.0125 0.0007Stripper 2 0.24 0 0 Washer/filter 1.34 0 0Bleaching 7.22 0.026 0.0002 Bleaching 7.22 0.0002 0.00003Fresh water Variable - - Wastewater Variable 0.01 0.01

Fresh water 2 814.86 1 776.00 1 776.00 1 736.70Wastewater 3 468.12 1 122.80 1 122.80 1 083.50Regeneration cost (energy) - 3.90 26.08 5.25Piping - 92.40 92.40 86.62Total cost 6 282.98 2 995.10 3 017.28 2 912.07* Costs are given in $1000/annum

A comparison between the ED units from scenarios 1 and2 shows that when the optimization of the ED is embeddedinto the water network the required unit has a more conser-vative design and therefore consumes less energy. Table Vshows key variables determined in the optimization,highlighting the comparison between the two scenarios. Theintegrated approach, therefore, results in an 80% reduction inthe overall cost of the ED unit required.

Key characteristics of the models are presented andcompared in Table V. While the model sizes are similar, thetime taken to solve the integrated model (scenario 2) wasclose to 21 hours, while the ‘black-box’ (scenario 1) requiredonly 2 minutes. This can be attributed to the nonlinearity ofthe ED model combined with the already nonconvex WNSmodel. It is necessary, therefore, to further develop the modelto reduce its computational complexity, which will constitutefuture work.

This case work proposes a superstructure optimization for thesynthesis of a detailed RON within a WNS. A rigorousnonlinear RON superstructure model, which is based on thestate space approach by El-Halwagi (1992), is included in theWNS to determine the optimum number of RO units, pumps,and turbines required for an optimal WNS. A fixed flow ratemodel that considers the concept of sources and sinks isadopted. The model takes into account streams with multiplecontaminants. The idea of using a variable removal ratio todescribe the performance of the regenerators is also exploredin this case. The water balances are similar to those proposedin case 1.

The characteristics of the RO membrane need to be describedin order to relate flow rate to pressure. The pressure dropacross the membrane ΔPr is given in Equation [31] (Khor etal., 2011). The equation was simplified by assuming a linear-shell side concentration and pressure profiles (El-Halwagi,1997).

[31]

The osmotic pressure, r , is defined as a function of thecontaminant concentration on the feed side (Saif, Elkamel,and Pritzker, 2008a) and is shown in Equation [32].

[32]


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Area m2 438 144Number of cell pairs - 353 229Desalination energy kWh/a 105 494 18 476Pumping energy kWh/a 912.3 18.32Total cost $/annum 26 083 5 216


The permeate flow rate per module is given in Equation[33].

[33]

The average concentration Cq,mav on the feed side is given

by Equation [34].

[34]

The concentration of contaminants on the feed side mustalso be described in terms of the pressure drop and theosmotic pressure. This is described in Equation [35].

[35]

A mass and concentration balance around the regeneratoris also needed and is described in Equations [36] and [37]respectively.

[36]

[37]

The objective function of the combined RON superstructureand WNS is used to minimize the overall cost of theregeneration network on an annualized basis which consistsof:

➤ TAC of the RON➤ Cost of fresh water (FW)

➤ Treatment cost of wastewater (WW)➤ Capital and operation costs of the piping intercon-

nection.The total annualized cost of the RON consists of the

capital cost of the RO modules, pumps, and energy recoveryturbines, operating cost of pumps and turbines, as well aspretreatment of chemicals. The operating revenue of theenergy recovery turbine is also considered in the determi-nation of the TAC and is shown in Equation [38]. The set nrepresents the mixing node before a regenerator unit and isused to connect the water network to the RON superstructure.

[38]

The piping cost of components is formulated by assuminga linear fixed-charge model. In the formulation, a particularcost of a pipe is incurred if the particular flow rate throughthe pipe falls below the threshold value. This is achieved byusing 0-1 variables. Equation [39] represents the objectivefunction of the total regeneration network.

[39]

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Fresh water flow rate (kg/s) 28.87 27.68Wastewater flow rate (kg/s) 3.91 2.72Cost of regeneration ($ million/year) 0.23 0.096Total cost ($ million/year) 1.32 1.11Network configuration Parallel ParallelNumber of HFRO modules 37 for each regenerator 15 for each regeneratorCPU time (h) 6 54

(kg/s) TDS COD (kg/s) TDS COD1 7.3 3.5 3.5 1 0.83 2.5 2.52 10.65 4 4 2 40 2 23 3.5 1 3 3 5.56 2.5 2.5FW 2 1 WW 25 25

The overall model results in a nonconvex MINLP due tothe bilinear terms as well as the power function in theconstraints.

The above model was applied to a petroleum refinery casestudy based on the work presented by Khor et al. (2011).The model was implemented in GAMS 24.2 using the generalpurpose global optimization solver BARON, which obtains asolution by using a branch-and-reduce algorithm. Thenetwork consists of four sources and four sinks. The limitingwater data for the sources and sinks is given in Table VI.

Table VII shows the comparison between a case wheremultiple regenerators with fixed (scenario 3.1) and variableremoval ratio (scenario 3.2) were used. The removal ratiochosen by the model in scenario 3.2 was 0.97 for all contam-inants instead the fixed value of 0.95 in scenario 3.1.Scenario 3.2 led to 3.12% reduction in fresh water and30.43% reduction in wastewater generation in comparisonwith scenario 3.1. A 15.91% reduction in the total networkcost was also achieved. The large decrease in the total cost ofthe network in scenario 3.2 can be attributed to the higherremoval ratio selected by the model than the value that wasinitially predicted. The modelling of scenario 3.2 is, however,computationally expensive as can be seen in Table VII.

Figure 6 shows the water network for scenario 3.2 withthe corresponding flow rate for each stream. The best caseused 15 HFRO modules per regenerator. The model selectedtwo regenerators, two pumps, and two energy recoveryturbines, as can be seen in Figure 6. It can also be seen that aparallel configuration of the network was chosen by the

model. In comparison with the case where no regenerationwas considered, scenario 3.2 leads to a 28% reduction infresh water consumption and 80% reduction in wastewatergeneration.

The long computational time for solving the model inscenario 3.2 was due to the complexity of the problem as wellas the large number of 0-1 variables. The model solvesquicker when tighter bounds are imposed on the feed andretentate pressure. The use of the energy recovery turbines inthe RON led to a reduction in the regeneration cost of thenetwork, and as a result, a reduction in energy usage by thesystem was achieved.

In this case, an integrated water network of ED and RO unitis developed with the possibilities of water and energyminimization. The choice of regenerators is motivated by theincreasing demand for and use of membrane technology forwater treatment and also the varying potential of differentmembrane systems to treat specific waste ranges.

The model formulation in this representation includedconstraints for mass and concentration balances of the EDand RO units in cases 1 and 2, detailed formulation of the EDand RO unit respectively, and the overall total annualizedcosts of both regeneration units represented in cases 1 and 2,which is incorporated in the objective function as follows.


1153 ▲


Equation [40] represents the objective function thatminimizes the overall annualized cost of the water network.This includes fresh water cost, wastewater treatment cost,and annualized regeneration cost, as well as capital andoperating costs of piping interconnections. The costs relatedto piping are accounted for by specifying an approximatelength of pipe, the material of construction, and linearvelocities through the pipes.

[40]

A 1-norm Manhattan distance is considered for all pipinginterconnections. All pipes are assumed to be of the samematerial of construction; as a result, the carbon steel pipeparameters of p and q are adopted for the piping costs. Af isthe annualization factor adopted from Chew et al. (2008)which is used to annualize the piping cost. The resultingmathematical model is a MINLP. The nonlinear terms are dueto the presence of bilinear terms in mass balance equationsand power terms in the cost functions of regeneration units.The MINLP model was solved using GAMS 24.2, using thegeneral-purpose global optimization solver BARON.

The developed mathematical model is verified and applied tothe pulp and paper case study adopted from Chew et al.(2008). The choice of the case study is motivated by the highamount of ionic components produce by the pulp and paper

industry. Moreover, the pulp and paper industry involvesmiscible phase networks that consist of water-water systemswhere streams lose their identities through the mixingprocess, hence the case study is suitable for a fixed flow ratemethod adopted for this work.

Table VIII shows the basic data for the plant waternetwork, which comprises five water sources, including thefresh water source, and five water sinks, including the wastesink.

The case study was applied to three different model casesin order to ascertain the benefits of incorporating a detailednetwork of the membrane regeneration units in theconstraints of the water network.

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1 2.07 0.0002 1 3.26 0.000572 0.34 0.0051 2 0.34 03 0.024 0 3 1.34 6.16x10-64 7.22 0.0083 4 7.22 0FW 0 WW 0.01

Optimal results of water network based on the case study

Fresh water use (kg/s) 18.300 11.145 10.012 11.183 10.189% of freshwater savings 39.1 45.3 38.89 44.32Wastewater generated (kg/s) 15.785 8.958 7.796 8.996 7.742% of wastewater saved 43.2 50.6 43.01 50.95Total cost of water network ($) 1.170×106 5.97×105 5.08×105 6.26×105 5.66×105

CPU time 0.06 865 2764.20 687.50 16709.78

Nr 50Ar (m2) 54.375Lr (m) 0.821Ir (A) 12.447vr (m/s) 0.01Ur (V) 30.152Er

spec (J/s) 0.021Er

pump (J/s) 0.004ΔP (kPa) 16.303Fr

f (kg/s) 1.025RRr 0.8Nr

s 10Pr

f (kPa) 5.73×105

Prq (kPa) 5.33×105

Δ r (kPa) 1.63Fr

f (kg/s) 0.72

➤ Scenario 4.1 considered a model of the water networkwithout regeneration

➤ Scenario 4.2 considered a model of water network withregeneration units based on the ’black-box’ approach

➤ Scenario 4.3 considered a detailed synthesis of theregeneration units incorporated into the overall waternetwork objective function.

For scenarios 4.2 and 4.3, the optimization wasconducted for both a fixed and a variable removal ratio. Forcomparison, in both scenarios the removal ratio had a fixedvalue of 0.7.

The optimal results for all scenarios are presented inTable IX. Scenario 4.1 represents the water network modelwithout regeneration. Scenario 4.2 represents the ’black-box’formulation with both fixed and variable removal ratios. Theresults showed a reduction in fresh water consumption,wastewater generation, as well as the total annualized waternetwork cost as compared to the non-regeneration scenario.The results of scenario 4.3 are displayed in Figure 7. For bothfixed and variable removal ratios scenario 4.3 showedsignificant reduction in water network cost as well as freshwater consumption and wastewater reduction as compared tothe direct water network model without regeneration.However, there was an increase in the total water networkcost of scenario 4.3 for both the fixed and the variableremoval ratios cases compared to scenario 4.2. This is aresult of scenario 4.3 being a true representation of the totalwater network, as it incorporates a detailed design of themembrane regeneration units and gives an accurateexpression of the regeneration cost compared to the linearcost function of scenario 4.2, which uses the ’black-box’method.

From the results in Table IX it is evident that the variableremoval ratio in case 3 presents the optimal configuration,since the model is allowed to choose the performanceparameters of the membrane regenerators. The results also

show that incorporating multiple membrane regeneratorswith different performance and inlet and outlet contaminantlimits in a water network can lead to an optimal use of freshwater. The inlet contaminant limits were set at different levelsin order to allow the membrane regenerators various optionsfor contaminant treatment. The variable removal ratio modelin scenario 4.3 proves to be the optimal results for the casestudy as represented in Figure 7. The configuration showedthat regeneration re-use and recycle within the water networkbetween the regenerators resulted in a 44.3% reduction infresh water consumption, 50.9% reduction in wastewatergeneration, and 45% savings in the total annualized waternetwork cost as compared to case 1. Table X shows thedesign results of the ED and RO units respectively.

This work addresses the synthesis of a multi-membraneregeneration water network by proposing a water networkmodel that incorporates detailed models of ED and ROregenerators. Different cases were considered under whichthe respective MINLP models were developed, and for eachcase a relevant literature case study was applied todemonstrate the applicability of the proposed model. Overall,the results showed that the use of a detailed modelguarantees more accurate and reliable results in terms ofwater network synthesis as well as regenerator design.Savings of up to 44% in fresh water intake and reductions ofup to 80% in wastewater generation and 45% in the totalannualized cost were obtained. Additionally, because adetailed regenerator model presents an expression of theregeneration cost, it also gives optimal regenerator operatingvariables for minimal energy usage, thereby illustrating theinadequacy of the ‘black-box’ approach to superstructureoptimization. Energy savings up to 82% were achieved. Theresults also showed an added advantage in setting the


1155 ▲


regenerator removal ratio as compared to fixing it arbitrarily.It is noteworthy that although the proposed models cater onlyfor ED and RO regeneration technologies, they offer scope forfuture work, and the problem can be extended to incorporateother membrane technologies such as ultrafiltration, microfil-tration, and nanofiltration.

J {j|j=water source}I {i|i=water sink}M {m|m=contaminants}R {r|r=regeneration units}

Dj,is Manhattan distance between source j and sink i

Dr,id Manhattan distance between regenerator r and sink, i

Dr,r'y Manhattan distance between regenerators r and r’

Dj,rk Manhattan distance between source j and regenerator

rDj,n

da Manhattan distance between source j and node nPr

m Shell side pressure drop per modulePr

P Pressure of a permeate stream from regenerator rμ Solution viscosityA Water permeability coefficientAf Annualization factoraLCD LCD constantbLCD LCD constantCchem Cost parameter for chemicalsCelec Cost of electricityCFW Fresh water costCmod Cost per module of HFRO membraneCpump Cost coefficient for pumpCtur Cost coefficient for turbineCWW Wastewater treatment costF Faraday constantkel Cost of electricitykm Solute permeability constantkmb Cost of membranektr Conversion factorLRr Liquid recovery for regenerator rm Interest rate per yearn Maximum equipment lifeOS Proportionality constant between the osmotic pressure

and average salt mass fraction on the feed sidep Parameter for carbon steel pipingq Parameter for carbon steel pipingSm Membrane area per moduletd Operating time per yearv Pipe linear velocityw Cell widthz Valenceα Spacer shadow factorβ Volume factorδ Cell thicknessε Safety factorζ Current utilizationη Pumping efficiency

ηpump Pump efficiencyηtur Turbine efficiencyλ Equivalent conductanceΛ° Infinite conductivityρ Total membrane resistanceσ,φ Limiting current density constantsϒ Dimensionless constant

TACr Total annualized cost for regenerator rAr Membrane area required by regenerator rEr

spec Specific desalination energy required by regenerator rEr

pump Specific pumping energy required by regenerator rIr Electrical current required by regenerator rLr Stack lengthvr Linear flow velocity at stage sUr Voltage appliedPr Pressure drop across the regenerator

Frf Regenerator feed flow rate

Frdil Final diluate stream flow rate of regenerator r

Frp Diluate stream flow rate for regenerator r

Frw Concentrate stream flow rate for regenerator r

Frcr Concentrate stream recycle flow rate for regenerator r

Frr Recycle stream flow rate for regenerator r

Frcon Final concentrate flow rate for regenerator r

Fr,id Diluate flowrate to sink i

Fr,ic Concentrate flow rate to sink i

Fj Source flow rateFj,r

k Flow rate from source j to regenerator rFj,i

s Flow rate from source j to sink iFr,r'

x Recycle from diluate stream to regenerator feedFr,r'

y Recycle from concentrate stream to regenerator feedFi

b Sink i flow rate requirementsCr

f Regeneration feed concentration for regenerator rCr

wf Concentration of feed concentrate stream forregenerator r

Crcr Concentration of recycling concentrate for regenerator

rCr

w Concentration of concentrate waste stream forregenerator, r

Crdil Diluate contaminant concentration

Crcon Concentrate contaminant concentration

SrU Maximum allowable regenerator concentration

Cj Source concentration of Ci

U Maximum allowable sink concentrationFj,n

da Allocated flow rate between sources j and node nFr,i

pe Flow rate of the permeate stream from regenerators rto sinks i

Fr,jq Flow rate of the retentate stream from regenerators r

to sinks iFn

a Flow rate of streams from re node nPn

a Pressure of streams leaving node nPn

i Pressure of an inlet stream to an energy recoveryturbine from node n

Pno Pressure of an outlet stream from an energy recovery

turbine from node nPr

q Pressure of a retentate stream from regenerator rCr,m

av Average concentration of contaminant m in the high-pressure side of regenerator

Cr,mf Concentration of contaminant m in the feed to the

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regenerator rCr,m

pe Concentration of contaminant m in permeate streamleaving regenerator r

Frpe Flow rate of permeate/diluate stream leaving the

regenerator rFr

q Flow rate of retentate stream leaving the regenerator rCr,m

q Concentration of contaminant m in retentate streamleaving regenerator r

Prf Feed pressure into regenerator r

Ceq Equivalent concentrationFW Fresh water flow rateiprac Practical limiting current densityRRr Removal ratio for regenerator rWW Waste water flow rateΔPr Pressure drop over regenerator rΔ r Osmotic pressure on the retentate side of regenerator

rκ Specific conductanceΛ Equivalent conductivity

Nrs Number of hollow fibre modules of regenerator r

Nr Number of cell pairs per ED

The authors would like to thank the National ResearchFoundation (NRF) for funding this work under the NRF/DSTChair in Sustainable Process Engineering at the University ofthe Witwatersrand, South Africa.

AHMETOVIC, E. and GROSSMANN, I.E. 2010. Strategies for global optimization ofintegrated process water networks. 20th European Symposium onComputer Aided Process Engineering – ESCAPE20. Pierucci, S. and BuzziFerraris, G. (eds). Elsevier.

ALVA-ARGÁEZ, A., KOKOSSIS, A., and SMITH, R. 1998. Wastewater minimizationof industrial systems using an integrated approach. Computers andChemical Engineering, vol. 22. pp. 741–744.

BAGAJEWICZ, M. and SAVELSKI, M. 2001. On the use of linear models for thedesign of water utilization systems in process plants with a singlecontaminant. Waste Management, vol. 79. pp. 600–610.

BANDYOPADHYAY, S. and CORMOS, C.-C. 2008. Water management in processindustries incorporating regeneration and recycle through a single unit.Industrial and Engineering Chemical Research, vol. 47. pp. 1111–1119.

CHEW, I.M.L., TAN, R., NG, D.K.S., FOO, D.C.Y., MAJOZI, T., and GOUWS, J. 2008.Synthesis of direct and indirect and interplant water and network.Industrial and Engineering Chemical Research, vol. 47. pp. 9485–9495.

DOYLE, S.J. and SMITH, R. 1997. Targeting water reuse with multiple contam-inants. Process Safety and Environmental Protection, vol. 75, no. 3. pp. 181–189.


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EL-HALWAGI, M. 1997. Pollution Prevention through Process Integration.Academic Press, San Diego.

ROSSITER, A.P. and NATH, R. 1995. Wastewater Minimization using NonlinearProgramming. McGraw-Hill.

SALVESKI, M. and BAGAJEWICZ, M. 2000. On the optimality conditions of waterutilization systems in process plants with single contaminants. ChemicalEngineering Science, vol. 55. pp. 5035–5048.

STRATHMANN, H. 2010. Electrodialysis, a mature technology with a multitude ofnew applications. Desalination, vol. 264. pp. 268–288.

TAKAMA, N., KURIYAMA, T., SHIROKO, K., and UMEDA, T. 1980. Optimal planning ofwater allocation in industry. Computers and Chemical Engineering, vol. 4,no. 80. pp. 251–258.

TAN, R.R., NG, D.K.S., FOO, D.C.Y., and AVISO, K.B. 2009. A superstructuremodel for the synthesis of single-contaminant water networks withpartitioning regenerators. Process Safety and Environmental Protection,vol. 87, no. 9. pp. 197–205.

TAWARMALANI, M. and SAHINIDIS, N.V. 2005. A polyhedral branch-and-cutapproach to global optimization. Mathematical Programming, vol. 103,no. 2. pp. 225–249.

TSIAKIS, P. and PAPAGEORGIOU, L.G. 2005. Optimal design of an electrodialysisbrackish water desalination plant. Desalination and the Environment, vol.173, no. 2. pp. 173–186.

YANG, L., SALCEDO-DIAZ, R., and GROSSMANN. E.I. 2014. Water networkoptimization with wastewater regeneration models. Industrial andEngineering Chemistry Research, vol. 53. pp. 17680–17695.

WANG, Y.P. and SMITH, R. 1994a. Wastewater minimization. ChemicalEngineering Science, vol. 49, no. 94. pp. 981–1006.

WANG, Y.P. and SMITH, R. 1994b. Design of distributed effluent treatmentsystems. Chemical Engineering Science, vol. 49, no. 94. pp. 3127–3145.

WRIGHT, M.R. 2007. An Introduction to Aqueous Electrolyte Solutions. Wiley,Chichester, UK. ◆

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There are about 6000 industrial-scale boilersin South African industries today, all usinglower grade coals than they were initiallydesigned for (Johns and Harris, 2009). Thetravelling grate spreader stoker boiler is one ofthe oldest combustion technologies that havebeen in use since the beginning of thetwentieth century (Giaier and Loviska, 1997).However, these traditional coal-fired boilersare still widely used for electricity generationin South African industries. The pulp andpaper, sugar, cement, and many otherindustries use steam to generate power,consuming approximately 9 Mt of coal perannum (SANEDI, 2013). Numerous investi-gations have also been conducted on thecompetitiveness of using existing convectionalcoal-fired utilities, such as grate stoker boilers,in firing and co-firing a wide range of fuels(Li, et al., 2009; Thai, et al., 2011; Sheng etal., 2012). Despite having been in the marketfor many years, coal-fired spreader stokertechnology still presents challenges in regard

to inefficient combustion of coal (Lin et al.,2009). This has always been regarded as atechnical operational problem, rather thanbeing due to the inherent characteristics ofcoal. This investigation is aimed at the studyof feed coals utilized in a specific boiler andthe effects of their properties on the efficiencyof combustion.

Most of the previous research in the fieldof industrial stoker-fired boilers, includingspreader stokers, has been undertaken inEurope and America (Falcon, 2010).Theresults of these studies reside with boilermanufacturers, who rarely publish theirfindings. The only published results that canbe found locally using South African coal(SAC) are limited to investigations conductedmostly by the sugar, pulp, and paperindustries (Falcon, 2010). These studies focusmainly on the effect of operating conditions onboiler performance, and not specifically on theimpact of coal quality. There is thus little or noknowledge on the compatibility of SACs andstoker fired boilers in this country. There isvirtually no published information whichclearly draws the relationship between coalquality, technical operational conditions, andthe efficiency of spreader stoker boilers forSACs. In addition, the characteristics of coalsshould also be well understood if retrofitting ofthe existing boilers is to be successful (Falconand Ham, 1988). It is important that thisstandpoint be fully embraced, especially in theSouth African context because the majority ofthe old boilers were designed by overseasmanufacturers (mostly American and British),using their own types of coal and hardly anylocal coals (Falcon, 2010). This implies thatoriginal designs of most of the old boilers didnot necessarily match SAC types.

The impact of coal quality on theefficiency of a spreader stoker boilerby R.L. Taole*, R.M.S. Falcon*, and S.O. Bada*

This research establishes the combustion characteristics and efficiencies ofSouth African coals of different qualities and their impact on theperformance of a grate spreader stoker boiler. Four different coal sampleswere tested in the particle size range 6.25 × 25 mm. A detailed investi-gation involving the boiler operating conditions associated with thephysicochemical characteristics of the coals, petrographic properties, andtemperature profiles from a thermal camera was conducted. The thermalanalysis indicates that there is a strong correlation between thermographicdata (combustion behaviour and maximum flame temperatures) andpetrographic composition of the coals. This association is not reflected incalorific values and proximate analyses of the coals. In terms ofcombustion efficiencies, all coals yielded relatively high amounts ofunburnt carbon in the fly ash (about 36.90%). The highest steam outputobtained was 41.76 t/h at the highest combustion efficiency of 79.13%.The thermographic results obtained from this study led to the conclusionthat South African low-grade Gondwana coals undergo delayed ignitionand burn at unusually high temperatures (1500–1800°C), which is incontrast to the original belief that the combustion temperature is around1400°C.

coal, combustion, macerals, thermographic camera, travelling grate.

* School of Chemical and Metallurgical Engineering,Faculty of Engineering and the Built Environment,University of the Witwatersrand, Johannesburg

© The Southern African Institute of Mining andMetallurgy, 2015. ISSN 2225-6253. Paper receivedMay 2015 and revised paper received Nov. 2015

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The impact of coal quality on the efficiency of a spreader stoker boiler

This paper attempts to refine the current understanding ofthe effect of varying coal qualities and operating conditionson boiler efficiency in one particular travelling grate spreaderstoker boiler. The study focuses on the combustion character-istics of four different coal samples and their impact on boilerefficiency. An advanced thermographic visual testing systemin the boiler is used to interpret the results, together withpetrographic techniques and conventional physical andchemical analyses (proximate and ultimate analyses).

Four coal samples, identified as A, B, C, and D, of similarcalorific value and different abrasive indexes, were used inthis study. The coals were sourced from separate mines in theWitbank area of South Africa, except for coals A and D whichwere both from the same mine. The coals were crushed to thestandard designed size specified for a spreader stoker boilerat 6.25 × 25 mm. The coal samples were sampled inaccordance with ISO 18283:2006 (E) guidelines in order toobtain the most representative coal fed into the boilerfurnace. The particle size distributions (PSDs), Hardgroveindexes (ASTM D3402), and abrasive indexes (Eskomstandard) of the samples are presented in Table I. The designcoal specification for the spreader stoker boilers utilized inthis study is 6.25 × 25 mm size fraction. The PSDs (Table I)below indicates that coal D has the lowest proportion of finerparticles at 16.47% <6.25 mm, while coal A contained thehighest amount of finer particles at 29.62% <6.25 mm.

Proximate analysis was conducted to determine the totalmoisture (ISO 589: 2008); inherent moisture (SABS925:1978); volatile matter (ISO 562: 1998); ash content (ISO1171: 1997); and fixed carbon (by difference). The ultimateanalysis (ASTM D 5373), along with the calorific value,which is the measure of the heat content, was determined inaccordance with ASTM D5865-04. The total sulphur (ASTMD4239:1997) and species of sulphur (ISO 157) were alsodetermined. Both the bottom ash and fly-ash samples wereanalysed for unburnt carbon (UBC) using the standard ASTMD4239:199 to determine the total carbon concentration. Ashfusion temperature (AFT) was determined for all samples inaccordance to ISO 540, and the results are shown in Table II.

The coals were prepared according to ISO 7404/2 (1998). A

Leica DM4500P petrographic microscope was used for theoptical determination of the organic, inorganic, andassociated components by analysing the microlithotypes,including the carbominerites and minorities analyses. Therank, as indicated by the mean random reflectance, Rr%, is ofthe order of 0.61 to 0.76%, as seen in Table III. In terms ofrank, all coals are of the bituminous C category, with coals Aand D slightly lower in maturity. The flue gas was analysedusing an Orsat apparatus. The gases measured were carbondioxide (CO2), carbon monoxide (CO), and oxygen (O2). Theconcentration of other gases, such as NOx and SOx, in theflue gas was analysed using a gas chromatograph in thelaboratory after capturing the flue gas in a gas pipette andTedlar bags.

The thermographic furnace camera is the main analytical toolin this study. The technique uses infrared radiation to acquireand analyse thermal information using a non-contact thermalimaging device. This provides the capability to differentiatebetween the thermal characteristics of different coal samplesduring combustion. The furnace temperature profiles and thesample flame morphology were studied to understand thethermal behaviour of the samples according to differentcolours emitted during combustion. The video (DURAG typeD-VTA 100-10 series) and thermography system utilizedallows for the analysis of the furnace conditions and thevisualization of the flame temperature profiles during coalcombustion in real time. In addition, the camera provides fortemperature determinations at individual points; such asthermal analysis of local temperature distribution, classifi-cation of temperature-definable measuring windows andlines, referred to as regions of interest (ROIs). The thermo-graphic camera D-VTA100-10 has the following technicaloutput:

Optical field of view 72° horizontal, 54° vertical, and 90°diagonalThermography from a total radiation range: 1000–1800°CCooling water volume 350 l/hCompressed air volume max. 25 Nm3/h.The location of the thermal camera field of view with

reference to the boiler furnace is depicted in Figure 1. Thefigure illustrates a typical arrangement of the thermographicsystem for data capturing in the boiler furnace andconveyance to a programmable logic controller (PLC) system

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%< 6.3 mm 29.62 26.60 21.87 16.47HGI 52 61 59 70AI 246 149 99 94

for operator control and monitoring. In order to perform athermographic test for furnace temperature profiling, thepositioning of the video camera was first defined and used asa reference to the extent of the optical field viewed and ofdata captured. The camera was placed about 1 m above theboiler grate level and from the furnace arch where the coalwas fed into the boiler (Figure 2). This arrangement allowedfor coverage of almost the entire furnace area of interest,based on an optical field of view of 72°.

The water-tube spreader stoker boiler used in this investi-gation has a heating surface area of 169.5 m2, mean heightof 9.98 m, width of 4 m, effective length of 4.8 m, a gratearea of about 19.3 m, and sample feed rate capacity of about42.43 t/h. The boiler has a steam generation capacity of 45t/h, producing saturated steam at 31 bar gauge (barg)pressure. The boiler consists of a negative pressure furnacehouse, an economizer, and an electrostatic precipitator (ESP)for capturing particulates as seen in the layout shown inFigure 3. The full details of the spreader stoker boiler havebeen reported elsewhere (Taole, 2015). The coal is fedthrough coal feeders at the front of the furnace. Lighter coalparticles burn in suspension and the heavier ones fall ontothe grate, burning on it. The grate travels from the back ofthe furnace towards the front, where the ash is discharged.

The boiler was operated under a steady load conditions asfar as possible during the test period, i.e. operations wereallowed to stabilize at least an hour prior to commencementof the tests. Steady-state conditions were determined fromthe analysis of combustion gases in the flue gas stream. Allboiler operating conditions, i.e. the grate speed, coal feederstroke rate, and the under-grate air (UGA) system, whichconveys primary combustion air to the overlying coal bed,were kept constant during the trials, in order to establish theimpact of coal quality on combustion performance. The testswere performed under full-scale operation. Fluctuations inoperating conditions were occasionally experienced, mostlythe grate speed. This led to tests being run on each sampleover a two-day period to constitute two separate samplebatches for the same coal in order to allow for repeatability ofthe results.

The calorific value (CV) of the coals ranges from 25.54 to27.00 MJ/kg. Coal C has the highest CV of 27 MJ/kg andlowest volatile matter content of 23.50%. All four coalsamples are considered to be of reasonably low ash, rangingfrom 14.70 to 17.30%. All the coals utilized contain about0.02%. sulphate sulphur. Pyritic sulphur is higher in coals A(0.78%) and D (0.71%) compared to coal B (0.13%). Thehighest fraction of organic sulphur is also found in coal A at0.66%, while coal B has the lowest proportion at 0.24%. Theultimate analysis results show that the fraction of nitrogenfor the four coals is fairly similar, with the lowest value being1.59% for coal D and the highest being 1.66% for both coalsA and C. This indicates that coals A and C are likely toproduce higher proportions of fuel NOx contributing to thetotal NOx emissions.

The HGI values for the coals in this study range from 52to 70, while the AI values vary from 54 to 246. Coal A wasthe hardest sample, with an HGI of 52 and AI of 246, whilecoal sample D was the softest with an HGI value of 70 and AIof 54. It was noted that coal A and coal C, with an HGI of 52and 59 respectively, have similar HGI values but clearlydifferent AI values of 246 for coal A and AI of 99 for coal C.This distinctive difference in AI might be a positive influenceon the grindability and thermal shattering of coal C in thefreeboard of the spreader stoker furnace, compared with coalA.

The propensity of the four coals to slagging and clinkerformation on the grate and furnace heat transfer equipmentwas also investigated. The flow ash fusion temperatures(AFTs) for the four coals ranged from 1400°C to 1500°C. Thehighest values were recorded for coals A and C, both at1500°C, while the lower ash fusion temperatures weredetected in coals B and D at around 1400°C.

The overview of the petrographic results for the four coals ispresented in Table III. Coals A and D are vitrinite-rich, at 47%and 44%, respectively, whereas coals B and C have signifi-cantly high proportions of inertite at 68% and 70% respec-


1161 ▲


tively. Total reactive macerals for the four coals range from54 to 64%. Coal D has the highest proportion of total reactivemacerals at 64%, while coal C shows the lowest fraction at54%. Coal D appears to have a slightly higher proportion ofabnormal (weathered) constituents than the other three coals,at 25%. This indicates the organic components in coal D aremore extensively cracked, weathered, and oxidized than inthe other three coals. The mean random reflectance values(Rr%) for the four coals range between 0.61 to 0.76%. Interms of rank, all coals are the bituminous C, with coals Aand D slightly lower in maturity.

Table IV presents the results obtained from the performanceof the test equipment in the form of the rates of steam outputand combustion efficiencies of the coals. Sampling wasperformed throughout the testing period as the boiler loadingor operating steam output was confirmed steadied for aboutthree hours. This test provides an insight into the conditions

of flue gas exiting the boiler furnace and before entering theeconomizer section, in terms of exit temperatures andcombustion gases. The readings recorded indicate averagedvalues over the four-hour testing period for each coal sample.The indications are that coal C, with the highest O2 contentand the lowest CO2 fraction of the flue-gas, exhibits poorcombustion as evidenced by the relatively high amounts ofunburnt carbon (UBC) reported in the ash. Coal D, with thelowest O2 content and the highest proportion of CO2 in theflue gas, displays improved combustion considering thecomparatively low amount of UBC in ash.

The impact of the physicochemical properties of the coalsamples utilized in this study on the boiler performance andefficiency is further elucidated in Figure 4. The performanceof the boiler during the combustion of each coal sample wasdetermined by monitoring the proportion of carbon loss in thefly ash as well as the steam output. Figure 4 also depicts howthe physical and chemical properties of coal, namely thecalorific value and volatile matter content, possibly affectedthe coals during combustion. It was observed that thecombustion efficiency increases with decreasing amounts ofunburnt carbon in the fly ash and increasing volatile mattercontent, but does not appear to correlate with the calorificvalue. Increasing combustion efficiency correlates withincreasing volatile matter and decreasing fixed carbon, andinversely with the unburnt carbon.

However, the petrographic analysis provides vitalinformation for the holistic understanding of the combustionbehaviour of the coals. The analyses and associated

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1162

Proximate: (Ar%)% fixed carbon 50.40 54.50 58.10 48.60% moisture 4.8 3.4 3.7 4.5 % volatile matter 29.20 24.60 23.50 30.20% ash 15.60 17.30 14.70 16.70CV (MJ/kg) 26.13 26.42 26.90 25.54Ultimate:% carbon 65.86 65.13 67.36 61.58% hydrogen 3.97 3.61 3.44 3.68% nitrogen 1.66 1.62 1.66 1.59% oxygen 6.65 8.56 8.63 8.76Sulphur species% mineral 0.78 0.13 0.15 0.71% organic 0.66 0.24 0.34 0.51% sulphate 0.02 0.01 0.02 0.01AFT (T, °C)Deformation >1500 1351 >1500 1320Flow >1500 1403 >1500 1400HGI 52 61 59 70AI 246 149 99 94Ar: as received; AFT: ash fusion temperature; HGI: Hardgrovegrindability index; AI: abrasive index

Maceral analysis (%mmf)% total vitrinites 47 28 24 44% total liptinites 4 4 5 9% total reactive inertinites 12 24 25 11% total reactive macerals 63 56 54 64Rank:% random reflectance (Rr) 0.61 0.70 0.76 0.63Standard deviation (δ) 0.066 0.075 0.099 0.064% total inertites 49 68 70 47% total inert macerals 37 44 45 36% inertites 24 33 40 20% abnormal (weathered) 14 19 22 25

Flue gas temperature at furnace exit/ economizer inlet (°C) 300.06 306.42 295.64 306.03Flue gas temperature at economizer outlet (°C) 181.06 179.74 177.98 176.16Steam output (t/h) 38.59 37.79 34.56 41.76Flue gas O2 content at furnace exit (% ) (Orsat analyser readings) 10.9 10.5 11.7 9.5Flue gas CO2 content at furnace exit (%) (Orsat analyser readings) 10.0 11.1 8.8 11.6Unburnt carbon (UBC) in fly ash (%) 30.13 42.76 42.81 31.90UBC in bottom ash (%) 16.97 22.70 21.62 16.26)Calculated heat loss corresponding to total % UBC detected (%) 4.92 8.92 12.04 6.70

combustion profiles of the four coals are illustrated in Figure5. The results indicate that higher combustion efficiency iscorrelated with higher vitrinite content and total reactivemacerals. Coals D and A had higher combustion efficienciesof 79.13% and 77.98%, and total reactivities of 64% and63%, respectively, compared to coals C and B. Coal Dproduced the highest steam output (41.76 t/h) andcombustion efficiency (79.13%), while coal C yielded thelowest steam output (34.56 t/h) and lowest combustionefficiency of 71.05%. It was also noted that higher amountsof unburnt carbon corresponded with higher quantities ofinertinite and lower combustion efficiency.

The primary objective of this investigation was to establishthe combustion characteristics and efficiencies of four coalsand their impact on the performance of one specific spreaderstoker boiler. In seeking to determine the dominantparameters influencing combustion efficiency and boilerperformance, a detailed investigation involving the boileroperating conditions associated with physical and chemicalcharacteristics of the coals, petrographic properties, andthermographic data as observed in the boiler was conducted.From Table V, it is noticeable that coals B and C, with thehighest calorific values and lowest volatile matter contents,yielded the lowest steam outputs and combustion efficiencies.In contrast, coals A and D, with the lowest calorific values

and highest volatile matter contents, produced higher steamoutputs and combustion efficiencies. It was also observedthat for coals with the closest similarities in physical andchemical properties, such as coals A and D, there werenoteworthy differences in the boiler performances undermatching operating conditions, as marked by varying steamoutputs and combustion efficiencies. The superiorperformance of coals A and D, compared to coals B and C,may be attributed partly to higher volatile matter contents, asthis would imply the coals were easier to ignite. In terms ofboiler performance based on proximate analyses, the higheststeam output of 41.76 t/h and highest combustion efficiencyof 79.13% was observed for coal D, which had the highestvolatile matter content and lowest fuel ratio (FR) value. Thelowest steam output at 34.56 t/h and lowest combustionefficiency at 71.05% were yielded by coal C, with the lowestvolatile matter content and highest FR value. However, thehigh steam output correlated with high volatile matter andhigh combustion efficiency, but correlated inversely with fuelratio and unburnt carbon, as shown in Table V. The fuel ratiois determined from the ratio of fixed carbon to volatile matterand is used to approximate the ease of ignition and burnoutfor a given coal sample.

The results in Table VI indicate that increasingcombustion efficiency correlates with increasing totalreactivity. Conversely, high combustion efficiency proves tobe inversely proportional to the amount of unburnt carbonand total inertinite. With regard to steam production, thehighest steam outputs correlate with high vitrinite content,higher combustion efficiency, and lowest unburnt carbon.Coal D, with the second highest vitrinite content of 44% mmfand lowest inertinite content of 47% mmf, produced thehighest steam output at 41.76 t/h. The association betweensteam output and petrographic composition was alsoconsistent for the other three coals B, C, and D, which yieldedsteam outputs paralleling their respective petrographiccompositions in terms of total reactive and inert maceralcontents. These results show that the impact of petrographiccharacteristics is crucial in understanding the combustionbehaviour of coal. It can further be asserted that forcombustion behaviour of any particular coal sample to bewholly known, there has to be an equally comprehensivestudy of the petrographic characteristics of the coal

The investigation into the combustion behaviour of the fourcoals tested was based on thermographic analysis andtemperature profiling of the furnace during combustion.Thermography provides insight into the thermal behaviour ofthe different coals tested by showing maximum combustiontemperatures in the flames and the characteristics of ignitioncombustion. A summary of the thermographic temperatureprofiles is presented in Figure 6, and the behaviour of eachcoal is illustrated in terms of flame characteristics andassociated temperature readings. All four coals showedsignificantly different combustion characteristics despitehaving comparable calorific values, volatile matter contents,and ash contents. The results indicate that there is a strongcorrelation between combustion efficiency, unburnt carbon,and petrographic composition of the coals. There is a


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correlation between the combustion efficiency and the totalreactive macerals, i.e. the highest combustion efficiency andthe lowest unburnt carbon correlate with a high content ofreactive organic materials. Low combustion efficiency andhigh unburnt carbon correlate with high-inertinite coals. Thisassociation is not reflected in calorific values or data from the

proximate analysis. In addition, according to Table V, there isa correlation between the combustion efficiency, fixed carbon,and volatile matter. The lower the fixed carbon of thesamples, the higher the combustion efficiency, and the higherthe volatile matter, the higher the combustion efficiency Thedifferent thermographic trends observed in coals A and Dfrom the same colliery illustrate the lack of a clear correlationbetween flame temperature, calorific value, combustionefficiency, and ash and volatile matter content. Despitehaving fairly similar proximate analyses and calorific values,the two coals burnt at notably different flame temperaturesunder similar operating conditions. Coal A burnt with thelowest maximum flame temperature of all the four coals atROI5 = 1549°C, while coal D recorded the highest maximumflame temperature amongst the four coals at ROI5 = 1793°C.

Coal A, with 14% weathered oxide content, has similarpetrographic properties to coal D, which is relatively fresh andunaltered and therefore is likely to burn in its normalcondition. Coal B was noted as the coal with the secondhighest flame temperature at ROI5 = 1741°C. Although thiscoal possesses the highest calorific value, its flame character-istics did not exhibit good combustion or ignition as the

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1164

VM FC FR CV (%) (%) UBC/ Flame T (°C) Flame T (°C) Average(fly ash) Lowest ROI1 Highest ROI5 steam output (O2 in flue

gas, %)D 30.2 48.6 1.61 25.5 79.13 31.90 1771 1793 41.76

(16.97) (10.27)A 29.2 50.4 1.73 26.1 77.98 30.13 1509 1549 38.59

(16.97) (11.5)B 24.6 54.7 2.22 26.4 75.54 42.76 1709 1779 37.79

(22.70) (11.4)C 23.5 58.1 2.47 26.9 71.05 42.81 1616 1722 34.56

(21.62) (11.7)

ad: air dry basis; VM: volatile matter; FC: fixed carbon; CV: calorific value; UBC: unburnt carbon; : combustion efficiency; FR: fuel ratio = % FC/% VM; ROI1:region of interest 1 (flame temperatures at highest parts of the furnace);ROI5: region of interest 5 (flame temperatures at lowest parts of the furnace)

Total vitrinte Total reactivity Total inertinite Rank RoVr% (%) (%) UBC/ Flame T°C Flame T°C Average (%) (%) (%) (Fly ash) Lowest RO1 Highest RO5 steam output

(O2 in flue gas %)

D 44 64 47 0.63 79.13 31.90 1771 1793 41.76(16.97) (10.27)

A 47 63 49 0.61 77.98 30.13 1509 1549 38.59(16.97) (11.5)

B 28 56 68 0.70 75.54 42.76 1709 1779 37.79(22.70) (11.4)

C 24 54 70 0.76 71.05 42.81 1616 1722 34.56(21.62) (11.7)

ad: air dry basis; VM: volatile matter; FC: fixed carbon; CV: calorific value; UBC; unburnt carbon; : combustion efficiency = [(Fuel - Heat input - Stacklosses)/Fuel - Heat input] ×100

flame burnt irregularly and was segregated to discrete partsof the furnace. This observation further confirms that there isno correlation between flame temperature, calorific value, andproximate analysis data. With the exception of coal B, whichproduced highest temperature in the middle of the furnace(the desirable combustion zone), all other coal samplestended to yield higher flame temperatures both on the grateand in the upper fireball zones of the furnace where theboiler heat-exchangers (steam drum) are located. Thisindicates delayed combustion at the back end of the boiler.Such conditions are undesirable as they imply loss ofefficiency due to combustion in regions outside of the furnaceheat transfer zones, leading also to fouling of the heatexchange surfaces and blocking of convective passes by ashdeposits. High flame temperatures pose a greater risk of sootformation due to volatile matter components of the coal,especially tar, undergoing secondary reactions at hightemperature (Fletcher et al., 1997).

This research compared the combustion performance of thefour coals with their physicochemical properties and theirpetrographic characteristics. This information providedvaluable insight into the differences in combustionbehaviour.

➤ The quality of coal proved to significantly influence thecombustion performance in the stoker boiler underinvestigation. This was best reflected in thepetrographic composition of the coals and the thermor-gaphic results as indicated by flame temperatures andcombustion flame characteristics

➤ The most relevant results were observed fro thecombustion performance of coals A and D, both fromthe same colliery. These coals had the same proximateanalyses, calorific values, and ash contents, butdiffered significantly in combustion temperatures,flame shapes, as well as petrographic composition

➤ In terms of efficiency, coal A produced the secondhighest combustion efficiency and steam output, andburnt at the lowest flame temperatures of all four coals.Coal D, on the other hand, while producing the higheststeam output and combustion efficiency, burnt at thehighest flame temperatures of all four coals, with amassive flame that encompassed virtually the entirefreeboard above the grate as well as on the grate.Under these conditions, extensive thermal damage ofboiler plant equipment could be expected

➤ The reasons for the difference in combustionperformance between coal A and coal D were revealedin part by petrographic analyses, which showed thatcoal A was a fresh coal and coal D comprised 25%oxidized and weathered organic matter. This wassupported by an unusually high Hardgrove index (softgrindability), a particularly low abrasion index (AI),and a lower than normal ash fusion temperature (AFT)relative to the values found in coal A

➤ The massive fireball and high temperatures in thefreeboard produced by coal D are interpreted to be dueto the presence of friable weathered coal material thatunderwent intense thermal shattering as the particles

entered the hot zone and were lifted up and thrownacross the boiler chamber

➤ The combustion characteristics of coals B and C werefound to differ significantly from those of coals A andD. Both coals exhibited limited ignition, reducedflames, and poor burnout characteristics leading tohigher unburnt carbon contents in the fly ash. Theseresults occurred despite these coals having the highestcalorific values and nominal ash contents. The lowercombustion efficiencies of these coals can be attributedto increased proportions of relatively inert forms oforganic components (inertinite)

➤ Coal A would be the preferred feed for the boiler underinvestigation, owing to its lower propensity to slaggingdue to the lowest flame temperatures of all four coals,its high AFT, second highest combustion efficiency andsteam output, and the lowest flame temperatures of allfour coals.

FALCON, R.M.S. and HAM, A.J. 1988. The characteristics of Southern Africancoals. Journal of the South African Institute of Mining and Metallurgy,vol. 88, no. 5. pp. 145–161.

FALCON, R.M.S. 2010. Internal unpublished reports. School of Chemical andMetallurgical Engineering, Faculty of Engineering and the BuiltEnvironment, University of the Witwatersrand.

FLETCHER, T.H., MA, J., RIGBY, J.R., BROWN, A.L., and WEBB, B.W. 1997. Soot incoal combustion system. Progress in Energy and Combustion Science, vol.23, no. 3. pp. 283–301.

GIAIER, T.A. and LOVISKA, T.R. 1997. Vibrating grate stokers for the sugarindustry. Proceedings of the Annual Congress of the South African SugarTechnologists Association, vol. 71. pp. 172–175.

JOHNS, A.R. and HARRIS, M. 2009. Boiler Efficiency Calculations. Lecture notes:Coal Combustion and Power Generation course, University ofWitwatersrand, Johannesburg, 31 August 2009.

LI, Z., ZHAO, W., LI, R., WANG, Z., LI, Y., and ZHAO, G. 2009. Combustioncharacteristics and NO formation for biomass blends in a 35-ton-per-hourtravelling grate utility boiler. Bioresource Technology, vol. 100. pp. 2278–2283.

LIN, P, JI, J, LUO, Y., and WANG, Y., 2009. A non-isothermal integrated model ofcoal-fired travelling grate boilers. Applied Thermal Engineering, vol. 29.pp. 3224–3234.

SANEDI. 2013. Overview of the South African Coal Value Chain. South AfricanCoal Roadmap.http://www.sanedi.org.za/archived/wpcontent/uploads/2013/08/sacrm%20value%20chain%20overview.pdf [Accessed 26 May 2015].

SHENG, J.S. WANG, B.B., and LI, W.J. 2012. A study on structural characteristicsof biomass briquette boiler. Applied Mechanics and Materials, vol. 197.pp. 211–215.

TAOLE, R.T. 2015. The Impact of Coal Quality and Technical OperatingConditions on the Efficiency of a Spreader Stoker Boiler.http://wiredspace.wits.ac.za/handle/10539/17553

THAI, S.M., WILCOX, S.J., CHONG, A.Z.S., WARD, J., and PROCTOR, A. 2011.Development of fuzzy based methodology to commission co-combustionof unprepared biomass on chain grate stoker fired boilers. Journal of theEnergy Institute, vol. 84, no. 3. pp. 123–131. ◆


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Coal in South Africa is found in 19 coalfieldslocated in the middle and northern sections ofthe country (Jeffrey, 2005). The main coalmining areas in the country at present are inthe Witbank-Middelburg, Waterberg, andSasolburg coalfields of the Mpumalanga andLimpopo provinces. The Springbok FlatsCoalfield (SFC), located in the LimpopoProvince, has not been mined to any degree ofeconomic profit, predominantly due to thepresence of uranium in the coal. The firstcoordinated exploration programme wasconducted by the Council for Geoscience (CGS)between 1952 and 1957, where 27 boreholeswere drilled in the northeastern portion of theSFC (Visser and Van der Merwe, 1959).Further exploration by the CGS in the westernand south-central portions of the coalfield washalted in 1972 when uranium was detected inthe upper Ecca coal zone (Christie, 1989).Similar to most materials in nature, coal

contains small quantities of naturally occurringradionuclides such as 40K, 238U, 232Th, andtheir decay products (Papastefanou, 2010).The Medium Rank C bituminous coal zones inthe Springbok Flats Basin, hosted in the coalhorizons of the Late Permian in the uppermostpart of the Hammanskraal Formation withinthe SFC basin, have a significant uraniumcontent (Cole, 1998). Further, the uranium inthe SFC is believed to be disseminatedthroughout the coal and the associatedcarbonaceous shale (Christie, 1989). This isparticularly noteworthy as it means that thiscoalfield could potentially have areas that arerich in uranium but with very little coalpresent. This gives metallurgists theopportunity to concentrate on extractinguranium from the carbonaceous horizonswithout worrying about the effects of theuranium extraction process on coal and itsability to combust post-extraction.

Overall, there is limited public domainresearch pertaining to the quality of coalpresent in the SFC as well as the uraniumassociated with the coal and carbonaceoushorizons. This knowledge is strategicallyimportant in determining the viability of theSFC as a potential source of either coal oruranium, thus addressing two key energymarkets. The Department of Mineral Resources(DMR) has seen a need for South African coalresearchers and metallurgists to investigatecleaner coal processing and energy production,and has thus created intervention strategiesfor the optimal beneficiation of coal(Department of Mineral Resources, 2011),which, among numerous other objectives, seekto invest in metallurgical research on the

Coal quality and uranium distribution inSpringbok Flats Coalfield samplesby M. Ndhlalose*, N. Malumbazo*, and N. Wagner†

The presence of coal in the Springbok Flats Coalfield (SFC) has beenknown since the beginning of the 1900s. However, the SFC has not beenmined to any degree of economic profit, mostly due to the presence ofuranium in the coal. Five boreholes were drilled in the SFC (BH1 to BH5);BH5 intersected two coal zones, the other boreholes intersected one coalzone. Coal samples were collected, selected, and characterized usingproximate, ultimate, and calorific value analyses. X-ray fluorescence,instrumental neutron activation analysis, and inductively coupled plasmamass spectrometry were used to determine uranium content. The BH1intersection and the upper coal zone in BH5 had ash contents higher than50% and were considered to be primarily carbonaceous shale. BH2 wasobserved to have better coal quality, resembling typical South Africanbituminous coal used in local electricity generation. The highest uraniumcontent was found in BH3 (up to 199 mg kg-1, followed by BH2 and BH1.BH4, the upper coal zone in BH5, and the lower coal zone in BH5 all haduranium contents averaging less than 10 mg kg-1. Uranium in the SFCsamples was found both in the coal and carbonaceous shale. For allboreholes except BH5, uranium is concentrated within the uppermost 1 mof the coal zone. X-ray fluorescence was the preferred analytical techniquesince the analysis gave consistent results that compared well with instru-mental neutron activation analysis results.

Springbok Flats Coalfield, coal quality, uranium.

* Council For Geoscience, Pretoria, South Africa.† School of Chemical and Metallurgical Engineering,

University of the Witwatersrand, (nowDepartment of Geology, University ofJohannesburg).

© The Southern African Institute of Mining andMetallurgy, 2015. ISSN 2225-6253. Paper receivedJune 2015 and revised paper received Nov. 2015.

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Coal quality and uranium distribution in Springbok Flats Coalfield samples

quality of the coal associated with uranium in the SFC. Thus,the aim of this study is to assess the quality of newlyacquired borehole core coal samples, and to accuratelydetermine the uranium content in those samples. Once anunderstanding of the uranium content and distribution isobtained, the extraction of the uranium from specificlocalities can be considered; this discussion is targeted for afuture publication.

The study covers five boreholes drilled in the SFC (BH1 toBH5) in 2013. BH1 to BH4 intersected a single coal zone,while BH5 intercepted two coal zones, an upper and a lowerzone. Thus, six coal localities were included in this research.Figure 1 depicts the five farms where the drilling occurred.The boreholes were drilled up to a depth of 450 m, recoveringa 4 cm cylindrical core. The recovered cores were placed in1.5 m long core trays, logged, and stored at the CGSDonkerhoek core shed, Pretoria, for about a month prior to

sampling. One quarter section of core from each coal horizonwas removed (the rest retained for future projects), andmilled using a Reutsch mill to obtain a -1 mm split (retainedfor coal petrography) and a subsequent -250 μm sample. AMACSALAB design rotary cascade splitter was used to obtaina representative -250 μm split for geochemical analysis(proximate, ultimate, CV, uranium determination). Allsamples were studied on an as-received basis. Proximateanalysis was conducted at the CGS coal laboratory followingISO 1171:1981, SANS 5924:2009, and ISO 562:1981. LecoCHN and Leco S instruments were used to determine ultimateanalysis using ISO 17247:2013. The CV data was obtainedusing a Parr 3600 bomb calorimeter where net CV (NCV) wasused as the measure of CV. To determine uranium content, X-ray fluorescence (XRF) data was processed using aPANalytical wavelength-dispersive Axios X-ray fluorescencespectrometer. Inductive coupled plasma–mass spectrometry(ICP-MS) analysis was conducted using a Bruker 500 MHzNMR spectrometer. Eleven samples that revealed an uraniumcontent higher than 10 mg kg-1 were subjected to instru-mental neutron activation analysis (INAA) to confirm theresults obtained from ICP-MS and XRF.

Figure 2 shows the major coal quality parameters relative todepth for each borehole coal zone, with the actual data reportedin Tables I–V for each of the coal zones sampled. Photographsof the coal zone intersections are provided in Figure 3.

BH1: The volatile matter content was highest in the samplesproximal to the roof of the coal zone where the bright bandswere observed. The average ash content for BH1 peaked at88.4%, indicative of carbonaceous shale horizons or partingsin the coal zone (Table I). The CV peaked at 4.2 MJ/kg, which

▲

1168

indicates a coal zone that is virtually incombustible. It wasthus concluded that the whole coal zone sampled is predomi-nately carbonaceous shale instead of coal as defined by SANS10320:2004.

BH2: Relatively good CV data was obtained for samples inBH2, peaking at 27 MJ/kg (Table II). However, the sulphurcontent was alarmingly high for a number of coal samples,reaching a maximum of 8.9%. Sulphur was found to beabundant in the samples with high CV and volatile matter,and low ash content. The ash content was higher towards thefloor of the coal zone. The majority of the coal zoneregistered ash contents well below 50%, indicating that thezone is made up predominately of coal.

BH3: When one considers the entire coal zone in BH3, it iscan be noted that 60% of the 3.6 m coal zone contained

samples with ash contents higher than 50% (Table III). Theremaining 40% of the samples recorded CV and volatilematter averages of 18.7 MJ/kg and 25.5% respectively.Similar to BH2, these samples also recorded a higher averagesulphur content (3.5%).

BH4: The ash content in BH4 was fairly constant in allsamples (46–58.4%), except for the sample close to the floorof the seam. Table IV shows that the coal quality in BH4 isvery poor, supported by the low CV that peaked at 16.5MJ/kg. Similar to the other boreholes, the sulphur contentwas highest (4.2%) in the regions where the coal quality wasbetter than the surrounding samples.

BH5 upper coal zone: 90% of the coal zone had an ashcontent higher than 50%. The lowermost sample was ofcomparatively better coal quality, with a CV and ash content


1169 ▲

277.0–277.9 1436 10.4 74.9 13.7 0.2 3.5278.0–278.8 1437 6.7 88.4 0.2 0.2 0278.8–279.4 1438 7.8 85.1 6.3 0.2 0.7279.4–280.0 1439 10.6 76.2 12.1 0.2 4.2280.0–280.5 1440 7.9 84.9 4.1 0.1 1.0308.7–309.1 1441 5.8 82.5 9.6 0.1 2.4309.1–309.6 1442 5.6 62.2 5.3 0.1 0.8Average 7.8 79.2 7.3 0.2 1.8


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1170

251.34–251.4 1426 22.4 46.2 38.6 4.4 16.3252.30–252.7 1427 29 32.1 51.7 8.9 22252.75–253.0 1428 19.3 53.1 34.4 1 13.4253.12–253.7 1429 25.4 36.8 47.8 2.5 20253.72– 254.1 1430 31.8 18.1 65.3 2.1 27254.14–254.2 1431 33.2 24 57.7 7.2 23.5254.6–255.5 1432 23.8 39.3 46.8 1.4 17.5255.5–255.93 1433 22.4 42.6 44 0.5 17.9256.33–256.7 1434 16.6 59.7 27.9 1.6 11.7257.7–258.0 1435 19.1 56 31.4 1.9 12.9Average 24.3 40.8 44.6 3.2 18.2

341.52–342.04 1421 27 37.3 47.6 3.5 19.8342.1.0–342.7 1422 16.2 63 25 0.9 9.9342.7–343.08 1423 24 40.1 41.4 3.5 17.6343.56–344.0 1424 8.5 84.7 5.5 1.1 1.72344.0–344.3 1425 11.1 78.2 32 3.6 4.1Average 17.4 60.7 30.3 2.5 10.6

387.81–389.13 1443 22.7 58.4 26.1 4.2 10.3389.1–390.0 1444 19.8 46.7 37.8 4.1 15.8390.0–391.0 1445 15.8 46.0 41.2 1.0 16.5391.0–-391.7 1446 9.7 49.7 40.2 0.6 13.6391.7–392.13 1447 7.0 53.4 38.6 0.6 13.7393.0–393.7 1449 5.0 73.9 19.0 0.3 4.4Average 13.3 54.7 33.8 1.8 12.4

143.90–144.45 1401 6.6 64.7 27.3 3.6 10.2144.5–145.0 1402 7.0 75.1 18.9 2.2 5.9151.6–152.10 1403 5.6 79.8 13.6 0.7 4.2152.10–152.72 1404 6.5 61.9 32.0 0.8 11.3152.72–153.23 1405 4.6 69.0 25.4 0.7 8.7153.23–153.70 1406 4.8 62.2 31.2 0.9 10.6153.7–154.1 1407 5.0 76.0 18.0 0.7 5.6154.1–154.51 1408 4.6 60.0 33.1 1.0 11.4154.51–154.9 1409 4.8 66.3 26.7 0.5 8.3154.9–155.27 1410 18.1 43.3 40.0 12.4 17.8Average 6.8 65.8 26.6 2.4 9.4

of 17.8 MJ/kg and 43.3% respectively (Table V). Theproximate analysis and CV results for the upper coal zone ofBH5 are below the limits of typical South African coals, andthe results resemble those of carbonaceous shale instead ofcoal (Martins et al., 2010).

BH5 lower coal zone coal: The ash content in the uppercoal zone in BH5 was high, with no sample recording ashcontent less than 40%. The majority of the coal zone reportedash contents higher than 50%. The CV was low for all

samples, peaking at a moderate 15.8 MJ/kg (Table VI). Theproximate analysis and CV results for the upper coal zone ofBH5 are below the limits of typical South African coals, andthe results resemble those of carbonaceous shale instead ofcoal (Martins et al., 2010).

Figure 4 provides the uranium content for each of the fiveborehole core samples. Figure 5 depicts the average concen-trations. As the samples included the high-ash carbonaceousshales, the uranium values are not indicative of only thecoal-rich zones.

ICP-MS produced the lowest uranium values of all theanalytical techniques used, and XRF consistently producedthe highest uranium values (Table VII). INAA (on selectedsamples) reported higher uranium values than ICP-MS, andthe results were closer to the XRF values (Table VII). Thevariation in some ICP-MS results led to the conclusion that anerror (either technical or human) could have occurred duringanalysis. Due to the consistent results provided by XRF,these results were used in the subsequent interpretations anddiscussion.

BH1: The uranium content in the BH1 samples ranged from5.3 mg kg-1 to 73 mg kg-1. The highest uranium valuesoccurred at the roof of the coal zone. Since the BH1 sampleconsisted entirely of carbonaceous shale, this givesmetallurgists the opportunity to concentrate on extractinguranium from these horizons without worrying about theeffects of the uranium extraction process on coal and itscombustion qualities post-extraction.

BH2: Samples from BH2 had uranium contents that rangedfrom 2.9 mg kg-1 to 130 mg kg-1. The uranium content washighest where the ash content was < 50%, with a significantpeak occurring towards the middle of the coal zone (96 mgkg-1), also a coal-rich zone.

BH3: The uranium content of sample 1421 was 199 mg kg-1,the highest of all samples. Relative to coal quality, bothcarbonaceous shale regions and coal regions containeduranium; however, the coal-rich samples yielded higheruranium values.


1171 ▲

344.67–345.10 1411 14.1 67.5 39.2 0.3 7.2345.10–345.54 1412 16.0 62.2 28.5 0.3 8.7345.54–345.89 1413 16.6 55.3 29.6 0.3 11.1345.89–346.25 1414 20.1 44.8 38.2 0.4 14.6346.25–347.10 1415 20.3 46.2 36.9 0.7 14.5347.10–347.86 1416 21.2 42.4 40.5 0.6 15.8347.86–348.28 1417 17.4 61.5 23.3 0.2 8.2348.28–349.05 1418 15.2 62.2 22.6 0.2 7.7349.05–349.86 1419 20.2 49.1 34.1 0.3 13.1349.86–350.67 1420 14.4 59.8 24.7 1.5 8.6Average 17.6 55.1 31.8 0.5 11.0


BH4: Maximum uranium content was detected where the coalzone reported an ash content of 58.4%. Similar to previousboreholes, uranium was found to be abundant at the roof ofthe coal zone.

BH5 upper coal zone: Similar to BH1, the entire coal zonewas made up of carbonaceous shale, and thus uranium inthis coal zone occurred in the carbonaceous shale. Unlike theother intersections, where the maximum uranium contentwas found at the roof, the uranium was distributed fairlyevenly throughout the coal zone with a difference of 5 mg kg-

1 between the maximum and the minimum valuesdetermined.

BH5 lower coal zone coal: The lower coal zone coal in BH5returned a peak uranium content of 14 mg kg-1. Similar toBH2, other peaks of interest were found further down thecoal zone. The uranium was distributed in some areas thatconsisted predominately of coal, and in areas that werepredominately carbonaceous shale.

It was apparent from visual inspection that the coal zonessampled do not consist only of coal, but carbonaceous andsandstone horizons are interbedded in the coal zone, asshown in Figure 2. The darker horizons in the cores representthe coal zones, made up of interbedded coal andcarbonaceous shale. BH1 was dominated by carbonaceousshale (blue arrows) with very few visible bright coal bands.BH2 had significantly more bright coal bands compared toBH1, where the coal zone appeared to be made up predomi-nately of bright coal (red arrows to left) interbedded withcarbonaceous shale (blue arrow to right). Calcite cleats (greenarrow top right) were visible in some areas in the coal zone.BH3 coal zone consisted of bright coal (red arrows to left)clustered at the top of the coal zone; the bright bands of coaldiminished and carbonaceous shale (blue arrows to right)dominated further down the coal zone. BH4 contained veryfew bright bands of coal. Carbonaceous shale dominated thetop of the coal zone, with regular bright coal bands a littlefurther down, towards the middle of the coal zone, whichdiminished again towards the bottom of the coal zone. Theupper coal zone in BH5 had very few bright bands of coal,with large areas showing no bright bands of coal at all.

Carbonaceous shale (blue arrows) dominated the entire coalzone. The lower coal zone in BH5 also had very few coal andcarbonaceous shale (blue arrows) dominated the entire coalzone.

The average ash content of boreholes BH1, BH3, BH4,and the upper and lower coal zones in BH5, were far greaterthan the 40.3% recorded in the CGS database, and higherthan the 30–55% estimated by De Jager (1983), while alsobeing higher than the 30–35% ash inferred by the PetricCommission (1975). BH2 average ash content of 40.8%agrees with the 40.3% recorded in the CGS database for coalfrom the same locality, and is in line with the 30–55% ashcontent estimated by De Jager (1983). BH2 coal qualityresembles a typical South African bituminous coal (Falconand Ham, 1988; Pinhiero, 1999); however, the sulphurcontent average of 3.2% is higher than the 2.8% recorded inthe CGS database for samples from the same region, whilealso being higher than 0.4–1.29% reported by Wagner andHlatshwayo (2005) for Highveld coals, and 1.47% found byRoberts (2008) for samples in Mpumalanga.

Figure 5 shows the average uranium contents for each of theboreholes studied. All borehole coal zones studied haduranium contents averaging higher than the 2 mg kg-1 worldaverage reported by Swaine (1990), and the 2.9 ppm globalaverage for coals (Ketris and Yudovich 2009). Ren et al.,(1999) determined a 7.52 mg kg-1 arithmetic mean uraniumcontent in Chinese coals.

The uranium content relative to selected coal qualityresults can be seen in Figure 6. Uranium in the SFC sampleswas disseminated throughout the coal and carbonaceousshale, as reported by Cole (2009) and Hancox and Gotz(2014). The uranium in the coal zones was generallyrestricted to a single layer, usually the highest in the localsequence, except in BH2 and the lower coal zone coal in BH5,where uranium mineralization was found in multiplelocations in the coal zone. This finding is in agreement withCole (2009), Christie (1989), and Nel (2012). BH3 had thehighest average uranium content, and the highest uraniumcontent (199 mg kg-1) was determined in a sample from thiscoal zone. BH4 and the upper and lower coal zones in BH5 allhad average uranium contents less than 10 mg kg-1 (which isstill high in the global context).

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1416 BH5 LCZ 12 8.9 8.61417 BH5 LCZ 14 11.8 9.81421 BH3 199 161 145.91422 BH3 18 15.6 11.31429 BH2 96 86.9 85.91436 BH1 73 64.6 34.11437 BH1 52 43.2 131438 BH1 51 39.4 19.41439 BH1 36 29.3 20.91440 BH1 14 11.5 6.21443 BH4 52 33.5 34.4

In summary, BH1 and the upper coal zone in BH5 reportedash contents higher than 50% for all the samples collectedthroughout the coal zone; these coal zones are made upalmost entirely of carbonaceous shale and are thus notsuitable for coal exploitation. BH2 samples reported coalqualities that resemble a typical South African bituminouscoal and could potentially be of economic benefit to thecountry, depending on the available tonnages in the area.BH3 and BH4 had coal horizons that are potentiallymineable, and could be of use in the coal conversionindustries.

INAA reported higher uranium values than ICP-MS, with theresults being closer to the XRF values; which were thehighest for all the samples. All borehole coal zones studiedhad an average uranium content higher than the 2 mg kg-1

world average reported by Swaine (1990). Uranium in thecoal zones sampled was generally restricted to a single layer,usually the highest in the local sequence, except in BH2 andthe lower coal zone coal in BH5, where uranium mineral-ization occurred in multiple locations in the coal zone. Thisfinding is in agreement with Cole (2009) and Nel (2012).Overall, uranium in the SFC samples was disseminatedthroughout the coal and carbonaceous shale horizons,findings supported by Hancox and Gotz (2014). BH4 and theupper and lower coal zones in BH5 all had average uraniumcontent less than 10 mg kg-1 , but BH2 and BH3 had averagevalues over 25 mg kg-1. Table VII shows the samples selected

for INAA analyses to confirm the high uranium values; thesesamples were selected for leaching experiments to extract andconcentrate the uranium. This work will be reported in afuture publication.

This research was sponsored by the CGS and the NationalResearch Foundation (NRF).

We would also like to thank Dr Samson Bada forassistance with the proximate analyses, and Ms ZwangaMulibana for assistance with ultimate analysis.

CHRISTIE, A.D.M. 1989, Demonstrated coal resources of the Springbok FlatsCoalfield. Report 1989-0069. Geological Survey of South Africa. 25 pp

COLE, D.I. 1998. Uranium. Mineral Resources of South Africa. Wilson, M.G.C.and Anhaeusser, C.R. (eds), Handbook 16, Council for Geoscience,Pretoria. pp. 642–658

COLE, D.I. 2009. A review on uranium deposit In the Karoo Supergroup ofSouthern Africa. Search and Discovery Article no. 80047. Council forGeoscience, Pretoria. pp. 1–9.

DE JAGER, F.S.J. 1983. An evaluation of the coal reserves of the Republic ofSouth Africa as at 1982. Report no. 1983–0006. Council for Geoscience,Pretoria.

DEPARTMENT OF MINERAL RESOURCES. 2011. Beneficiation Strategy.http://www.dmr.gov.za/publications/summary/162-beneficiation-strategy-june-2011/617-beneficiation-strategy-june-2011-.html[Accessed 6 November 2014].


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FALCON, R.M.S. and HAM, A.J. 1988. The characteristics of Southern Africancoals. Journal of the South African Institute of Mining and Metallurgy, vol.88, no. 5. pp. 145–161.

HANCOX, J.P. and GOTZ, A.E. 2014. South Africa’s coalfields – a 2014perspective. International Journal of Coal Geology, vol. 132, no. 1. pp.170–254.

JEFFREY, L.S. 2005. Characterization of the coal resources of South Africa.Journal of the South African Institute of Mining and Metallurgy, vol. 105,no. 2. pp. 95–102.

KETRIS, M.P. and YUDOVICH, Ya.E. 2009. Estimations of Clarkes for carbonaceousbiolithes: world averages for trace element contents in black shales andcoals. International Journal of Coal Geology, vol. 78. pp. 135–148.

MARTINS, M.F., SALVADORA, S., THOVERT, J.F., and DEBENEST, G. 2010. Co-currentcombustion of oil shale – Part 1: Characterization of solid and gaseousproducts. Fuel, vol. 89, no. 1. pp. 144–151.

NEL, L. 2012. The geology of the Springbok Flats. PhD thesis, Department ofGeology, University of the Free State.

PAPASTEFANOU, C. 2010. Escaping radioactivity from coal-fired power plants(CPPs) due to coal burning and the associated hazards: a review. Journalof Environmental Radioactivity, vol. 101, no. 3. pp. 191–200.

PETRIC COMMISSION. 1975. Report of the Commission of Enquiry into the CoalResources of the Republic of South Africa. Government Printer, Pretoria.

PINHIERO, H.J. 1999. A techno-economic and historical review of the SouthAfrican coal industry in the 19th and 20th centuries and analysis of coalproduct samples of South African collieries. Bulletin 113. South AfricanBureau of Standards and Department of Minerals and Energy, Pretoria.

REN, D., ZHAO, F., WANG, Y., and YANG S. 1999. Distribution of minor and traceelements in Chinese coals. International Journal of Coal Geology, vol. 40.pp. 109–118.

ROBERTS, D.L. 2008. Chromium speciation in coal combustion by products: casestudy at a dry disposal power station in Mpumalanga province, SouthAfrica. PhD thesis, University of the Witwatersrand, Johannesburg. p. 235.

SWAINE, D.J. 1990, Trace Elements in Coal. Butterworths, London.

VISSER, H.N. and VAN DER MERWE, S.W. 1959. The Northern Springbok FlatsCoalfields. Records of boreholes 1-27. Bulletin of the Geological Survey ofSouth Africa. pp. 31–97.

WAGNER, N.J. and HLATSHWAYO, B. 2005. The occurrence of potentiallyhazardous trace elements in five Highveld coals, South Africa.International Journal of Coal Geology, vol. 63. pp. 228–246. ◆

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During the oil and gas well cementing process,some wells often lose circulation zones, andare therefore prone to formation breakage.Often, low-density slurries are required toovercome these problems, and extenders,which help to reduce the weight of the slurry,are utilized (Salim and Amani 2013;Ahmaruzzaman 2010; Shahriar 2011). Thecommonly used extenders are water extenderssuch as bentonite and sodium silicate, whichallow addition of water to the slurry; and low-density aggregates such as microspheres andpozzolans, which have densities lower thanthat of Portland cement (3.15 g.cm-3) (Nelsonet al., 1990). These extenders reduce thedensity of the slurry, resulting in a reductionof the hydrostatic pressure during cementing(Nelson et al., 1990). Extenders also increaseslurry yield by replacing a substantial amount

of the cement required to complete a giventask, thereby reducing the expenditure.

One of the most commonly used waterextenders for oil well cement (OWC) is sodiumsilicate (Na2SiO3). It has been reported thatNa2SiO3 as a water extender is five times moreeffective than bentonite (Nelson et al. 1990).Unlike pozzolanic extenders such as fly ash,Na2SiO3 is highly reactive with OWC (Joel andUjile, 2009). Na2SiO3 reacts with the Ca2+ ionsfrom the lime in the OWC or calcium chlorideto produce additional calcium-silica-hydrate(C-S-H) gel (Nelson et al., 1990). The gelstructure provides sufficient viscosity to allowthe use of large quantities of mix waterwithout excessive free water separation(Nelson et al., 1990). The further C-S-Hformation also results in a reduction inthickening time, hence the accelerating effectof Na2SiO3 (Joel and Ujile, 2009). A lowconcentration of Na2SiO3 is required for a highyield as compared to other extenders such asbentonite and raw coal fly ash, making it apreferred additive for OWC (Joel and Ujile2009). While fly ash is added in concen-trations of up to 50% by weight of cement(BWOC) and bentonite up to 20% BWOC,Na2SiO3 additions range from 0.2% to 3.0%BWOC (Nelson et al., 1990). The acceleratingeffect of Na2SiO3, however, limits itsapplication at lower temperatures, typically atless than 52°C bottom hole circulatingtemperature (BHCT) (Nelson et al., 1990; Joeland Ujile 2009). However, it can be used athigher temperatures with the addition of aretarder, although in the presence of aretarder, the effectiveness of Na2SiO3 as anextender is reduced because of the inhibitionof C-S-H formation (Nelson et al., 1990; Joeland Ujile, 2009).

Synthesis of sodium silicate from SouthAfrican coal fly ash and its use as anextender in oil well cement applicationsby T. Kaduku*, M.O. Daramola*, F.O. Obazu*, and S.E. Iyuke*

In this work, the use of sodium silicate derived from South African coal flyash (CFA) in oil well cement (OWC) applications is reported. Silica (SiO2)was extracted from the CFA and used to synthesize CFA-derived sodiumsilicate (CFA-Na2SiO3), a typical OWC slurry extender. The physico-chemical properties of the CFA-Na2SiO3 were compared to those of acommercial sodium silicate (com-Na2SiO3) using scanning electronmicroscopy (SEM), X-ray diffraction (XRD), and Fourier transforminfrared (FTIR) spectroscopy. OWC slurries with varying proportions ofcement, distilled water, and 2% CaCl2 by weight of water (BWOW) wereprepared and extended using the CFA-Na2SiO3 and the com-Na2SiO3 atcompositions ranging from 0.25-2.5% by weight of cement (BWOC).Rheological properties of the slurries were evaluated using AmericanPetroleum Institute procedures and compared. The physico-chemicalproperties of the CFA-Na2SiO3 are consistent with those of com-Na2SiO3,indicating the purity of the CFA-Na2SiO3. A comparative study of the OWCslurries indicated that the slurries extended with CFA-Na2SiO3 haveslightly lower densities, lower viscosities, and higher compressive strengththan those extended with com-Na2SiO3. This indicates that CFA-Na2SiO3slurries would be easier to pump and preferable where early strengthdevelopment is critical. This report could be instrumental in providing away for the beneficiation of South African CFA in the petroleum, oil, andgas industry.

oil well cementing, coal fly ash, sodium silicate, compressive strength.

* School of Chemical and Metallurgical Engineering,Faculty of Engineering and the Built Environment,University of the Witwatersrand, Wits 2050,Johannesburg, South Africa.

© The Southern African Institute of Mining andMetallurgy, 2015. ISSN 2225-6253. Paper receivedJune 2015 and revised paper received Nov. 2015.

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Synthesis of sodium silicate from South African coal fly ash

At industrial scale, commercial sodium silicate istraditionally manufactured by calcination of sodiumcarbonate (Na2CO3) and SiO2 at a temperature range of 1400–1500°C in furnaces (Folleto et al., 2006). Although the rawmaterials are cheap, the process is not cost-effective due to itshigh energy consumption and maintenance cost (Folleto etal., 2006). The process also emits dust, nitrogen, and sulphuroxides, contributing to air pollution. Alternatively, Na2SiO3can be produced by the reaction of SiO2 with NaOH solutionin an autoclave, at high temperature and pressure (McDanielet al., 1961). In light of the information at hand, it isnecessary to carry out an investigation on alternativemethods, which are less energy intensive, for producingNa2SiO3 for use as an additive to OWC. In addition, the SiO2,one of the raw materials required in the aforementionedalternative preparation method of Na2SiO3, can be obtainedfrom coal fly ash (CFA).

CFA is an inorganic powder that is produced during thecombustion of coal (Ahmaruzzaman, 2010). Several studieshave been carried out and reported on the beneficiation ofCFA (Iyer and Scott, 2001; Ahmaruzzaman, 2010; Taylor,1990; Kamarudin et al., 2009; Park et al., 2012).Beneficiation of fly ash from other materials such as ricehusks, bagasse, and corn cobs has also been reported(Aigbodion et al., 2010; Foleto et al., 2006; Okoronkwo etal., 2013). The use of CFA in OWC has been reported(Shahriar, 2011), but composition of the CFA differs fromcountry to country and this could affect its suitability asadditive in OWC operations. Furthermore, the use of raw CFAresults in slower strength gain and longer setting times,thereby resulting in low early-age strength and delays in thewell completion process (Bazzar et al., 2013). In SouthAfrica, about 25 Mt of CFA is produced annually and itsdisposal constitutes a huge environmental problem. In thisstudy, SiO2 was extracted from CFA and used as startingmaterial to synthesize Na2SiO3. The potential use of thesynthesized CFA-derived sodium silicate as an OWC extenderwas evaluated and compared with that of commercial sodiumsilicate (com- Na2SiO3).

Class G cement was obtained from Dyckerhoff, Germany, andCFA from a power station in South Africa. Demineralizedwater was prepared in-house. Hydrochloric acid solution(37%), sodium hydroxide pellets (98% purity), calciumchloride (99.99% purity), and commercial sodiummetasilicate (95%) were purchased from Sigma Aldrich andused as delivered without any modification or purification.

Small quantities of CFA were scooped randomly fromdifferent points and then mixed together to make therepresentative sample. The CFA samples were characterizedusing X-ray diffraction (XRD: Brucker D2 X-ray diffractionmachine), X-ray fluorescence (XRF: PANalytical AXIOS X-ray fluorescence spectrometer), scanning electron microscopy(SEM: Zeiss Sigma VP field emission scanning electron

microscope), and thermogravimetric analysis (TGA: TGA DSCSTA 600 with Pyris software). The pH of CFA (slurried inwater) was measured using a Metrohm 744 pH meter, andthe particle size distribution of the CFA was obtained using aMalvern Mastersizer 2000.

The metal oxides such as Al2O3 and CaO were removed fromCFA by acid refluxing using 3 M HCl at 100°C for 6 hours asdescribed by Tang et al. (2012). The solid product, SiO2, wasfiltered out and purified by successive washings withdemineralized water. The wet SiO2 was dried in an oven at200°C for 2 hours to obtain an amorphous silica powderwhich was then analysed using SEM-EDX, XRD, and Fouriertransform infrared spectroscopy (FTIR: Brüker Tensor 27Fourier transform infrared spectrometer). 60 g of theamorphous silica was reacted with 80 g sodium hydroxidepellets in 100 ml distilled water in a Pyrex flat-bottomed flaskat 80°C and atmospheric pressure to produce a colourlessviscous solution. The solution was then poured into acrucible and calcined at 300°C for 3 hours to produce a whitesolid (CFA-Na2SiO3) which was crushed to a powder using amortar and pestle. The product was then subjected to SEM-EDX, XRD, and FTIR analyses.

Slurries containing varying amounts of cement, distilledwater, 2% calcium chloride (CaCl2) by weight of water(BWOW), com-Na2SiO3, and CFA-Na2SiO3 were prepared andtheir densities, rheology, and thickening times evaluated. AChandler Ametek constant speed mixer (Model 30-60) wasused for mixing and the slurries were pre-conditioned using aChandler Ametek Atmospheric Consistometer (Model 1200)prior to the rheology tests. The rheology tests were conductedusing a Chandler Ametek automated viscometer (Model3530) and a Chandler Ametek pressurized mud balance wasused to determine the density of the slurries. A ChandlerAmetek twin cell ultrasonic cement analyser (UCA) (Model4262) was used to determine the development of compressivestrength of the slurries. All the tests on the cement slurrieswere carried out according to the specification for materialsand testing for well cements (American Petroleum InstituteSpecification 10A, 2002). The compositions of the slurries arepresented in Table I.

Figure 1 shows the XRD patterns for the CFA. The patternsare consistent with those reported for previously studiedSouth African CFAs (Ayanda et al., 2012; Mainganye et al.,2013; Ikotun et al., 2014). Table II shows the XRF analysisof the CFA together with results from reports in the literature(Ayanda et al., 2012; Mainganye et al., 2013). The majorcomponents of the CFA are silica, alumina, iron oxide,calcium oxide, and carbon (inferred from the loss on ignition(LOI) test). The CFA is of class F (ASTM C618, 2012). Themetal oxide contents decreased in the order SiO2> Al2O3>Fe2O3> CaO> MgO> K2O> Na2O> TiO2. This is consistent withprevious reports on South African CFA (Ayanda et al., 2012;Mainganye et al., 2013; Ikotun et al., 2014). Interestingly,

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the CFA contained about 58% SiO2, which is one of therequired materials for the synthesis of Na2SiO3.

The morphology of the CFA is depicted in the SEMmicrograph in Figure 2. The shapes of the CFA particles aredetermined by the exposure conditions (time andtemperature) in the combustion chamber (Fisher et al.,1978). As seen in Figure 2, most of the particles arespherical, especially in the finer fractions. A similarobservation has been reported for other South African CFAs(Ayanda et al., 2012; Mainganye et al., 2013). The particlesare a mixture of opaque and non-opaque spheres. Theopaque spheres are predominantly iron oxides and somesilicates, while the non-opaque spheres are mainly silicates(Fisher et al., 1978). Previous studies have shown that flyash is made up of, in some cases, smaller particles (<< 1 μm)which are attached to the surface of larger particles, hollowspheres (cenospheres), and some spheres containing otherspheres (plerospheres) (Mainganye et al., 2013). In addition,the SEM micrograph shows the presence of some non-spherical particles. These amorphous particles arise mainlyfrom incomplete combustion of coal components (Fisher etal., 1978). Furthermore, the TGA shows that the CFAcontains about 0.2% moisture, 1.6% volatile matter, and1.7% fixed carbon. The particle size ranges from 0.32–112µm. These results are also in agreement with previousstudies (Ayanda et al., 2012 ; Ikotun et al., 2014). A rise inpH from 7 to 10.7 was observed when the CFA was mixedwith de-ionized water over a period of 5 hours. This could beattributed to the dissolution of compounds such as CaO in theCFA. This observation is in good agreement with previousreports (Ayanda et al., 2012).

The morphologies of the extracted SiO2, synthesized CFA-Na2SiO3, and com-Na2SiO3 were characterized by SEM.Figure 3 shows the SEM images of the extracted SiO2. Similarimages for precipitated SiO2 have been reported in theliterature (Music et al., 2011). The elemental compositionsobtained using energy dispersivee X-ray spectroscopy (EDS)(not shown in this manuscript) indicated the presence of Siand O, confirming the presence of SiO2. The XRD pattern inFigure 4 shows the characteristic slope and pattern foramorphous SiO2, consisting of a broad band with a peakwhich indicates that the substance is amorphous andcontains pure SiO2 (Saikia et al., 2008; Essien et al., 2011;Music et al., 2011; Okoronwo et al., 2013). Similar patternsfor amorphous silica have been recorded in the literature(Saikia et al., 2008; Okoronwo et al., 2013). The two sharppeaks in the pattern are due to the presence of quartz,corroborating the results obtained from EDS. The FTIRspectrum of the SiO2 is depicted in Figure 5. The bands ofabsorption at 1199 cm-1, 964 cm–1, and 682 cm–1 can beattributed to the absorption peaks characteristic of SiO2(Ying-Mei et al., 2010). The absorption peak at 1199 cm–1


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0 44 792 15.8 15.80.25 68 677 14.0 14.00.5 78 638 13.4 13.50.75 104 555 12.5 12.4

1 78 637 13.5 13.41.5 80 627 13.1 13.02 88 595 13.0 12.8

2.5 100 556 12.8 12.6


corresponds to the asymmetrical stretching vibration of Si–O(Ying-Mei et al., 2010). In addition, the absorption peaks at964 cm–1 and 682 cm–1 correspond to the symmetricalstretching vibrations of Si–O groups on the surface of theamorphous solid (Ying-Mei et al., 2010; Essien et al., 2011).The stretch between 1500 cm–1 and 2000 cm–1 can beattributed to the presence of the Si–OH and bending vibrationabsorption of the O–H bond of physically adsorbed water,respectively (Music et al., 2011).

The XRD patterns for CFA-Na2SiO3 and com-Na2SiO3 areshown in Figure 6. The two patterns are similar, although asmall difference in the intensities of some of the peaks wasobserved. Curve fitting showed that there is a slight shift inthe peaks of CFA-Na2SiO3. The shift in the peaks could beattributed to the small quantity of the sample used in theanalysis. Figure 7 depicts the SEM images for CFA-Na2SiO3and com-Na2SiO3. The morphology of the CFA-Na2SiO3 istotally different from that of com-Na2SiO3. However, the EDSresults showed the same elemental components with differentcompositions. Figure 8 shows the FTIR spectra for the com-Na2SiO3 and CFA-Na2SiO3. The FTIR analysis of the twosamples indicates that there is no observable chemicaldifference between the samples. Both samples showabsorption bands at 2340 cm-1, 1160 cm–1, 1125 cm–1, 980 cm–1, and 715 cm-1 that characterize the presence ofsodium metasilicate (Miller and Wilkins, 1952). The stretchbetween 1500 cm–1 and 2000 cm–1 could be attributed to thepresence of Si–OH and bending vibration absorption of the O–H bond (Ying-Mei et al., 2010).

The compositions and the densities of the slurries preparedusing CFA-Na2SiO3 and com-Na2SiO3 as additives are shownin Table I. The slurries had similar densities, with slightdifferences as the amount of additive added increased. Someof the slurries containing CFA-Na2SiO3 had slightly lowerdensities compared to the slurries containing com-Na2SiO3.There was a 0.02% difference in the densities of the slurriescontaining 2% additive (CFA-Na2SiO33 and com-Na2SiO3).The difference may be due to the fact that slurries preparedusing CFA-Na2SiO3 contained a lot of froth. The rheologies ofslurries prepared using CFA-Na2SiO3 and com-Na2SiO3 asadditives are shown in Tables III and IV, respectively. The

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slurries prepared using both additives exhibited goodrheology, with plastic viscosities (Pv) between 3.75 and18.75 cp and yield points (Yp) between 13.5 and 61.75lb/100 ft2. The slurries containing com-Na2SiO3 generallyhad higher rheological values than those prepared using theCFA-Na2SiO3. At 60 r/min the viscosity of the slurrycontaining 1% com-Na2SiO3 was 45 cp, while that for theCFA-Na2SiO3 slurry was 26 cp. The slurries prepared usingCFA-Na2SiO3 were less viscous and this can be attributed tothe presence of froth.

It is known that the use of sodium silicate as a waterextender in OWC operation helps to prevent breakdown ofweak formations and loss of circulation (Nelson et al., 1990).In addition, it helps to lower the hydrostatic pressure, therebyenhances the ‘pumpability’ of the cement slurry (Nelson etal., 1990). When sodium silicate is used as a water extenderin OWC operation, it reacts with calcium hydroxide in thecement slurry to produce a viscous C-S-H gel that allowsaddition of large volume of water to the slurry, thereby


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SiO2 57.9 55.66 51.43Al2O3 31.12 27.95 30.93Fe2O3 0.33 3.22 2.29FeO 2.65 NR NRMnO 0.04 0.04 0.02MgO 0.95 1.91 1.95CaO 4.28 4.38 6.75Na2O 0.13 0.31 0.54K20 0.66 0.48 0.77TiO2 1.519 1.13 1.74P2O5 0.39 0.26 1.08Cr2O3 0.0223 0.03 0.02NiO 0.0008 NR 0.01LOI 0.73 4.74 1.21Sum 100.72 100.07 99.28


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300 29 42.5 21.5 59 76 64 70200 24.5 37 18.5 52 70.5 59 67.5100 24 33 19 46.5 64 56 64.560 23 31.5 19 45 60 56 6330 22 30 19.5 23.5 56 54 55.56 15 19 14 23 32 38.5 333 12 12 11.5 20 26 27 29.5

Pv (cp) 7.5 14.25 3.75 18.75 18 12 8.25Yp (lb/100 ft2) 21.5 28.25 17.75 40.25 58 52 61.75

300 31.5 43.5 24 37 31 44.5 40.5200 24.5 38.5 19 33 25.5 40 36.5100 19.5 36 18.5 26.5 24 37.5 3360 17.5 32.5 19 26 23 36.5 31.530 15 31 17 27 21 36.5 31.56 8.5 17.5 14.5 15 16.5 22.5 223 10 8.5 12 11.5 10.5 19 17

Pv (cp) 18 11.25 8.25 15.75 10.5 10.5 11.25Yp (lb/100 ft2) 13.5 32.25 15.75 21.25 20.5 34 29.25

0.34 MPa (h: min) 2:12:00 2:09:00 3:22:30 2:12:00 2:49:00 3:11:30 3:40:003.4 MPa (h: min) 7:26:00 8:58:00 _ 7:41:00 22:47:00 _ _8 h compressive strength (MPa) 3.64 3.21 1.32 3.65 2.08 1.94 1.6612 h compressive strength (MPa) 4.54 4.02 1.68 4.75 2.87 2.53 2.0624 h compressive strength (MPa) 6.35 5.11 2.38 5.66 3.53 2.89 2.51

0.34 MPa (h: min) 1:59:30 2:28:30 3:14:00 2:01:30 2:36:00 3:00:00 2:43:03.4 MPa (h: min) 5:41:00 8:45:30 _ 7:37:30 21:43:30 _ _8 h compressive strength (MPa) 4.44 3.25 1.63 4.15 2.20 2.12 1.7512 h compressive strength (MPa) 5.81 4.12 2.21 4.93 3.03 2.63 2.4224h compressive strength (MPa) 7.67 5.70 3.11 5.77 3.97 2.95 3.10

reducing the density of the slurry and increasing its yield.From the results from the rheology analysis of the CFA-Na2SiO3 prepared from CFA in this study and tested in theformulation of OWC slurries, it is obvious that slurriesprepared with CFA-Na2SiO3 might be preferable to thoseprepared with com-Na2SiO3 for an OWC operation thatrequires early strength development.

Tables V and VI show the compressive strength resultsfor slurries containing com-Na2SiO3 and CFA-Na2SiO3,respectively. As expected, there was a decrease incompressive strength for all slurries as the amount of wateradded increased. This is consistent with findings from theliterature. An increase in water-to-cement ratio results in adramatic decrease in the compressive strength of the slurries(Fawzi, 2012), Figures 9–11 show that the slurriescontaining CFA-Na2SiO3 had higher compressive strengththan those containing com-Na2SiO33 at 8 hours, 12 hoursand 24 hours. From Tables V and VI, it can be observed thatthe CFA-Na2SiO3 slurries gained a compressive strength of0.34 MPa earlier than the Na2SiO3 slurries. This is theminimum strength required to hold the casing in position. Inaddition, the earlier gain of the compressive strength by thewith CFA-Na2SiO3 slurries indicates that the slurries withCFA-Na2SiO3 set quicker than those with com-Na2SiO3. Theresults obtained from the ultrasonic cement analyser (UCA)

also indicate that the same observation was obtained forslurries that attained a compressive strength of 3.4 MPawithin the first 24 hours. A strength of 3.4 MPa is sufficientto hold the casing when further drilling or perforation of thecasing is required.

The results indicate that the South African CFA used in thisstudy is a Class F CFA and contains 58% amorphous SiO2.The physico-chemical properties of the synthesized Na2SiO3are consistent with those of the commercial Na2SiO3,indicating the purity of the as-prepared Na2SiO3 from theCFA. In addition, the synthesis protocol, which was at a mildtemperature, confirms the energy efficiency of the methodused. Cement slurries prepared with CFA-Na2SiO3 showbetter performance than those prepared with com-Na2SiO3.Rheological testing indicated that the slurries prepared withCFA-Na2SiO3 are less viscous than those prepared with com-Na2SiO3. The CFA-Na2SiO3 slurries will thus be easier topump and handle during OWC operation compared to theslurries prepared with com-Na2SiO3. UCA analysis showedthat the slurries prepared with CFA-Na2SiO3 have highercompressive strength in comparison to those prepared fromthe com-Na2SiO3. Although a small concentration of sodiumsilicate (0.2% to 3.0% BWOC) is always used in OWCoperations to yield a reasonable compressive strength(Nelson et al., 1990), the higher compressive strength of theslurries with CFA-Na2SiO3 implies that smaller amounts ofCFA-Na2SiO3 will be required for OWC operations. Inaddition, slurries prepared with CFA-Na2SiO3 will bepreferable to those prepared with com-Na2SiO3 for an OWCoperation that requires early strength development. Theresults of this study could provide a platform for furtherresearch development on the beneficiation of South AfricanCFA in the petroleum, oil, and gas industry.

The authors hereby acknowledge the financial support fromChemical Industries Education and Training Authorities(CHIETA) South Africa and Baker Hughes South Africa(Mossel Bay) for availing their cement testing laboratoryfacility for use in this study.


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AHMARUZZAMAN, M. 2010. A review on the utilization of fly ash. Progress inEnergy and Combustion Science, vol. 36, no. 1. pp. 327–363.

AIGBODION, V.S., HASSAN, S.B., AUSE, T., and NYIOR, G.B. 2010. Potentialutilization of solid waste (bagasse ash). Journal of Minerals and MaterialsCharacterization and Engineering, vol. 9, no. 1. pp. 67–77.

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ASTMC618. 2012. Standard specification for coal fly ash and raw or calcinednatural Pozzolan for use in concrete.

AYANDA, O.S., FATOKI, O.S., ADEKOLA, F.A., and XIMBA B. J. 2012.Characterization of fly ash generated from Matla Power Station inMpumalanga, South Africa. E-Journal of Chemistry, vol. 9, no. 4. pp. 1788–1795.

ESSIEN, E.R., OLANIYI O.A., ADAMS L.A., and SHAIBU R.O. 2011. Highly poroussilica network prepared from sodium metasilicate. Journal of Metals,Materials and Minerals, vol. 21, no. 2. pp. 7–12.

FAWZI, R.H. 2012. Thickening time and compressive strength correlations forBentonitic –class ‘G’ cement slurries. Iraqi Journal of Chemical andPetroleum Engineering, vol. 13, no. 2. pp. 37–45.

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IKOTUN, B.D., MISHRA, S., and FANOURAKIS G.C. 2014. Structural characterizationof four South African fly ashes and their structural changes with β-cyclodextrin. Particulate Science and Technology, vol. 32, no. 4. pp. 360–365.

IYER, R S. and SCOTT, J.A. 2001. Power station fly ash - a review of value-addedutilization outside of the construction industry. Resources, Conservationand Recycling, vol. 31. pp. 217–228.

JOEL, O.F. and UJILE, A.A. 2009. Performance evaluation of low densitybentonite and econolite cement, Nigeria. International Journal of Naturaland Applied Science, vol. 5, no. 4. pp. 322–328.

KAMARUDIN, R.A., MATLOB, A.S., JUBRI, Z., and RAMLI Z. 2009. Extraction of silicaand alumina from coal fly ash for the synthesis of zeolites. Proceedings ofICEE 2009, 3rd International Conference on Energy and Environment,Malacca, Malaysia, 7–8 December 2009. IEEE, New York.

LEA, F.M. 1971. The Chemistry of Cement and Concrete. Chemical PublishingCompany Inc., New York, USA.

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MILLER, F.A. and WILKINS, C.H. 1952. Infrared spectra and characteristicfrequencies of inorganic ions: their use in qualitative analysis. AnalyticalChemistry, vol. 24, no. 8. pp. 1253–1294.

MUSIC, S., VINCEKOVIC, N.F., and SEKOVANIC, L. 2011. Precipitation of amorphousSiO2 particles and their properties. Brazilian Journal of ChemicalEngineering, vol. 28, no. 1. pp. 89–94.

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Austenitic stainless steels are widely used forstructural applications in the petrochemical,telecommunication, aerospace, and food-processing industries. This is due to theirexcellent corrosion resistance and goodmechanical properties, such as toughness,ductility, and formability (Bain and Griffiths,1927; Jenkins et al. 1937; Zapffe, 1949).However, due to the austenitic structure, thesesteels have quite low surface hardness andpoor wear resistance (Bell, 2002; Fewell et al.,2000). To improve the surface properties,diffusion and thermochemical surfacetreatment techniques such as carburizing(Agarwal et al., 2007; Fewell et al., 2000),nitriding (Bell, 2002), nitro-carburizing(Renevier et al., 1999) and ion implantation(Liang et al., 2007) have been used, withoutimpairing the corrosion resistance of the steel

(Bell, 2002; Renevier et al., 1999). Thetreatment temperatures were kept below 500°Cto prevent the formation of chromium carbidesand nitrides, which deplete chromium from thematrix and reduce corrosion resistance (Matulaet al., 2001).

Little has been reported on the packcarburizing of austenitic stainless steels andits effects on the mechanical properties. This isprobably because pack carburizing of thesestainless steels is considered a difficultprocess, due to the presence of the Cr2O3 oxidesurface layer (Davis, 1994; Mingolo et al.,2006). The tenacious Cr2O3 surface layerserves as an inhibiting barrier and is also self-healing, which contributes to the ‘stainless’characteristic of stainless steels. However, itwas felt a worthwhile endeavour to ascertainwhether this cheaper method could be used.Other forms of carburizing, such as gas andplasma, are normally used for stainless steelrather than pack carburizing, which is morecommonly used for medium- and low-carbonsteels (Agarwal et al., 2007; Fewell et al.,2000; Renevier et al., 1999). The majorparameters that influence carburizing aresoaking time, carburizing temperature, andcarbon potential (Shewmon, 1963).

As a high proportion of mechanical failuresare due to fatigue, extensive research is beingdone in this area (Akita and Tokaji, 2006).Nucleated fatigue cracks grow into macro-cracks, resulting in catastrophic failures.Initiation of fatigue is a surface phenomenon,and approximately 80% of all engineering

Mechanical behaviour of packcarburized AISI 316L austeniticstainless steel by D.E.P. Klenam*†, C. Polese†‡, L.H. Chown*†, S. Kwofie‡‡,and L.A. Cornish*†

The effect of surface hardening by pack carburizing on the mechanicalproperties of AISI 316L steel was studied. Pack carburizing with 60 wt%BaCO3, 30 wt% activated carbon, and 10 wt% sodium chloride was carriedout at 450, 550, 650, 700, and 750°C for 24 hours and the specimens werefurnace-cooled. Tensile, impact, hardness, and fatigue tests wereconducted, and SEM and was used to characterize the specimens.

The ultimate tensile strength of the as-received steel was similar tospecimens carburized at 450 and 550°C (approx. 650 MPa), but decreasedfrom 638 to 603 MPa with further increase in carburizing temperature from650 to 750°C.

Hardness profiles of the specimens treated at 450°C and 550°C weresimilar to the as-received steel, at approximately 250 HV0.5. Typical casehardening profiles were obtained for specimens carburized at 650, 700, and750°C.

The number of cycles to failure (N) of the as-received specimens wasclose to 60 000, which was similar to those carburized from 450 to 650°C.Further increase in carburizing temperature decreased the cycles to failureto approximately 25 000 (700°C) and 7000 cycles (750°C).

Crack initiation was mainly characterized by cleavage (mode I) for alltested carburized and as-received specimens. Specimens carburized at 450,550, and 650°C also showed secondary cracking. The final rupture zonecontained ductile fracture with dimples, and the specimens showedextensive plastic deformation.

316L austenitic stainless steel, mechanical behaviour, fractography, packcarburizing.


† DST-NRF Centre of Excellence in Strong Materials,University of the Witwatersrand, Johannesburg.

‡ School of Mechanical, Industrial and AerospaceEngineering, University of the Witwatersrand,Johannesburg.

‡‡Department of Materials Engineering, KwameNkrumah University of Science and Technology,Kumasi, Ghana.

© The Southern African Institute of Mining andMetallurgy, 2015. ISSN 2225-6253. Paper receivedMay 2015 and revised paper received Oct 2015.

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Mechanical behaviour of pack carburized AISI 316L austenitic stainless steel

failures are due to fatigue, which is a cause for concern insurface-modified structures and components (Berrı os et al.,2001; Berrıos-Ortız et al., 2004). Fatigue behaviour ofaustenitic stainless steels with their surfaces modified bytechniques such as plasma carburizing and nitriding, ionimplantation, shot peening, and physical vapour deposition ofcoatings with TiN, CrN and ZrN has been studied by Ceschiniand Minak (2008), Fewell et al. (2000), Agarwal et al.(2007), Azar et al. (2010), Berrı os et al. (2001), Collins et al.(1995), Liu et al. (2003), Samandi et al. (1993), and Berrı os-Ortız et al. (2004). Surface hardness, wear resistance, andfatigue strength were improved by most of these techniques(Berrıos et al., 2001; Berrı os-Ortız et al., 2004; Ceschini andMinak, 2008). Much work has been done on fatigue instainless steels, but there is no study on pack carburizedaustenitic stainless steels.

This research was conducted to study the effects of packcarburizing on the mechanical properties and microstructureof AISI 316L stainless steel, and to ascertain which temper-atures in the range of 450 to 750°C would provide a suitablecarburized case.

As-rolled AISI 316L stainless steel plates (1000×1000×30 mm) containing 17.1 wt% Cr were purchased and thecomposition was determined by optical emission spectroscopy(Table I).

Flat tensile specimens (dogbone shaped) were machinedfrom the as-received plate in the longitudinal rolling directionaccording to ASTM E8. The length of each sample was 60 mmwith the gauge length of 7 mm and thickness of 12 mm. Thefatigue specimens having continuous curvature weremachined according to ASTM STP91-A. The dimensionswere: gauge length of 23 mm, radius of curvature of 190 mm,and a thickness of 6 mm. The Charpy V-notch specimens(45°, 2 mm deep notched bar of length of 55 mm and 10×10 mm thick) were machined according to ASTM A370(ASTM Standards, 2000). The Charpy V-notch specimenswere all notched before the carburizing heat treatment wasdone. All tests were done in triplicate at all carburizingtemperatures.

A container with a lid of dimensions 145×80×80 mm wasfabricated from mild steel for the carburizing heat treatment.The tensile, fatigue, and Charpy V-notch specimens werepack carburized in the container with 60% BaCO3 (as theenergizer), 30% activated charcoal (source of carbon), and10% NaCl (activator). The carburizing heat treatment wasdone at temperatures of 450, 550, 650, 700, or 750°C for 24hours in a Lenton® muffle furnace, followed by furnacecooling.

Tensile tests were performed according to ASTM E8 usinga Tinius Olsen® tensile testing machine under a uniaxial load.

Fatigue tests were performed according to ASTM STP91-Ausing an Instron 1342® fatigue testing machine. The testingwas performed at a peak stress of 500 MPa with a stress ratioR of 0.1 (where R = minimum peak stress / maximum peakstress), stress range of 1, and a frequency of 7 Hz. Thefractured sample was cut for secondary electron imaging ofthe fractured surfaces using a FEI Nova® NanoSEM 200.Room-temperature Charpy V-notch impact tests wereperformed on three impact test samples for each carburizingtemperature, according to ASTM A370 (ASTM Standards,2000). All mechanical tests were performed on packcarburized specimens and on as-received specimens forcomparison.

Transverse sections of the carburized and tested sampleswere prepared metallographically to examine themicrostructure from the surface to the centre. The finalpolishing was done using a colloidal silica suspension onsatin woven acetate cloth. The polished specimens werechemically etched using 15 ml HCl, 10 ml HNO3, and 10 mlethanol for approximately 8 minutes and were then rinsed inalcohol and water. Scanning electron microscopy with EDXwas used to study the microstructures of the as-received andthe carburized specimens.

Micro-Vickers hardness testing was done on sectionedsamples from the surface to the centre of the carburized andas-received steel specimens, using a load of 500 g and adwell time of 10 seconds. Hardness-depth profiles were thenplotted.

The effects of carburizing on the ultimate tensile strength(UTS) of AISI 316L steel is shown in Figure 1. Within error,the ultimate tensile strength was unchanged at approximately651 MPa for carburizing temperatures of 450°C and 550°C,which is marginally higher than the as-received steel (648 MPa). Further increase in temperature caused a sharpdecrease in UTS to 638 MPa (650°C), 627 MPa (700°C), and603 MPa (750°C).

The effect of carburizing temperature on ductility isshown in Figure 2. The total elongation was almostunchanged with increasing temperature up to 650°C (46-45%compared to the as-received 49%) and decreased moresharply above 650°C to 32% at 750°C. An increase intemperature had a stronger effect on decreasing the reductionin area (% RA). The RA after carburizing at 450°C was thesame as the as-received at 79%, and dropped to 65% at650°C and 45% at 750°C.

The impact energy of the as-received AISI 316L steel was272 J. After carburizing between 450-750°C, the impactenergies decreased with increasing temperature, as shown in

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wt% 0.025 0.42 1.00 0.032 0.031 17.12 2.11 10.13 0.449 0.056 bal.

Figure 3, from 257 J at 450°C showing a constant drop inimpact energy with increasing carburizing temperature from550°C (243 J) to 750°C (132 J).

The microhardness measurements for the as-receivedmaterial varied, with an average surface hardness of 255HV0.5 and a core hardness of 248 HV0.5. The specimens thatwere carburized at 450 and 550°C showed only smalldifferences in hardness between the surface and the core,ranging from 246–255 HV0.5, as shown in Figure 4a. Not allthe carburizing compound in the case burnt off, thuscarburizing was not properly achieved at these two temper-atures. However, the surface hardness did increase nominallywith increasing temperature for samples carburized attemperatures of 650, 700 and 750°C (Figure 4b). Thesespecimens showed a hardness profile similar to that found incase hardening, with higher hardnesses at the surface andcore hardnesses similar to the as-received material. The casedepth is related to the amount of carbon diffused inwards

from the surface (Ceschini and Minak, 2008), with the extentof the case indicated by the position where there is a suddendrop in hardness. At 650°C, there was a negligible increase ofapproximately 5 HV0.5 in the hardness of the surfacecompared to the core; and at 700°C and 750°C the increaseswere approximately 25 HV0.5 and 42 HV0.5 respectively.

The as-received sample had similar microstructures at thesurface and core as the sample treated at 550°C (Figures 5a


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and b), showing austenite grains, annealing twins, pores,and some oxides. Figure 5b shows deformation at the samplesurface from the rolling process of the as-received steel.There were prominent grain boundaries and etch pits (asfound by Fong and Tromans, 1988) throughout themicrostructure. No carbides were found by EDX analysis inthe specimens treated at 450°C or 550°C. The passive oxidelayer on the surface of the sample carburized at 550°C wasapproximately 8.0 μm thick (Figure 6).

The core and near-surface microstructures of the samplescarburized at 700°C also showed austenite grains, annealingtwins, slip lines, and pores. Grooved grain boundaries wereformed at the core and at the near surface. Intergranularoxidation at the surface of the samples (Figures 7a and b)could be possible, but not at the core since the diffusion ofoxygen at temperatures of 550–750°C for 24 hours would be

too sluggish for penetration to the core. The grooved grainboundaries at the core could be attributed to the combinedeffect of sensitization and etching, which produce similareffects in austenitic stainless steels in the ranges of 450–800°C (Agarwal et al., 2007; Ceschini and Minak, 2008).EDX analyses revealed a higher amount of carbides andoxides near the surface compared to the core (Table II). Thethin white layer on the surface (Figure 7b) contained calciumand chloride compounds from the carburizing chemicals andthe etchant (Figure 7b). There were more slip lines andsmaller grains at approx. 50 μm beneath the surface on thenear surface (Figure 7b), due to deformation from thefinishing rolling.

Micrographs of samples carburized at 750°C (Figures 8aand b) revealed similar microstructural features to the lowertemperature treatments in terms of grain size, carbides,oxides, and voids. Both the core and the near surfaceunderwent grain boundary oxidation. There were more poreson grain and sub-grain boundaries and fewer annealingtwins (Figure 8) than at lower carburizing temperatures. Thecarburized layer was measured as approximately 95–103 μmthick (Figure 9). The grain boundaries became moreprominent with increased carburizing temperature.

The effect of carburizing temperature on the fatigue strengthof AISI 316L austenitic stainless steel is shown in Figure 10.The fatigue behaviour of samples carburized at 450 to 650°Cwas similar to the as-received sample, with 50–60 thousandcycles to failure (N). Lower cycles to failure were observed atcarburizing temperatures of 700°C (N approx. 26 000), and750°C (N approx. 8 000), indicating decreasing fatigueresistance of the steel with increase in testing temperature.

Visual inspection of the fractured fatigue surfacesidentified ratchet marks and ‘thumbnails’, indicating regionsof slow growth, where the crack was able to maintain itspreferred orientation transverse to the applied stress(Roylance, 2001). Macro-examination showed that the edgesof the fractured surface were slightly brighter and shiny, afeature known as small fatigue cracks (Ritchie and Lankford,

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1986; Agarwal et al., 2007; Ceschini and Minak, 2008;). Thefractured surfaces of samples carburised at 450, 550, and650°C showed more secondary cracking and fatigue pre-


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cracks along the sides than samples carburized at 700 and750°C.

SEM examination of the fractured surfaces of all samplesshowed the crack initiation, propagation, and rupture zones.Cleavage was the characteristic feature of the crack initiationzone (around the edge of the fatigue specimen), withsecondary cracking (indicated by an arrow in Figure 11a) forsamples carburized at 450°C. The initiation zones showedbrittle cleavage, which is a characteristic feature of fatiguecrack initiation zones (Fong and Tromans, 1988). The crackpropagation zone in Figure 11b shows areas of fatiguestriations at regions around the core. The final rupture for theas-received sample was ductile fracture with dimples andmicro-voids nucleated within the surface (Figure 11c).

After carburizing at 650°C, the crack initiation stage wascharacterized by cleavage and dispersed secondary cracking,as shown in Figure 12a. As the cracks propagated, fatiguestriations were also found on the fracture surface (Figure12b). At lower magnification (Figure 12c), the rupture zoneshowed a step-like pattern. Fractographs of samplescarburized at 700 and 750°C (not shown) displayed similarcharacteristic features to those treated at the lower temper-atures.

The fracture surfaces of the Charpy test samples wereanalysed using SEM. The as-received samples (Figure 13a)and samples carburized at 450°C (Figure 13b) and 550°C

showed dimples and microvoid coalescence, which arecharacteristic of ductile fracture. After carburizing at 650,700, and 750°C, the fracture surface showed evidence oftransgranular brittle fracture. This is shown in Figure 13c forthe sample carburized at 750°C.

When compared to the as-received sample, carburizing theAISI 316L steel at 450°C slightly improved the ultimatetensile strength, caused marginal decreases in ductility (bothelongation and reduction in area), and was detrimental totoughness. At 550°C, the ultimate tensile strength was thesame as for 450°C, but the ductility and toughness werelower. Above 550°C, these bulk mechanical properties werecompromised, as shown by the incremental loss of ultimatetensile strength, ductility, and toughness with increasingcarburization temperature. This was due to the increasedcoarsening of grain boundary carbides (Fong and Tromans,1988).

Micrographs of all carburized specimens showedintergranular voids and oxidation along the grain andsubgrain boundaries. These defects are potential nucleationsites for cracks (Zavattieri and Espinosa, 2001). Uniaxialtension around these defects could lead to crack opening andthe oxides can act as brittle zones (King and Cotterill, 1990),decreasing ductility and toughness of the AISI 316L steel. At

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450 and 550°C, strengthening from carbon uptake wasslightly more beneficial than the negative effect fromintergranular oxidation, as seen by the higher tensilestrength values.

The amount of carbon that diffused into the steel at 450and 550°C was too low to significantly increase the surfacehardness (Figure 4a). Pores and annealing twins in theaustenitic microstructure caused the slight variations in thehardness of these samples and the as-received material. Thetenacious, self-healing 8.0 μm thick Cr2O3 layer that formedon the steel surface prevented an increase in surfacehardness, as these carburizing temperatures and times wereinsufficient for carbon to diffuse through this inhibitive

surface layer. In contrast, the plasma and gas carburizingprocesses produce permeable oxide layers, which allowenough carbon diffusion into the steel (Renevier et al., 1999;Fewell et al., 2000; Bell, 2002). Thus, high hardness valuescan be obtained by these processes.

Samples treated at higher temperatures of 650 to 750°Cshowed hardness profiles similar to those achieved by casehardening, with higher hardness at the surface and corehardness values similar to that of the as-received steel. Thehighest surface hardness was 294 HV0.5 (750°C), which is18% higher than the core hardness. This indicates amoderate intake of carbon and surface carbon enrichmentfrom the carburizing treatment, which also contributed to thedecrease in the ductility and toughness. The presence oftwins could also increase the hardness, although theannealing twins were fairly well-distributed throughout thesteel and were not concentrated towards the surface. Twinboundaries are known to impede dislocation motion (Lu etal., 2009), which would also contribute to the hardness.However, the main contribution to the higher near-surfacehardness was the increasing carbon content from the core tothe surface of the stainless steel.

Surface hardnesses of up to 1400 HV have been reportedfor plasma and gas carburized AISI 316L steel (Fewell et al.,2000; Mingolo et al., 2006). This is substantially higher thanthe maximum of 294 HV0.5 found for the pack carburizedsamples in this work. The very high surface hardnesses fromthese carburizing methods can be attributed to highcompressive residual stresses from lattice distortion byinterstitial carbon, facilitated by the diffusion of carbonthrough the permeable surface oxide (Fewell et al., 2000;Mingolo et al., 2006).

In XRD spectra, shifts in the austenite peaks to lowerdiffraction angles indicate compressive residual stresses,which usually improve the mechanical properties (Mingolo etal., 2006). However, the XRD patterns of the carburizedsamples in this work (not shown) did not display shifts inthe austenite peaks. This indicates that there was littleinterstitial carbon uptake, no substantial change in latticesize occurred, and that negligible compressive residualstresses were induced. A 4% by volume content is required toreliably detect a phase by XRD (Liu, 2006), and the smallamounts of carbides and oxides identified by EDX werebelow this limit. Carbides, which can be detrimental to thecorrosion resistance of the AISI 316L steel (Bell, 2002), werepresent in small amounts in both as-received and carburizedsamples, as shown by the precipitation at the grainboundaries and within the grains. There was only a very thinobservable carburized case.

The number of cycles to failure for the as-received AISI316L steel and samples carburized from 450–650°C rangedfrom approximately 52 000 to 61 500 (Figure 10), showingthat the fatigue resistance was similar. As the carburizingtemperature increased above 650°C, the number of cycles tofailure decreased significantly: approximately 26 000 at700°C and 7 100 at 750°C. Although carburizing at temper-atures above 650°C has been reported to lead to stress reliefof the compressive stresses and a significant decrease infatigue strength (Gelfi et al., 2005; Ceschini and Minak,2008), here the surface had already been removed by themachining of the fatigue samples. Thus, the decrease in the


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fatigue strength is more likely to be due to the coarsening ofcarbides on the grain boundaries at higher carburizingtemperatures, which would then have less effect in reducingthe initiation and growth of fatigue cracks. Also, the oxidesand voids act as imperfections in the material, which couldalso have been a contributing factor (Lampman, 1997).

The fractured surfaces of the as-received and all of thecarburized samples showed cleavage fracture at the initiationstage. SEM examination of the as-received steel fracturesurface showed that crack initiation occurred at the surface,which could be attributed to the cyclic and fatigue slip bands(Ceschini and Minak, 2008). Fatigue slip bands, also calledpersistent slip bands (PSBs), are zones of high cyclic slipactivity (Lukáš and Kunz, 2004). The cyclic plasticdeformation within PSBs result in surface extrusion andintrusion along the traces of the active slip plane, and fatiguemicro-cracks start from these surface intrusions. Theinitiation of these cracks is also attributed to surface defectssuch as machining lines, notches, and stress concentrationsites (Akita and Bell, 2002; Tokaji, 2006; Agarwal et al.,2007). Cleavage is a Mode I type of fracture, in which shearstresses act parallel to both the crack front and the plane ofthe crack (Yates and Mohammed, 1996; Tvergaard, 2008; DeFreitas et al. 2011). The as-received and the carburizedsamples up to 650°C exhibited acceptable ductility, higherthan 65% RA and 45% elongation. Above 650°C, cleavagewas observed, which could be attributed to loss in ductilityand toughness due to the coarsening of the grain boundarycarbides.

Brittle fracture is characterized by quasi-cleavage, lowrelease energy, and minimal plastic deformation (Hull, 1999).These features were absent in the fractured surfaces of theas-received and carburized samples. The increasedcarburizing temperature enhanced the formation of brittlecarbides and grain boundary oxides (Zavattieri and Espinosa,2001), contributing to the decreased ductility and cleavage ofthe carburized samples at the crack initiation zones. Thefractures originated on the surfaces of the samples, andpropagated towards their cores.

The crack propagation zones in all fatigue specimensshowed striations, beach marks, and a few secondary cracks,all characteristic features of fatigue failure (Akita and Tokaji,2006; Bell, 2002). Striations can be attributed to micro-depressions induced in the structure, with the plane normalto the fracture surface, confirming the hollow micro-relief offatigue striations (Grosskreutz and Waldow, 1963; Ceschiniand Minak, 2008). The formation of striations was also dueto decohesion along the sub-grain boundaries and possibleinitiation sites for secondary cracking (Jin-Bo and Chen,1988; Yang et al., 2008). Secondary cracks are formed byincreased stresses due to voids, and occur at sites wherethere are micro-stress raisers and material defects duringcrack propagation (Jin-Bo and Chen, 1988). Twinning iscaused by continuous mechanical deformation, which leadsto discontinuity on the surface of the material, hence creatinga site for crack nucleation when stress or strain is applied(James, 1981). Secondary cracks formed along twin bandsand propagated below the primary fracture surface (Yang etal., 2008).

The final rupture zones of the as-received and carburizedsamples showed more ductile dimple rupture than brittlefracture. Ductile dimple rupture occurred by the formation

and coalescence of micro-voids along the fracture path. Therewere faceted patterns within the fractures, suggestingincremental tearing, which could be due to either chemical ormicrostructural segregation patterns (Gao et al., 1995).

Fractured surfaces of the as-received AISI 316L andsamples carburized at 450°C and 550°C showed predomi-nantly ductile fracture, with dimples, microvoid coalescence,and an irregular and fibrous surface, which indicated plasticdeformation (Hull, 1999). The dimples on the crack surfaceare attributed to dislocation movements, which coalesce intograin boundary voids. The carbon diffusion was low andcould not cause a major change in the microstructure, nor inthe ductility, at these temperatures. At 650°C and above, thefracture appearance was more brittle, with more faceting,which is a characteristic feature of transgranular fracture(Hull, 1999). The Charpy toughness is a bulk materialproperty and the carburizing effect was very shallow, in theorder of 100 µm. Therefore, reduced Charpy toughness couldnot be attributed to the carburizing effect, but ratherattributed to the coarsening of grain boundary carbides,which is known to cause a decrease in toughness foraustenitic stainless steels (Fong and Tromans, 1988).

The tensile behaviour was more sensitive to carburizationthan the fatigue behaviour. The tensile and fatigue specimenshad different geometries, but this probably did not have amajor effect, as the thicknesses were within 1 mm. All testpieces were mixtures of carburized layers and non-carburizedcores, and the different proportions of these would have hadan effect on mechanical properties. The tensile specimenswere slightly thicker (7 mm diameter) than the fatiguespecimens (6 mm thickness), and the surface to volume effectof the specimens would have meant that the proportion of thecarburized layer of the fatigue specimens was slightly higher,due to their flat, rectangular cross-sections. However, sincefatigue is a surface phenomenon, it would not be affected bythe proportions of carburized to non-carburized material,although the tensile specimens would be affected. For tensile(and impact) tests and fatigue tests, the cracks initiated atdifferent positions. Cracks initiated at the surface of thefatigue specimens, with some secondary cracks found on thesub-surfaces, whereas cracks initiated within the core oftensile and impact (around the notches) specimens. Thus, thedecreased impact toughness and UTS of the carburized steelcould be attributed to the brittle carbides and oxides thatformed during carburizing, resulting in coarse grains (Figures5–8) allowing for easy crack propagation.

From this work, pack carburizing was shown to beunsuitable for AISI 316L stainless steel, as the process signif-icantly reduced the ductility, ultimate tensile strength, andimpact toughness. The plasma and gas carburizingtechniques, in contrast, are known to considerably improvemechanical properties.

Surface hardness was unchanged at carburizing temperaturesof 450 and 550°C, but increased with increasing temperatureabove 550°C due to intergranular and intragranular carbideprecipitation.

An increase in pack carburizing temperature to 650, 700,or 750°C adversely influenced the mechanical properties ofAISI 316L austenitic stainless steel by decreasing theductility, toughness, tensile strength, and fatigue resistance.

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The mode of failure was mostly cleavage, fatigue failure,and ductile dimples, with some secondary cracking frommicrovoid coalescence.

In summary, the process of pack carburizing at or above650°C was found to be unsuitable for increasing the fatigueresistance of AISI 316L austenitic stainless steel, andcarburizing below 650°C gave no benefit.

The authors thank the Department of Science and Technologyand the National Research Foundation, South Africa forproviding funding for this research. They also thank MrRichard Couperthwaite of the Advanced Materials Division,Mintek, for help with the SEM imaging and analysis.

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Gypsum is a waste product generated byvarious industries, such as the mining, powergeneration, and fertiliser industries. Forinstance, phosphate fertilizer production usingthe ‘wet process’ generates phosphoric acidwhich in turn generates around 4.5 t of wastegypsum per ton of phosphoric acid. Foskor, theonly current producer of phosphoric acid inSouth Africa, operates a fertilizer complex atRichards Bay with a capacity of 780 000 t/a ofphosphoric acid (http://www.sulphuric-acid.com/sulphuric-acid-on-the-web/). Thewaste gypsum generated at this plant ispumped into the sea, representing a lostopportunity partially due to the lack of wastegypsum beneficiation or treatment. A total of55–70 Mt of waste gypsum is currentlystockpiled in South Africa at various sites, andindications are that the amounts of wastegypsum generated in South Africa are going

to increase substantially in the future as aresult of the treatment of acid minewater andof flue gases in coal-burning operations.Disposal of waste gypsum to landfill is not aviable option due to the shortage of landfillspace and the formation of hazardous andtoxic gaseous emissions in the form ofhydrogen sulphide (H2S), when gypsum islandfilled with biodegradable wastes.Moreover, legislative requirements for landfilldisposal methods, such as the NationalEnvironmental Management Waste Act(NEMWA) 59 of 2008, are projected to bemore stringent in future, resulting in the needto develop alternative waste managementapproaches. Previous studies have shown thepotential of thermal reduction of wastegypsum at 900 to 1100°C to produce calciumsulphide (CaS) using reducing agents,including solid carbon materials such as coalor activated carbon (Equation [1]) (Kato et al.,2012; Ma et al., 2011; Mihara et al., 2008;Nengovhela et al., 2007), carbon monoxidegas (Equation [2]) (Miao et al., 2012; Zhanget al., 2012; Tian and Guo, 2009; Li andZhuang, 1999), or hydrogen gas (Equation[3]) (Ning et al., 2011):

CaSO4(s) + 2C(s) CaS(s) + 2CO2 [1]

CaSO4(s) + 4CO CaS(s) + 4CO2 [2]

CaSO4(s) + 2H2 CaS(s) + 4H2O [3]

Wastewater containing toxic as well asvaluable metals is discharged as acid minedrainage (AMD) in major mining andindustrial operations. This has led to a sharpincrease in metal contamination of waterreserves and a potential risk of decant water

Making sense of our mining wastes:removal of heavy metals from AMDusing sulphidation media derived fromwaste gypsumby J. Mulopo*

This study investigates the recovery of water and selective removal ofvaluable metals from acid mine drainage (AMD) using sulphidation media(CaS) derived from waste gypsum. AMD systems containing Fe(II), Ni, Co,Zn, and Pb were investigated using CaS produced from the carbothermalreduction of Anglo Coal waste gypsum at 1025°C to precipitate metals asinsoluble metal sulphides. The results show a sulphidation dependence onthe pH, sulphide dosage, and metal concentration. The selective sulphi-dation of metals also showed significant dependence on the respectivemetal sulphide solubility order as a function of pH. According to theDepartment of Environmental Affairs’ South African Waste InformationCentre, over 42 million cubic metres of general waste is generated everyyear in South Africa and mining waste is by far the biggest contributor tothe solid waste (about 72%)). Although alarming, these vast quantities ofwaste also present an opportunity for integrated economic development,particularly in the recycling sector. The major argument has always beenthat the mining sector generates a large number of waste streams whichshow strong differences in time, in their treatment methodologies, or evenin their spatial distribution. This paper presents a case of a simple strategyfor integrated recycling of two mining waste streams and highlights theneed for the mining industry to break away from the traditional ‘linear’cul-de-sac disposal of wastes and think of new sustainable ways of wastemanagement.

acid mine drainage, waste gypsum, CaS, metals removal.

* University of the Witwatersrand, SustainableEnvironment and Energy Research Group, Schoolof Chemical and Metallurgical Engineering,Johannesburg, South Africa.

© The Southern African Institute of Mining andMetallurgy, 2015. ISSN 2225-6253. Paper receivedMay 2015 and revised paper received Oct. 2015.

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Making sense of our mining wastes: removal of heavy metals from AMD

from closed mines is looming in the Western, Central, andEastern basins of the Witwatersrand, South Africa. Becauseof their toxicity, any of these metals in excessive quantitieswill adversely interfere with many beneficial uses of thewater, such as human consumption and crop irrigation.

Current methods for the removal of heavy metals fromwastewater generally require the use of chemical reagents forprecipitation of these metals from solution. For instance, limecould be used to precipitate soluble metals in their insolublehydroxide forms in an alkaline environment (Barnes et al.,1986). Other methods used for removal of metals from AMDinclude coagulation-flocculation, electro-coagulation,cementation, membrane separation, membrane filtration,solvent extraction, ion exchange, adsorption, and bio-sorption (Meunier et al., 2006; Kurniawan et al., 2006).Among these methods, chemical precipitation with NaOH orCa(OH)2 followed by filtration is by far the most widely usedprocess to remove metals from wastewater. However, themajor setback with hydroxide precipitation lies in thedifficulty of efficiently dewatering the sludge, which leads togeneration of enormous volumes of hydroxide sludge.

Other treatment methods such as sulphidation haveattracted several researchers (Tokuda et al., 2008; Lewis etal., 2006; Maruyama et al., 1975; Kim, 1980; Bhattacharyyaet al., 1979, 1981). The use of sulphidation media derivedfrom waste gypsum as sulphide sources for metal precipi-tation has been reported by Mihara et al. (2008) and Soya etal. (2008) as a recycling process for gypsum boards in Japan.This study considers the use of CaS produced bycarbothermal reduction of waste gypsum for the treatment ofAMD in an attempt to integrate the treatment of two wastestreams that poses major challenges to the South Africanmining industry.

Waste gypsum from Anglo Coal (Landau Colliery) (Figure 1)was collected. XRD analysis showed that the samplecontained 33.65% CaO, 51.38% SO3, 5.02% MgO, 0.02%Na2O, 0.15% P2O5, 0.03% Fe2O3, 0.01% Al2O3, and 0.01%SiO2. The waste sludge was sized to less than 250 μm. X-ray

fluorescence (XRF) analysis was also used to identify theelemental composition in waste gypsum samples. Table Ishows the trace metal contents in weight (%) or ppm.Industrial coke from George (South Africa) was used forthermal treatment with composition 60.1% fixed carbon,2.8% moisture, 10.5% ash content, and 26.7% volatilematters. Acid minewater was collected from Shaft 8, or Winze18, Harmony Gold Mine (Table II) and the Navigation CoalMines (Table III). The sulphide precipitation agent (CaS) wasobtained by the reductive decomposition of the wastegypsum.

A tubular furnace consisting of a 750 mm long, 24 mmdiameter mullite tube mounted horizontally and equipped witha temperature controller was used for the thermal reduction ofwaste gypsum to calcium sulphide. All precipitationexperiments were carried out in 1 litre batch plastic beakersequipped with overhead stirrers fitted with radial turbineimpellers. A Metrohm 691 pH meter was used to monitor andmeasure pH. A Perkin Elmer Analyst 700 atomic absorptionspectrometer was used to determine Pb, Zn, Ni, and Co.

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Cr % Mn % Fe % Co ppm Ni ppm Cu ppm Zn ppm Ga ppm Ge ppm As ppm

0.027 0.007 0.029 24.1 11.1 8.200 16.4 7.3 <0.9 0.4

2.400 1.6 661.60 <0.7 <4.8 <0.5 <0.5 <0.8 1.7 <1.0

4.8 8.80 12.70 <13.0 5.50 <4.10 41.4 1.40 4.90 <0.9

0.089 <0.420 0.341 0.127 0.031 16.110 <0.01 21.11 <0.003 0.003

pH 3.1Sulphate 4510Chloride 37Free acid 500Sodium 96Potassium 3Magnesium 113Calcium 559Pb 16Manganese 174Iron(II) 1196Aluminium 6Zinc 49Nickel 43Cobalt 85

The two AMD samples were submitted for Pb, Zn, Ni, and Coanalysis by atomic absorption spectrometry (AAS) inaccordance with the Standard Methods for the Examinationof Water and Wastewater (APHA, 1992). Fe(II) in the AMDwas determined in-house by iodometry. The amount of CaSrequired to remove the metals from the AMD was calculatedfrom the total metal analyses using a sulphide/total metalratio of 1.0.

CaS was produced by carbothermal reduction of wastegypsum in a muffle furnace at a temperature of 1025–1030°Cfor 45 minutes using a C/CaSO4 molar ratio of 2. The CaSyield was about 78%, as shown in Table IV. The effect ofsulphide addition to the AMD system was investigated usingsulphide/total metal mole ratios of 0, 0.5, 0.75, 1.0, 1.5, 2.0,and 2.5. Appropriate amounts of CaS were added to the AMD

to give a total of 1 L mixture and batch equilibrium removalexperiments were run at appropriate pH values using a pHcascading approach. The metal removal batch experimentswere carried out for at least 5 minutes at a particular pH oruntil a steady pH was attained. At each pH used a 50 mlsample was collected, filtered using Whatman 12.5 cmqualitative filter papers, acidified with 2.5 ml concentratedHCl, and left overnight to drive out any residual sulphide andpreserve the metals. A portion of the sample was used forFe(II) determination while the rest of the sample was used forthe determination of Pb, Zn, Ni, and Co by AAS. The residuewas submitted for XRD analysis using a PANalytical X’PertPro powder diffractometer with X’Celerator detector andvariable divergence and fixed receiving slits with Fe-filteredCo-Kα radiation on a back-loading preparation method. Thephases were identified using X’Pert Highscore Plus software.

The extent of metal sulphide precipitation in multi-metalsystems such as AMD is expected to be a function of pH,reaction time, initial metal concentration, sulphide dosage,and the presence of chelating agents and other interferingions. With some metals such as nickel and cobalt, the precipi-tation is also dependent on the reactor system (closed oropen). The effect of pH on solubility can be used to separatemetal ions by sulphide precipitation. Many metal sulphidesare insoluble in water but dissolve in acidic solution.Qualitative analysis uses this change in solubility of themetal sulphides with pH to separate a mixture of metal ions.Hydrogen sulphide is a stronger acid than water, ionizing inwater as a diprotic acid according to Equations [4] and [5]:

H2S(aq) + H2O(l) H3O+(aq) + HS-(aq);Ka1 = 8.9 × 10-8 [4]

HS-(aq) + H2O (l) H3O+(aq) + S2-(aq);Ka2 = 1.2 × 10-13 [5]

The ionization forms bisulphide ion, HS-, and sulphideion, S2-, which can combine with the metal ions to precipitatethe metal sulphides. However, the S2– ion is a strong base(Kb approx. 105) and will react immediately to form HS– anda hydroxide ion. The true concentration of S2– in solutiontherefore is negligible.

By adjusting the pH in an aqueous solution, one canadjust the sulphide ion concentration in order to precipitatethe least soluble metal sulphide while maintaining the othermetal ions in solution. For instance, the solubility productconstant of lead (II) sulphide is much smaller than that ofzinc sulphide, therefore lead sulphide will be expected toprecipitate before zinc sulphide.

In order to investigate the interactions between differentmetal ions and observe the possible differences in individualmetal sulphide precipitation in typical AMD wastewatercontaining Pb, Zn, Ni, Co, and Fe(II),


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pH 3.00 Acidity mg/L CaCO3 700Alkalinity mg/L CaCO3 0Sulphate mg/L 3200Aluminium mg/L 43Calcium mg/L 447Fe (II) mg/L 840Co mg/L 75Ni mg/L 93Pb mg/L 0.09Zinc mg/L 75

0 78 6 4 5 5 2


The pH values required for selective sulphidation of Pb, Zn,Ni, Co, and Fe (II) in typical AMD wastewater weredetermined based on the results reported by previous workers(Soya et al., 2008). The basis of metal sulphide solubility asa function of pH was also taken into consideration. In thisregard, the pH range 3.0–10.0 was targeted for selectivesulphidation of Pb, Zn, Ni, Co, and Fe(II) in AMD wastewater.The selective sulphidation of the various metals was carriedout using a pH cascade approach. Figures 2 and 3 show thechange in Zn, Ni, Co, and Fe (II) concentrations in the filtrate.For reasons of clarity, the results for Pb are not plotted. It canbe seen that the Zn concentration was reduced to a valuebelow 1.0 mg/L for all AMD wastewaters studied at a molarratio of sulphide to Zn of about 1.0. As the pH increased,selective removal of Ni was achieved at an average pH rangeof 5.0–7.0. From Figures 2 and 3, it can be seen that Ni is90% removed at pH 5.0 from Harmony AMD and at pH 7.0from Navigation AMD. To achieve the same removalefficiency, both the Harmony would require a pH value of

6.0. The next metal to be removed from AMD was Co. Figures2 and 3 show that Co is more than 80% removed at pHvalues above 7.0 for from Navigation AMD, while for theHarmony AMD the same removal is achieved at a lower pH ofslightly greater than 4.0. Figures 2 and 3 show thatsignificant Fe(II) removal occurs only at pH values higherthat around 6.0 .

To achieve 90% Fe(II) removal, the pH of the AMDwastewater had to be increased to an average of 8.0. Fe(II) isremoved to less than 50 mg/L at pH 9.0 from both types ofAMD wastewater used in this study. At this pH, more than99% of the Zn, Ni, and Co have already been completelyremoved.

Despite using an open reactor system, which is prone toatmospheric oxidation, no evidence for nickel sulphide andcobalt sulphide dissolution was observed. This could be dueto the short retention times for the metal sulphide residue inthe AMD wastewater.

The selective removal data trends for the two AMDwastewaters studied indicate the critical role of metalsulphide solubility and pH on the removal efficiency. Thesolubilities of the metal sulphides under consideration are inthe order PbS < ZnS < NiS < CoS < FeS. In this regard, theleast soluble metal sulphides (PbS and ZnS) are precipitatedfirst while the most soluble metal sulphide (FeS) is precip-itated last in a pH cascade experiment. NiS and CoS, withcomparable solubilities, are removed within a narrow pHrange. From these results, it was also inferred that under lowpH conditions (pH < 4.0), H2S(aq) was the predominantspecies (García-Calzada et al., 2000; Peters et al., 1985), andpart of the H2S is released from the solution as H2S gas dueto the poor precipitation of the metal sulphides in an acidicsolution. Moreover, from molecular orbital theory, the highestoccupied molecular orbital (HOMO) for HS– has beencalculated to be –2.37 eV, which compares well with theexperimental value of –2.31 eV (Drzaic et al. 1984; Radzigand Smirnov 1985). The HOMO for HS– is less stable thanthat for H2S (–10.47 eV), indicating that HS– is morenucleophilic and basic than H2S, which is consistent with theobserved reactivity for metal sulphide precipitation observedin this study. Thus, H2S is not a strong electron donorbecause the HOMO is so stable.

Figure 4 shows the changes in the Pb, Zn, Ni, Co, and Fe(II)concentrations in filtrates obtained from Harmony AMDwastewater at different sulphide to total metal molar ratiosover a period of 90 minutes. The order of metal removalfollows the order of solubility of the respective metalsulphides, with the least soluble metal sulphide precipitatedfirst. In the case of Pb, Zn, Ni, and Co, it can be seen that themetal concentrations in the filtrate were reduced to below 5%using a sulphide to total metal ratio of 1.0. In contrast, at thissame sulphide to total metal molar ratio, less than 80% ofFe(II) is removed. At a sulphide to total metal ratio of 1.5, Pb,Zn, Ni, and Co in the filtrate were reduced to a value below1.0 mg/L, representing more than 99% metal removal. Lessthan 40% of the Fe(II) was removed using this sulphide tototal metal molar ratio. Thus the addition of the CaS agent ata sulphide to total metal ratio of 2.0 was necessary to achievemore than 70% Fe(II) removal in the filtrate.

The poor Fe(II) removal at sulphide to total metal ratios of1–1.5 can be explained in two ways. Firstly, Fe(II) forms theleast soluble metal sulphide compared to all the other metals,

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Pb, Zn, Ni, and Co. In this regard, FeS is not expected toprecipitate at pH values lower than 5.5, as shown by the pHprofile for the sulphide to total metal ratios of 1.0–1.5.Secondly, rapid precipitation of both PbS and ZnS on the CaSparticles could have brought about encapsulation ofunreacted CaS inside the PbS and ZnS particles. As aconsequence, a higher molar ratio of CaS to total metal wasneeded to achieve more than 70% removal of Fe(II) in thefiltrate. Similar CaS encapsulation by CuS precipitation at lowpH has been reported by Soya et al. (2008).

The sulphidation behaviour of Fe (II) using CaS derived fromwaste gypsum as a sulphidation agent was investigated,together with the possibility of selective precipitation of Pb,Zn, Ni, Co, and Fe(II) from various AMD solutions. It wasfound that Pb, Zn, Ni, and Co can be removed as metalsulphides at lower pH values while Fe(II) stays in solution –enabling the ferrous iron to be separated from the othermetals, which is a great advantage for metal recovery.Selective metal removal and recovery as metal sulphides maybe achieved conveniently using CaS as the sulphidationmedium. However the purity of CaS obtained by the thermalreduction of waste gypsum and mass transfer limitationsassociated with the AMD-CaS system may be critical forprocess development. Moreover, the settling characteristics ofthe precipitates are poor, but this could probably be improvedby the use of an anionic polymer at low pH.

APHA. 1992. Standard Methods for the Examination of Water and WasteWater. 19th ed. American Public Health Association, Washington DC.

BARNES, D., BLISS P.J., GOULD B.W., and VALLENTINE, H.R. 1986. Water andWastewater Engineering Sytems. Longman Scientific and Technical, UK.

BHATTACHARYYA, D., JUMAWAN, A.B. Jr., and GRIEVES, R.B. 1979. Separation oftoxic heavy metals by sulphide precipitation. Separation Science andTechnology, vol. 14. pp. 441–452.

BHATTACHARYYA, D., JUMAWAN, A.B. JR., SUN, G., SUND-HAGELBERG, C., andSCHWITZGEBEL, K. 1981. Precipitation of heavy metals with sodiumsulphide: bench-scale and full-scale experimental results. ACSIChESymposium Series 77, no. 209. pp. 31–38.

DRZAIC P.S., MARKS J., and BRAUMAN J.I. 1984. Electron photo-detachment fromgas phase molecular anions. Gas Phase Ion Chemistry, vol. 3.pp. 167–211.

GARCÍA-CALZADA, M., MARBÁN, G., and FUERTES, A.B. 2000. Decomposition ofCaS particles at ambient conditions. Chemical Engineering Science, vol. 55.pp.1661–1674.

KATO, T., MURAKAMI, K., and SUGAWARA, K. 2012. Carbon reduction of gypsumproduced from flue gas desulphurization. Chemical EngineeringTransactions, vol. 29, no. 11. pp. 805–810.

KIM, B.M. 1980. Treatment of metal-containing wastewater with calciumsulphide. AIChE Symposium Series 77. pp. 39–48.

KURNIAWAN, T.A., CHAN, G.Y.S., LO, W.H., and BABEL, S. 2006. Physiochemicaltreatment techniques for wastewater laden with heavy metals. ChemicalEngineering Journal, vol. 118. pp. 83–98.

LEWIS, A. and VAN HILLE, R. 2006. An exploration into the sulphide precipitationmethod and its effect on metal sulphide removal. Hydrometallurgy, vol.81. pp. 197–204.

LI, H.J. and ZHUANG, Y.H. 1999. Catalytic reduction of calcium sulphate tocalcium sulphide by carbon monoxide. Industrial and EngineeringChemistry Research, vol. 38, no 1. pp. 3333–3337.

MA, L., NIU, X., HOU, J., ZHENG, S., and XU, W. 2011. Reaction mechanism andinfluence factors analysis for calcium sulphide generation in the process ofphospho-gypsum decomposition. Thermochimica Acta, vol. 526, no 1–2.pp. 163–168.

MARUYAMA, T., HANNAH, S.A., and COHEN, J.M. 1975. Metal removal by physicaland chemical treatment processes. Journal of the Water Pollution ControlFederation, vol. 47. pp. 962–975.

Meunier, N., Drogui, P., Montan’e, C., Hausler, R., Mercier, G., and Blais, J.F.2006. Comparison between electro-coagulation and chemicals precipi-tation for metals removal from acidic soil leachate. Journal of HazardousMaterials, vol. 137, no 1. pp. 581-590.

MIAO, Z., YANG, H., WU, Y., ZHANG, H., and ZHANG, X. 2012. Experimentalstudies on decomposing properties of desulphurization gypsum in athermogravimetric analyzer and multiatmosphere fluidized beds.Industrial and Engineering Chemistry Research, vol. 51, no 15. pp. 5419–5423.

MIHARA, N., SOYA, K., KUCHAR, D., FUKUTA, T., and MATSUDA, H. 2008. Utilizationof calcium sulphide derived from waste gypsum board for metal-containing wastewater treatment. Global NEST Journal, vol 10, no 1. pp. 101–107.

NENGOVHELA, N.R., STRYDOM, C.A., MAREE, J.P., OOSTHUIZEN, S., and THERON, D.J.2007. Recovery of sulphur and calcium carbonate from waste gypsum.Water SA, vol. 33, no 5. pp. 741–747.

NING, P., ZHENG, S.C., MA, L.P., DU, Y.L., ZHANG, W., NIU, X.K., and WANG, F.Y.2011. Kinetics and thermodynamics studies on the decompositions ofphospho-gypsum in different atmospheres. Advanced Materials Research,vol. 162, no. 1. pp. 842–848.

PETERS R.W. and KU Y. 1985. Batch precipitation studies for heavy metalremoval by sulfide precipitation. AIChE Symposium Series, vol. 81. pp. 9–26.

RADZIC A.A. and SMIRNOV B.M. 1985. Reference Data on Atoms, Molecules, andIons. Vol. 31. Springer-Verlag.

SOYA K., MIHARA N., KUCHAR D., KUBOTA M., MATSUDA H., and FUKUTA T. 2008.Selective sulfidation of copper, zinc and nickel in plating wastewater usingcalcium sulfide. Engineering and Technology, vol. 44. pp. 356–360.

TIAN, H. and GUO, Q. 2009. Investigation into the behaviour of reductivedecomposition of calcium sulphate by carbon monoxide in chemical-looping combustion. Industrial and Engineering Chemistry Research, vol.48, no 12. pp. 5624–5632.

TOKUDA, H., KUCHAR, D., MIHARA, N., KUBOTA, M., MATSUDA, H., and FUKUTA, T.02008. Study on reaction kinetics and selective precipitation of Cu, Zn, Niand Sn with H2S in a single-metal and multi-metal systems. Chemosphere,vol. 73, no 9. pp.1448–1452

ZHANG, X., SONG, X., SUN, Z., LI, P., and YU, J. 2012. Density functional theorystudy on the mechanism of calcium sulphate reductive decomposition bycarbon monoxide. Industrial and Engineering Chemistry Research, vol. 51,no 18. pp. 6563–6570. ◆


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Where the levels of attrition among universityor college entrants are high, some form of‘study skills’ module in the first-yearprogramme is frequently employed to improvethe academic prospects of students. Behindthis strategy is the belief that a significantfactor contributing to attrition and academicunderperformance is that the learning practicesand study skills of many entrants are in someways inappropriate for effective learning at atertiary level. However, the effectiveness ofsuch learning skills interventions hasgenerally been disappointing. For example,Hattie, Biggs, and Purdie (1996), in a meta-analysis of 51 studies on the effectiveness oflearning skills interventions, concluded thatthe interventions did appear to improvestudents’ attitudes to learning and alsoreduced their levels of anxiety, but hadminimal effect on improving their study skills.This apparent ‘resistance to change’ has been

noted by several researchers, even in literature(discussed shortly) that reports some degree ofsuccess of study skills interventions.

This paper reports the findings of a studythat investigated the dynamics associated withstudents changing their learning practicesduring their first year at university. Thestudents were entrants to an engineeringprogramme at a South African university in2008. After a consideration of the literature onthe apparent ‘resistance’ associated withchanging learning practices, the study isdescribed and the findings are presented anddiscussed.

Several reasons have been offered for therelative lack of effectiveness of interventionsdesigned to improve the learning practices andstudy skills of entrants to tertiary education.Wingate (2006) argues that stand-alone studyskills modules are ineffective because ‘learninghow to study effectively at university cannotbe separated from subject content and theprocess of learning’ (p. 457). Others argue thatlearning practices and study skills are difficultto change because they are inherently stableand that students’ prior experiences at schoolhave developed in them ‘habitual patterns ofstudy’ (Entwistle, 1998) or have ‘automatedtheir study habits’ (Dembo and Seli, 2004).This kind of stability appears to persist inmany students even when considerable effortis made to deploy ‘powerful learningenvironments’ intended, among other things,

Enhancing study practices: are first-year students ‘resistant to change’?by L. Woollacott*, S. Booth†, and A. Cameron‡

One of the strategies for trying to reduce attrition among first-yearstudents and for improving their academic performance generally is toinclude some kind of study skills module in the first-year programme. Oneof the reasons often given for the relative lack of success of suchprogrammes is the claim that students are ‘resistant to change’. This paperpresents a study that investigated this claim by interviewing chemical andmetallurgical engineering students in a South African university at thebeginning and end of their first year. The basis for evaluating the extent towhich students’ practices appeared to change was a set of six categories ofpractice identified in a related phenomenographic study on the learningpractices of the same students. It was evident from the interview data thateven where some change in practice had occurred, the extent of changewas somewhat disappointing. For those who reported changing theirpractice, the primary change driver appeared to be underperformance inthe mid-year exam. Underperformance prior to that seemed to exert lessforce and students did not appear to give very serious attention to class ortextual input/activities on study practices. ‘Resistance to change’ appearedto be implicit in nature and to be more a consequence of overconfidenceand the ‘momentum’ resulting from habit rather than an explicitattitudinal resistance.

engineering education, first-year education, resistance to change, studypractices, study skills, student retention.

* School of Chemical and Metallurgical Engineering,University of the Witwatersrand, Johannesburg,South Africa.

† Department of Pedagogical, Curriculum andProfessional Studies, University of Gothenburg,Sweden.

‡ Science Teaching and Learning Centre, Universityof the Witwatersrand, Johannesburg, South Africa.

© The Southern African Institute of Mining andMetallurgy, 2015. ISSN 2225-6253. Paper receivedMay 2015.

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Enhancing study practices: are first-year students ‘resistant to change’?

to improve the learning practices of those students (Brownleeet al., 2001; Vermetten et al., 2002). A number of studies onSouth African engineering students have also commented onthis apparent stability and cited it as a possible reason for therelative lack of change noted in some students’ learningpractices (Case and Gunstone, 2002; Cliff, 1996, 1995, 2000;Meyer, 1991; Meyer et al., 1994, 1992; Simelane, 2007).

Another reason given for the relative lack of effectivenessof interventions intended to improve students’ learningpractices and study skills is that students are ‘resistant tochange’. In this regard, Dembo and Seli (2004) found thatsome students failed to benefit from study skills modulesbecause they didn’t believe they could change, didn’t want tochange, didn’t know what to change, or didn’t know how tochange. They also noted that some students failed to benefitmuch from learning skills interventions because they didn’tseek help and they didn’t attend regularly. Whether this wasthe result of the other reasons they quoted they did not say.Yuksel (2006) proposed two additional explanations forstudents’ resistance to study skills interventions: studentsdidn’t believe that the skills being taught had any value or,alternatively, did not consider those skills to be useful withrespect to their future careers.

In contrast to the conscious ‘resistance’ to study skillsinterventions evident in the above examples, resistance mayalso be more unconscious in nature. As pointed out earlier, itis inherently difficulty to change well-established, stablelearning practices or study skills. Accordingly, it could beargued that learning practices and study skills are inherently‘resistant to change’ because of the difficulty associated withchanging them. This is strongly supported by recent findingsfrom cognitive and neuroscience research. For example, Clark(2008, 2010) indicates that a high proportion (up to 70%) ofadult knowledge is unconscious and automated in nature,and in addition, that dysfunctional, automated, unconsciousknowledge can be difficult to unlearn. Furthermore, suchdysfunctional knowledge can interfere with a student’sattempts to change that knowledge and to develop new andmore appropriate knowledge along with the associatedbehaviours. On this basis, inappropriate or dysfunctionallearning practices and study skills are inherently ‘resistant tochange’ even if students are consciously open and committedto changing them.

From this brief review, it appears that changing learningpractices and improving study skills that have beendeveloped over many years of secondary schooling isinherently difficult and requires considerable time andcommitment both on the part of students and teachers if theeffort is to be successful.

A study was initiated in 2008 to investigate the learningpractices of first-year engineering students at a South Africanuniversity and how these practices changed during their firstyear at university. In the study, learning practices were takento be orientations or predispositions to study and learn andto act in learning situations in certain ways and with certainintentions that people have developed as a result of their pastexperience. The motivation for the study was the high rate ofattrition of students entering the school and the possibility

that problematic aspects of their learning practices andresistance to changing these aspects were significantcontributing factors. The premise behind the study was thatlearning practices affect student attrition by the way theyinfluence the quality of student learning and, consequently,the academic prospects of students; i.e. that problematicfeatures of students’ learning practices contribute to pooracademic performance and therefore to attrition by academicfailure. The study and its findings are reported in detail byWoollacott (2013).

This paper reports the results of an investigation into theextent to which the students’ learning practices changedduring their first year at university and the dynamicsassociated with such change. The investigation was guidedby the following questions. What proportion of studentschanged their practice? To what extent did they change? Ifchange occurred, when did it happen in the year and whatprompted the change? Did the level of practice of a student onentry have a bearing on the extent and nature of change?What sort of change processes operated during the year? Ifno change occurred, why was that?

The methodology employed to address these questionswas to interview a sample of students from the 2008 cohortat the beginning and end of their first year at university.Accordingly, how students changed their learning practiceswas investigated only from the perspective of the studentsand the findings were based only on what students reportedin interviews on the subject. All interviews were semi-structured in nature and were based on protocols that werediscussed with research colleagues after trial interviews withstudents.

In order to obtain a qualitatively representative sample ofstudent experience, ‘maximum variation sampling’ (Green,2005) was used when selecting students for the study.Twenty-seven students out of the entering cohort of 156were selected and were interviewed at the beginning of theacademic year and again towards the end of the year. Ofthese, nine were female.

The interviews at the beginning of the year focusedprimarily on the nature of the students’ learning practices onentry to university and on establishing, through a phenom-enographic analysis (Akerlind, 2005; Green, 2005; Martonand Booth, 1997), the qualitative variation in the practicesfound among the students. The categories of variationestablished from this analysis, which is reported in detail byWoollacott (2013), provided an analytical framework for theanalysis of the changes in learning practices reported by thestudents in their second interviews at the end of the year.The categories of variation used in the analysis are describednext, after which the findings of the study are reported anddiscussed.

The interview data was particularly rich with regard to onetype of learning practice, which was termed ‘theory-focusedstudy practice’. Accordingly, this paper focuses only on thatpractice. Theory-focused study practice is the type of practicewhere a student, studying on their own, is focused only onunderstanding and mastering the ‘theory’ of the subject theyare studying and concerns about tests and examinations are

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absent or are at the back of their minds – i.e. the focus is tolearn in order to understand as opposed to learning in orderto pass impending tests/exams. Here ‘theory’ is referring to‘bookwork’ and is taken to mean the conceptual andtheoretical knowledge and information presented in coursematerial. This is in contrast to a focus on developing theproblem-solving skills associated with that theory. Here,‘problem’ is used in a technical sense as commonly used bythe students and in mathematics, science, and engineeringcourses – i.e. as a question or difficulty that cannot beresolved without some kind of numerical or mathematicalmanipulation.

Among the students, six qualitatively different categoriesof theory-focused study practice were identified by thephenomenographic analysis of the transcripts from the firstset of interviews. These are summarized in Table I anddiscussed thereafter.

The most elementary category of theory-focused studypractice is information-oriented practice. Here the focus is onassimilating or memorizing information with no particularregard for making sense of it. In the next category – compre-hension-oriented study practice – the focus is on compre-hending the material being studied by simply reading therelevant texts. This does not include any activity other thanreading those texts. In consolidation-oriented study practice,the next category, the focus is on reinforcing and consoli-dating what has been comprehended by using one or moreconsolidation technique such as making summaries,vocalizing what has been learned, or memorizing concepts orprinciples. A sub-category of consolidation-oriented practice –integration-oriented study practice – involves consolidatingand reinforcing comprehended theory further by integratingthe learning of theory and the development of problem-solving skills; i.e. problems are attempted explicitly as ameans of applying the theory being learned in order todeepen one’s grasp of that theory.

In the four categories of study practice discussed so far,learning is conducted within the framework and structures ofthe theory as presented to the students. In the next categoryof study practice – refinement-oriented practice – the focus ison deepening personal mastery of that theory by explicitly

looking for new conceptual connections and linkages and,consequently, restructuring one’s understanding of thattheory. Techniques used to do this include developingconcept maps, elaborating study notes, asking oneselfquestions about aspects of the theory, or trying to thinkabout the theory from different perspectives. The sixthcategory – know-how-oriented practice – takes thisrefinement process a step further by explicitly trying to relatetheory to real-world situations.

The five categories of study practice form a progressionwith one category including, but going beyond, theorientations of the previous category in the progression.Comprehension-oriented practice works with learnedinformation to develop comprehended theory. Consolidation-oriented practice works with comprehended theory to developconsolidated theory. Refinement-oriented practice works withconsolidated theory to develop a refined grasp of disciplinaryknowledge, and know-how-oriented practice works withrefined disciplinary knowledge to develop practical know-how. As such the progression constitutes an increase in thesophistication of the study practice and involves an increasein the sense made of information and theory, and in thedegree of consolidation, integration, and refinement ofunderstanding and the relatedness of that theory to the realworld.

In the study, it was found that while an individualstudent may be oriented to exercise several of the categoriesof practice under different circumstances, the range ofpractices they might exercise is constrained by their priorexperience. Specifically and logically, students cannot beoriented to exercise categories of study practices with whichthey have had no prior experience. This observation providesa simple basis for characterizing the theory-focused studypractice of individual students, namely by indicating the mostsophisticated level of practice with which they have had priorexperience. This observation was used as a basis for charac-terizing the students’ learning practice and evaluating theextent to which these changed during their first year atuniversity. So for example, a student could be characterizedas having a theory-focused study practice at a consolidationlevel if their prior experience included a consolidation-


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1 Information-oriented practices Oriented to learning facts, formulae, or information by assimilating, memorizing, or cramming that information with no particular regard for its meaning or relevance.

2 Comprehension-oriented practices Oriented to making sense of course material by reading through it, going through it, or working through it in order to develop personally comprehended theory with no particular regard for consolidating or restructuring the material as it is presented in the course.

3a Consolidation-oriented practices Oriented to consolidating or reinforcing personally comprehended theory by using consolidation tools such as vocalizing, memorizing, or summarizing in order to develop personally consolidated theory with no particular regard for refining it beyond the content or structure presented in the course.

3b Integration-oriented practices Oriented to further consolidating and reinforcing personally comprehended theory by integrating the learning of theory and the development of problem-solving skills so that appropriate problems are selected and worked on for the express purpose of consolidating one’s grasp of the theory.

4 Refinement-oriented practices Oriented to deepening personal mastery of consolidated theory by using refinement tools such as restructuring,self-questioning, elaborating, concept maps, or visualizing in order to develop a personally refined grasp of disciplinary knowledge with no particular regard for how it relates to real-world situations.

5 Know-how-oriented practices Oriented to deepening personal mastery of disciplinary knowledge by relating it to real-world situations in order to, implicitly or explicitly, develop practical know-how.


oriented practice and did not include more sophisticatedpractices such as integration-, refinement- and know-how-oriented practices.

The extent of change of each student’s theory-focused studypractice during their first year at university was gauged bythe degree to which their practice appeared to have shiftedfrom one category of practice to another. Four types ofchange were evident and were labelled ‘no change’, ‘minorchange’, ‘adapted’, and ‘shifted’. ‘No change’ speaks foritself. Changes labeled as being ‘minor’ were ones in whichthe small degree of change reported by a student wasconsidered to have involved only their adjustment to theteaching and learning environment and not a discerniblechange in the study practice itself. Changes labelled as‘shifted’ were those where a student’s practice had ‘shifted’from one category of practice to another. Change labelled as‘adapted’ is an in-between category where some change wasclearly discernible but did not involve a shift from onecategory to another; it consisted of discernible change withinone category of practice. For example, several students with aconsolidation level of practice on entry did not shift toanother category but reported that, at the end of the year,they paid more attention to developing understanding thanthey had done at the beginning of the year.

For convenience the five levels of theory-focused studypractice were coded SP1 to SP5 (Study Practice level 1 to 5),which correspond respectively to information-, compre-hension-, consolidation/integration-, refinement-, and know-how-oriented practice respectively. The study practice ofseveral students appeared to lie somewhere between thesecategories, either because the data was unclear or becausesome students reported having had some experience at alevel of practice more sophisticated than the one at whichthey tended to operate. In such cases, the researcher’sdiscretion was exercised to represent the actual level ofpractice as appropriately as possible – either at the less or

more sophisticated level or as somewhere between. Of the 27 students, 10 (37% of them) shifted their

practice, three students (11% of them) adapted their practicebut did not change category, two students (7%) appeared tochange in only minor ways, while 12 students (44% of them)did not appear to change their study practices at all.Interestingly, one student adapted his practice by trying outsome of the strategies recommended in class. However, afterfinding they ‘didn’t work for him’, he intentionally revertedback to the practice he had used at school.

Figure 1 breaks the results down further to explore theextent to which students who entered university with aparticular category of practice changed that practice. Thebreakdown is presented both in the form of a bar chart andas an accompanying table – the information in both is thesame.

The figure indicates the following. Ten students entereduniversity with relatively unsophisticated study practices – upto and including comprehension-oriented practice (SP2 andSP1/SP2 categories) – and had much scope for improving thequality of their practice (they could progress to levels SP3,SP4, or SP5); it was important for them to do so if they wereto improve their academic prospects at university. Of these10, the majority (7 of the 10) shifted their practice, oneadapted, but two did not appear to change their practice at all.However, in all but one case, the extent of change involvedonly a shift to the next most sophisticated level of practice.

At the other end of the spectrum, nine of the studentsentered university with relatively sophisticated studypractices – up to the level of refinement-oriented practice andalso those with some know-how oriented dispositions (SP4,SP3/SP4, and SP4/SP5 categories) and did not have as muchscope for improving their practice (they could only progressto SP5). The majority of these (8 of the 9) did not changetheir practices or made only minor changes and only oneadapted their practice.

Between these two groups of students were those whoentered university with an intermediate level of study practice– practice up to the level of consolidation-oriented practice(SP3 and SP2/SP3 categories). Here, the scope to improvetheir study practice was still substantial – they could progressto SP4 and SP5. Of the eight students with this profile, only

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three shifted, one adapted (and then reverted to his oldpractice), and four did not appear to change or only mademinor changes to their practice.

With regard to the dynamics behind students changing theirlearning practices, data from only 15 students was available;the other 12 students appeared not to have changed theirpractice at all. Of the 15 where some degree of change wasevident, two had changed little, three had ‘adapted’ theirpractice, and 10 students had ‘shifted’ their practice. Thefindings from the study are as follows.

➤ The extent of change appeared to be limited to crossingfrom one practice category or subcategory to the nextmost sophisticated. This was the case with five of the10 students who shifted their practice. The studypractices on entry of four of the 10 students werebetween two adjacent categories and the changeappeared to involve moving more fully into the moresophisticated practice

➤ Most students who realized they needed to be seriousabout changing their study practice seemed to takeabout half the academic year to reach this conclusion. Ofthe 15 students who indicated they had changed theirstudy practice in some way – minor change, adapted, orshifted – only five started to do so in the first semester.Of these, two were making only minor changes to theirpractice, and two were responding to class input

➤ Few students shifted their study practice as a result ofclass or textual input on the subject. Of the 13 studentswho shifted or adapted their practice, only three did soas a result of formal input in class and one as a resultof receiving a faculty newsletter on study skills

➤ The primary driver of change in study practiceappeared to be the stress created by getting poorgrades and the students’ recognition that their currentstudy practices weren’t ‘working for them’ in the senseof not facilitating the achievement of satisfactorygrades. Even in the case of the four students whoresponded to formal input on study practice, two ofthem appeared to be responsive because their currentpractice was not ‘working for them’. Of the 13 studentswho adapted or shifted their practice, only three werenot pushed by marks pressure to change their studypractice. Two of these took their lecturer on trust andstarted using recommended study strategies. The othermade the change through a ‘eureka experience’ ofdiscovering the efficacy of using summaries effectivelywhen preparing for a mid-year supplementarymathematics examination

➤ Poor performance in the first semester appeared to befar less of a change driver than poor mid-year marks.Of the nine students who were pushed towards changeby pressure directly or indirectly because their practices‘were not working for them’, only two did so on thebasis of poor performance in first semester tests andassignments. For the other seven it appeared to takepoor performance in what they perceived to be their‘major’ assessments – namely, the mid-yearexaminations – before poor grades had the impact ofpushing them towards change.

The following extract gives other reasons why poorperformance in the first semester did not seem to have theimpact of poor performance at mid-year. The student inquestion felt she could still catch up; she was still adjustingto ‘varsity; and she didn’t realize that it was her studypractice that needed to change. (In the extract, statements bythe interviewer are italicized to distinguish them fromstatements by the students.)

‘OK, I changed when I come back now, the 2ndsemester, ‘cuz I’ve seen already … the way I am studyingit was not working. … There was something serious thatneeds to be done or else I am just going to end upregretting. Ja. You didn’t realize that after the first set oftests after the 1st quarter? Not really. Why was that? Ithink it’s because I used to tell myself that I’m going tocatch up ... [But] I’ve been trying to catch up and still it’snot working. So now it’s like, OK. You did have results atthe beginning of 2nd quarter. Ja, I did but I just thought… I’m just adjusting to varsity life, all those things[laughs] and then I can see that no, it’s actually the waythat I am studying, it’s not really that effective. So it tookuntil mid-year. What made you realize that it wasn’tworking? ‘Cuz I was still not progressing. By progressing,what were you looking at? I’m looking at passing as awhole, you find that some of the things I am passing, butnot … really that much even though some I was failinglike really failing, but now, since I have started practicingthese things [the new practices], that’s why I have somuch hope and so, so much confidence in myself ‘cuzI’ve seen that it’s working [in] the second [semester]. Iam actually passing and I thought I was never going topass like that.

The limitations of the study findings are fairly obvious. Thefindings derive only from the student’s perspective and fromstudent reports, and more objective data was not included inthe analysis. In addition, the number of students in the studywas quite small (27) and only 10 to 13 of these appeared tohave changed their learning practice to any discernible degreeduring their first year at university. Accordingly, the findingsare not generalizable and provide only indications. However,the indications are very interesting.

In the first place they are in accord with the literaturediscussed earlier. The stability of the study practices is clearlyevident in that many students tended to continue with thepractices they were used to until they came to the realizationthat these practices were ‘not working for them’ and somekind of change was necessary if they were to succeedacademically. In the study there was no evidence of studentsbeing consciously ‘resistant’ to change in the mannerdescribed by Dembo and Seli (2004) and Yuksel (2006). Itappears that many students were quite open to changingtheir study practice once they became aware that this wasnecessary. What can be said, however, is that these studentswere consciously resistant to change only in that they werenot aware or convinced that change was or might benecessary. This possibility is not mentioned by Dembo, Seli,or Yuksel and so should be added to the list of ways in which‘conscious resistance to change’ can manifest.


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‘Unconscious resistance to change’, derived from thedifficulty associated with changing one’s practice, was clearlyevident among the students. It was partially evident instatements made by students about how difficult it was tochange. It was also evident from the observation that whenstudents did attempt to modify their practice the extent ofmodification was only modest – change was limited toshifting from the current category of practice to the next mostsophisticated category.

There are two significant pedagogical implications of thestudy findings that stand out: the need to open students’awareness about alternative study practices and thepossibility that they might need to modify their own practice;and the effect of the diversity of student practices on thedesign of ‘study skill’ interventions.

It was noted earlier that, despite considerable input in classon the need for students to give serious attention to theirstudy practices, many students appeared to remain unawareor unconvinced that such attention might be necessary. Evenwhen warning indications such as poor grades in first-semester tests were evident to students, some failed to realizetheir need to modify their study practice because theyattributed the problem to other factors such as ’I am stilladjusting’ or ’I am just behind and can catch up’. It was clearfrom the study that, with the majority of students, class inputwas not effective in bringing about the necessary shift inawareness. Only the pressure of poor performance in ‘teststhat count’ (such as mid-year exams) appeared to have thenecessary ‘power’ to generate the needed ‘wake-up call’ forthose students who needed to change their study practices.

These observations have several pedagogicalimplications. First, teachers need to find effective measuresfor generating the necessary wake-up call as early in the yearas possible. The study findings suggest that without suchmeasures, hearing the wake-up call will probably take abouthalf the academic year for most students who need to hear itand this may very well be too late. Secondly, poor marks in‘tests that count’ appear to be the most effective vehicle forconveying that call, and assessments should be designed andscheduled accordingly. Finally, while some input on studyskills is needed early in the year (e.g. for those who will payattention to it), some thought should be given to reviewingthis input in class at whatever point in the academic yearstudents begin to be convinced that they need to modify theirstudy practices and are therefore more open to paying seriousattention to the input provided.

The study identified three groupings of students withdifferent levels of study skills and different attitudes towardsmodifying their study practices. The first grouping consists ofstudents with study practices at the comprehension level.From the study findings, it appears that such students aretypically open to or are ‘open to becoming open’ todeveloping their learning practices once they become aware ofthe limitations of their current practice. The comments madeearlier, about the need to engineer circumstances that fosterthe opening of students’ awareness about alternative studypractices and their need to modify them, apply to these

students. In view of the extent of change that students in thisgrouping must negotiate, it is important that such awarenessis developed as soon as possible in the academic year andthat appropriate instruction, materials, and student supportshould be provided early in the year so that these studentshave available what is needed for them to begin the processof changing their learning practice when they become seriousabout wanting to do so.

The second grouping of students consists of those with aconsolidation level of study practice. Here the pedagogicalchallenge is somewhat different. The indication from thestudy is that if these students do make the effort to improvethe quality of their learning practice they are likely to besuccessful in developing to the refinement level of learningpractice. The problem with these students lies in the word ‘if’.Only about-half of the students in the study made the effortto modify their learning practice. It seems that with thesestudents, the level of sophistication of their learning practiceis high enough that it can mask their need to develop itfurther. Accordingly, it is particularly important to providemeasures for sensitizing these students to their need forchange and development – to engineer the ‘wake-up call’discussed earlier.

The third grouping of students consists of those whoenter university with a refinement level of study practice.Here a different kind of wake-up call is needed because thesestudents do not appear to recognize that there is still room forthem to develop their learning practice further – i.e. to theknow-how level. To help students to gain this awareness,formative ‘what if’ or ‘think about’ exercises could beincorporated in tutorials or in lectures and possibly in tests asoptional questions. The purpose of these formative measuresshould be made clear to the students; they should bepresented as forerunners to ‘higher level, world-related’questions that will appear in tests/exams later in the yearwhen all students have had a chance to develop their learningpractice to the extent needed to address such questionseffectively.

The study described in this paper set out to address a numberof questions about how, when, and why students modifytheir study practices. The findings suggest that, with regardto study practices, there is considerable diversity amongSouth African students entering engineering education today.Many enter with practices at only a comprehension level andmust develop their practice to at least a refinement level inorder to improve the quality of their learning and theirchances of passing. Some enter with a consolidation level ofpractice which, although more sophisticated in nature, stillrequires further development to raise the quality of theirlearning and to improve their chances of performing wellacademically. However, these students are more ‘resistant tochange’ in that it is more difficult for them to becomeconvinced that they do need to pay attention to modifyingtheir study practice. Students who enter with a refinementlevel of study practice do not have much scope for developingtheir practice further but can benefit from developing to aknow-how level of practice.

The findings with regard to the dynamics of change

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associated with modifying one’s study practice suggest thatopening the awareness of students with regard to thepossibility that aspects of their learning practices need tochange is critical but difficult to engineer. For students whoenter with comprehension and consolidation levels of studypractice, it appears that the most effective means forengineering the appropriate wake-up call is to implement‘tests that count’ early in the academic year so that studentswho are likely to perform poorly come to this realization asearly as possible. (Obviously, care must be taken that suchassessments should contribute to their final mark only to theextent necessary for an effective wake-up call to beengineered, and should not count so much that failure inthese assessments is demoralizing and cripples their chancesof passing the year.) For students who enter with arefinement level of study practice a different kind of sensiti-zation appears to be necessary – one that is more motiva-tional in nature and facilitates reflection and deepens interestin how the material being learned is relevant to real-worldsituations.

Although the findings presented in this paper areidiosyncratic to the students involved in this study, it is verylikely that the conclusions that have been reached are morewidely applicable to entrants to South African engineeringeducation in general.

AKERLIND, G.S. 2005. Learning about phenomenography: interviewing, dataanalysis and the qualitative research paradigm. Doing DevelopmentalPhenomenography. Bowden, J. and Green, G. (eds). RMIT UniversityPress, Melbourne.

BROWNLEE, J., PURDIE, N., and BOULTON-LEWIS, G. 2001. Changing epistemologicalbeliefs in pre-service teacher education students. Teaching in HigherEducation, vol. 6. pp. 247–268.

CASE, J. and GUNSTONE, R. 2002. Metacognitive development as a shift inapproach to learning: an in-depth study. Studies in Higher Education, vol.27. pp. 459–470.

CLARK, R.E. 2008. Resistance to change: Unconscious knowledge and thechallenge of unlearning. Fostering Change in Institutions, Environments,and People: a Festschrift in honor of Gavriel Salomon. Berliner, D. andKupermintz, H. (eds). Routledge, New York.

CLARK, R E. 2010. Cognitive and neuroscience research on learning andinstruction: recent insights about the impact of non-conscious knowledgeon problem solving, higher order thinking skills and interactive cyber-learning environments.http://www.cogtech.usc.edu/publications/clark_2010_nonconscious_learning_motivation_icer_9sep2010.pdf

CLIFF, A.F. 1995. A qualitative review of study behaviour before and during thefirst year of engineering studies. Higher Education, vol. 29. pp. 169–181.

CLIFF , A.F. 1996. Conducting a program of learning improvement with'educationally disadvantaged' students in engineering. InternationalJournal of Engineering Education, vol. 12. pp. 165–171.

CLIFF , A.F. 2000. Dissonance in first year students' reflections on theirlearning. European Journal of Psychology of Education, vol. 15, no. 1. pp. 49–60.

DEMBO, M.H. and SELI, H.P. 2004. Students' resistance to change in learningstrategies courses. Journal of Developmental Education, vol. 27. pp. 2–11.

ENTWISTLE, N.J. 1998. Approaches to learning and forms of understanding.Teaching and Learning in Higher Educationi. Dart, B.C. and Boulton-Lewis, G. (eds). Australian Council for Educational Research, Melbourne.

GREEN, P. 2005. A rigorous journey into phenomenography: from a naturalisticenquirer standpoint. Doing Developmental Phenomenography. Bowden, J.and Green, G. (eds). RMIT University Press, Melbourne.

HATTIE, J., BIGGS, J., and PURDIE, N. 1996. Effects of learning skills interventionson student learning: a meta-analysis. Review of Educational Research,vol. 66. pp. 99–136.

MARTON, F. and BOOTH, S. 1997. Learning and Awareness. Lawrence ErlbaumAssociates, Mahwah, New Jersey.

MEYER, J.H.F. 1991. Study orchestrations: the manifestation, interpretation andconsequences of contextualised approaches to learning. Higher Education,vol. 22. pp. 297–316.

MEYER, J.H.F., CLIFF, A F., and DUNNE, T.T. 1994. Impressions of disadvantage:II - monitoring and assisting the student at risk. Higher Education, vol.27. pp. 95–117.

MEYER, J.H.F., DUNNE, T.T., and SASS, A.R. 1992. Impressions of disadvantage: I- school versus university study orchestration and consequences foracademic support. Higher Education, vol. 24. pp. 291–316.

SIMELANE, Z.F. 2007. Identification and classification of incoming learningbehaviours amongst a sample of first year, English second language,engineering students: a case study. University of the Witwatersrand.

VERMETTEN, Y.J., VERMUNT, J.D. and LODEWIJKS, H.G. 2002. Powerful learningenvironments? How university students differ in their response to instruc-tional measures. Learning and Instruction, vol. 12. pp. 263–284.

WINGATE, U. 2006. Doing away with 'study skills'. Teaching in HigherEducation, vol. 11. pp. 4457–469.

WOOLLACOTT, L.C. 2013. On the learning practices of first year chemical andmetallurgical engineering students at Wits: A phenomenographic study.PhD thesis, University of the Witwatersrand.

YUKSEL, S. 2006. Undergraduate students' resistance to study skills course.College Student Journal, vol. 40. pp. 158–165. ◆


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Ferrous 2016FERROUS AND BASE METALS

DEVELOPMENT NETWORK CONFERENCE 20167–11 November 2016 · MSC Sinfonia Cruise, Durban-Mozambique-Durban

BACKGROUNDThrough its Advanced Metals Initiative (AMI) the South African Department of Science and Technology (DST) promotes research, developmentand innovation across the entire value chain of the advanced metals field. The goal of this initiative is to achieve sustainable local mineralbeneficiation and to increase the downstream value addition of advanced metals in a sustainable manner. The achievement of this is envisionedto be through human capital development on post-graduate and post-doctoral level, technology transfer, localization and ultimately,commercialisation.The AMI comprises four networks, each focussing on a different group of metals. These are Light Metals, Precious Metals, Nuclear Materialsand Ferrous and Base Metals (i.e. iron, steel, stainless steels, superalloys, copper, brass, etc.).The AMI FMDN 2015 Conference aims to bring together stakeholders from the mineral sector, academia, steel industry, international researchinstitutions and government in order to share and debate the latest trends, research and innovations, specifically in the areas of energy,petrochemical, corrosion, materials for extreme environments and transport, local mineral beneficiation and advanced manufacturing relatedto these materials. Keynote speakers to be invited include international specialists in the fields of ferrous metals, computational materials science, high temperaturecorrosion and mineral beneficiation.The Ferrous and Base Metals Development Network (FMDN) of the DST’s Advanced Metals Initiative (AMI) programme will host the AMI’sannual conference in 2016. The conference seeks to share insight into the state of R&D under the AMI-FMDN programmes and explore anddebate the following broad themes:

� Development of high performance ferrous and base metal alloys for application in the energy and petrochemical industries

� Development of corrosion resistant ferrous and base metal alloys

� Development of lightweight and/or durable steels for cost-effective transportation and infrastructure, and

� Panel discussions on possible future value-adding R&D programmes under FMDN within the South African National Imperatives.

WHO SHOULD ATTENDStakeholders from the energy, petrochemical, corrosion andtransportation industries where ferrous (i.e. iron, steel, stainless steels,superalloys, etc.) and base (i.e. copper, brass, etc.) metals are used intheir infrastructure. Also included in this invitation are local andinternational Higher Education Institutions (HEIs), GovernmentDepartments and Science Councils that are involved and/or have interestin R&D in these areas.

advanced metals initiative

our future throughscience

For further information contact:Head of Conferencing, Raymond van der BergSAIMM, P O Box 61127, Marshalltown 2107

Tel: +27 11 834-1273/7 ·Fax: +27 11 833-8156 or +27 11 838-5923E-mail: [email protected] · Website: http://www.saimm.co.za

Conference

Announcement

OBJECTIVESInsight into ferrous and base metal materials R&D for applicationin the areas of energy, petrochemical, corrosion, extremeenvironments, improved processing technologies and advancedalloys for the transport industry in South Africa and globally.

EXHIBITION/SPONSORSHIPSponsorship opportunities are available. Companies wishing tosponsor or exhibit should contact the Conference Co-ordinator.

Cemented tungsten carbides (also known ashardmetals) are used extensively in the miningand manufacturing industries, and account forapproximately two-thirds of the world’stungsten consumption. If present productionvolumes continue, the world’s tungstenresources could be depleted in 40 years (Ishidaet al., 2012). In addition to this mineraldepletion, raw material costs are high.Therefore recycling of tungsten carbide scrapis becoming increasingly important. For thecurrent study two different recycling methodswere investigated, namely the zinc recyclingprocess and acetic acid leaching. The aim ofthe research was to determine whether the tworecycling techniques could be used as comple-mentary processes on an industrial scale torecycle cemented tungsten carbide mining toolscrap. The recycled products would then beconverted into feedstock powders for themanufacture of new mining tools, only if therecycled powders have properties similar tonewly purchased powders, to ensure toolintegrity. Although the zinc recycling processis currently being used globally, to theauthors’ knowledge, the acetic acid leachingtechnique is not used to produce commercialcemented tungsten carbides. Therefore theassessment and comparison of both recycling

methods can potentially improve the successfulusage of recycled materials, leading to lessdependence on large quantities of new rawmaterials. In this way, raw material costs maybe reduced and the global demand forproduction and mining of tungsten becomesless urgent. Successful recycling will alsoensure that mining and manufacturingindustries dependent on tungsten carbide toolsare not adversely affected. A brief review ofthe recycling of hardmetals will be given first,followed by the methodology and results of theresearch undertaken.

Recycling of cemented tungsten carbidematerials is usually energy-intensive andenvironmentally unfriendly (Edtmaier et al.,2005). According to Paul et al. (1985),cemented tungsten carbide recycling methodscan be subdivided into two general categories,namely removal of the binder metal using aselected process, leaving a finely dividedcarbide matrix behind (skeleton-like,framework structure) or by chemical modifi-cation methods which convert the carbides intoa different form, for example into oxides.Numerous methods have been developed torecycle hardmetal scrap materials, namely, acidleaching, electrochemical methods, blasting,oxidation/chemical modification at hightemperature, liquid metal infiltrationtechniques, and hybrid methods (combinationsof the aforementioned processes). In thecurrent study two recycling methods were

Recycling of cemented tungsten carbidemining tool scrap by C.S. Freemantle*† and N. Sacks*

The zinc recycling process (PRZ) and acetic acid leaching (AC) weresuccessfully employed to recycle cemented tungsten carbide mining toolscrap for re-use as production powders. The main success of the PRZprocess was that it produced powders which were suitable for manufac-turing sintered alloys having properties within the commercial benchmarkranges for WC-6 wt% Co mining-grade tools. Although the powdersproduced from the AC process were deemed unsuitable for manufacturingthe same grade of mining tools, the process cannot be viewed as a failure,since the recycled powders are suitable for different commercialapplications. The two recycling processes can therefore be used as comple-mentary processes on an industrial scale.

cemented tungsten carbide, recycling, zinc process, acetic acid leaching,mining tools.

* School of Chemical and Metallurgical Engineeringand DST-NRF Centre of Excellence in StrongMaterials, University of the Witwatersrand,Johannesburg, South Africa.

† Pilot Tools (Pty) (Ltd), Johannesburg, SouthAfrica.


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Recycling of cemented tungsten carbide mining tool scrap

employed to recycle cemented tungsten carbide mining toolscrap, namely acid leaching and zinc recycling. A brief reviewof each process is given below.

The zinc process is the most widely used recycling process inthe cemented carbide manufacturing industry. It is commonlyreferred to as ‘PRZ’, an abbreviation for ‘process of recyclingwith zinc’. This method has experienced renewed interestsince 2005 (when global tungsten prices increased) as it isthe most cost-efficient and environmentally friendly recyclingmethod. Prior to 2005, only 20–25 % of hardmetals wererecycled in Europe, but today recycling has reached almost50% (Karhumaa and Kurkela, 2013). In the PRZ process, thescrap material is sourced, sorted, and then packed intographite boats or crucibles together with zinc. The furnace isevacuated of air, filled with argon, and heated to temper-atures ranging from 750°C up to 960°C, depending on thedetails of the process such as furnace type, nature of thescrap, etc. (Barnard et al., 1970). Treatment of the carbidewith molten zinc at these temperatures results in the zinc andthe metal binder (typically cobalt) forming a liquid alloy asthe zinc is pulled through the carbide scrap by a powerfulvacuum. The zinc is removed by distillation, and the resultingproduct consists of a mixture of the carbide and the metalbinder, in which the bond between the two has been broken(Barnard et al., 1970; Karhumaa and Kurkela, 2013; Trent,1946). This recycled product is easily broken down bymechanical means to a particle size similar to that of thegrain size of the original cemented carbide microstructure.The zinc vapours are recovered by condensation in a coolerzone of the distillation furnace. The weight ratio of zinc tometal binder used may range from 30:1 to 10:1, with apreferred range of 15:1 or 20:1. The time required for thetreatment depends on the size and shape of the scrapmaterial (Barnard et al., 1970).

There are several patents and publications relating to acidleaching technology for cemented carbides. Kinstle andMagdics (2002) described a method of recovering tungsten,vanadium, chromium, and molybdenum metals from carbidemetal scrap by treatment with an alkali metal hydroxide inthe presence of oxygen at an elevated temperature andpressure for a period of time sufficient to form a water-soluble alkali metal hydroxide. The metals are then recoveredfrom the water-soluble alkali metal salt using chemicalmeans. According to Seegopaul and Wu (1998) cementedcarbide materials can be reclaimed by oxidizing scrap intotetragonal and octahedral tungsten trioxide, which isinsoluble in water with a neutral pH. This material is digestedin an acidic solution that selectively dissolves the cobalt andnot the tungsten. Cobalt hydroxide and oxychloride areprecipitated by raising the pH to between 6 and 10. Thetungsten and cobalt compounds are separated from the slurryand re-dissolved in an aqueous solution with a pH greaterthan 11. The product is spray-dried and carburized asnecessary.

Hydrothermal techniques have also been investigated byseveral researchers (Kojima, 2005; Reilly, 1983; Ritsko et al.,1982) in which the cobalt binder is extracted by using

hydrochloric acid at 110°C, and subsequently pulverizedusing ball milling. Due to its brittleness, the carbideframework remains behind. Oxidation was found to occurmore easily on these materials (probably due toactivated/fresh surfaces and reprocessing procedures), whichdegrades the properties of the resulting materials. Phosphoricacid leaching techniques have also been attempted by someauthors (Nützel and Kühl, 1979; Vanderpool and Kim, 1991).Tungstic acid is another method described by Brookes(1990), who investigated a leaching method that producesammonium paratungstate. Acid leaching, while successful, isknown to have a negative environmental impact, and the lowpH used typically results in a lack of selectivity duringleaching.

Three classes of WC-6 wt% Co materials were studied in thisresearch, namely materials produced from (a) new, un-recycled powders, (b) zinc recycled mining scrap metalpowders, and (c) acetic acid recycled powders. The newpowders (NP) were produced from a blend of 94 wt%tungsten carbide and 6 wt% cobalt powders, milled in a 600-litre production stainless steel mill, using a 3:1 ratio ofcemented carbide milling media to powder load, with 13.65wt% ethanol. The powder was milled to an Mv grain sizerange of 1.6–2.0 μm, measured using a Microtrac s3500particle size analyser. After milling, the powders were spray-dried under a constant 7 bar pressure using a Niro HC 120mixed flow spray dryer.

The zinc recycled powders (PRZ) were produced using acommercial PRZ process, in which graphite cruciblescontaining pure zinc and cemented carbide mining tool scrapcomponents were inserted into a furnace, which was thenevacuated of air and filled with argon. The temperature of thefurnace was raised to 930°C and held for 24 hours to allowfor zinc infiltration. Removal of the zinc was accomplished bya powerful vacuum and distillation process at 960°C over a36-hour time period, after which the load was graduallycooled to room temperature. The recycled product was thenmilled and spray-dried using the same production conditionsas for the NP. Prior to milling, the PRZ powder compositionwas adjusted to a 60:40 ratio; 60% zinc recycled scrappowder plus 40% NP. The reason for the dilution is thatrecycled mining scrap typically contains greater than 6 wt%Co (usually 8–12 wt% Co on average), thus requiringblending to return the batch composition to 6 wt% Co.

The acetic acid recycled (AC) powders were producedfrom acid-leached, zinc-recycled ‘oversize materials’. ThePRZ process often produces recycled products larger than 15mm in diameter, which are referred to as ‘oversize materials’.These products have generally been only partially attacked bythe molten zinc. It is deemed neither energy- nor production-efficient to subject these oversized products to the millingprocess described above to produce suitable powders. Onealternative is to subject these oversized products to a secondcycle of the PRZ process. However, on a commercial scale thisis not feasible, as the amount of oversized material producedis small, which would entail storing the recycled product untila production-size batch is ready for processing. The effects oflong-term storage on the recycled product are unclear at thisstage. Therefore the option of using acetic acid leaching on a

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laboratory scale, as a complementary recycling process, wasinvestigated. The powders produced from this process wouldalso be used for the commercial production of new tools, ifdeemed suitable. An acetic acid recycling plant, capable ofleaching approximately 150 kg of material, was constructedfor this study.

The plant operated at atmospheric pressure and 80°C,with an air flow rate of 120 litres per minute. The pH waskept below 4 at all times to maintain cobalt extraction, inaccordance with the work of Edtmaier et al. (2005). Therecycling process was run for 21 days, after which the aceticacid was extracted, and the recycled product was washedwith water repeatedly until the purple hue of the cobaltacetate was removed and the material was clean. The leachedscrap was then dried, and crushed in an 80-litre stainlesssteel ball mill with ethanol, with some new cobalt added tobring the batch composition back to 6 wt % Co. These ACpowders were milled to the same Mv grain size range (1.6–2.0 μm) as the NP and PRZ powders.

All three powders, NP, PRZ, and AC, were examinedusing a Carl Zeiss field emission scanning electronmicroscope (FESEM) and the powder morphologiescompared. It is well known that the properties of the powdersused to produce sintered tools have a significant influence onthe production processes used to achieve the final sinteredmicrostructure and material properties, which directlyinfluence the industrial performance of the tools (Walker,Reed, and Verma, 1999). One important powder property isslurry rheology, which is defined as the deformation and flowof the slurry under applied stress or strain (Steffe, 1996). Thepowder’s slurry rheology directly impacts the formation andproperties of the spray-dried granules, the density and sizedistribution of which has a major effect on the ease ofcompaction and subsequent shrinkage of the pressedcompacts (Bertrand, 2003; Walker, Reed, and Verma, 1999;Walker and Reed, 1999). A detailed analysis of the slurryrheology of the NP and PRZ powders was presented in aprevious publication (Freemantle and Sacks, 2015). In thecurrent research, the slurry rheology of the AC powders wasinvestigated and compared to that of the NP and PRZpowders.

Slurry rheology tests were performed using a BrookfieldR/S Plus rheometer equipped with a Pt-100 thermocouple andtemperature control jacket regulated by a Lauda Eco RE-420temperature control bath. A CC40 coaxial cylinder spindlegeometry was used for all experiments. The temperature ofthe slurry was held constant at 25°C and the slurries wereallowed to equilibrate to temperature while gently agitatedusing an IKA Eurostar 40 digital mixer equipped with a non-bubble generating turbine, inside a temperature control bath;after which 71 ml of sample was extracted from the mixing

cup and rheologically tested. Shear stress as a function ofshear rate was measured over 120 seconds, during which thespindle accelerates from 1 s-1 to 500 s-1 during the first 60seconds, and then decelerates to zero, at the same rate, in thefinal 60 seconds. Using the plot of shear stress against shearrate, approximate yield stress values were extrapolated fromthe y-intercept of the straight-line graphs of the spray-driedslurries, as for the Bingham plastic method (Darbouret et al.,2005; Lewis, 2000). To further understand the rheologyresults, the zeta potential of all three powders was testedusing a Malvern Nano-ZS Zetasizer at 25°C.

To assess the influence of the two recycling methods onthe final sintered material properties, the spray-dried, new(NP), and recycled powders (PRZ and AC) were compactedinto test pieces and sintered using commercial productionmethods. Comparisons were made to benchmark values ofsintered alloys manufactured using new, unrecycled powders.Cylindrical test pieces of 10 mm diameter were uniaxiallycompacted using a Fette MP-250 hydraulic press, whichresulted in a 20% shrinkage. The green compacts weresintered at 1430°C in an Ultratemp sinter-HIP furnace for 75minutes. During the last 20 minutes of sintering, the pressurewas increased to enable hot isostatic pressing. The sinteredtest pieces were then subjected to standard quality controltests used during commercial production. Sintered sampledensities were determined using the Archimedes principle ona Shimadzu AY120 scale equipped with an automatic densitysuspension and reporting system. The magnetic saturation ofthe sintered samples was measured using a Setaram 6461cobalt magnetic saturation machine, equipped with a Sigma-meter digital controller and a Scout Pro SPU402 digitalbalance. Magnetic coercivity of the sintered samples wasmeasured using a Dr. Foerster-Koerzimat coercimeter.Vickers hardness was measured using a Mitutoyo AVK-COhardness tester with an indenting load of 30 kg force appliedto the sample for 10 seconds.

The particle size distributions and zeta potential values ofeach powder slurry are reported in Table I. The mean volumeaverage particle size of the NP powder slurry is 1.43 µm,compared to 1.89 µm and 1.65 µm for the PRZ and ACpowders respectively. Despite having the finest mean volumeaverage particle size, the NP powder has the highest D10value and the lowest D90 value, indicating that the particlesize distribution of this powder is narrower compared to thePRZ and AC powders. This is illustrated in Figure 1. The ACpowder possessed the finest particles with D10 approaching0.4 µm, as well as coarse particles, which approached themaximum size (D90) of the PRZ particles, giving the AC


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NP 1.43 ± 0.004 0.53 ± 0.002 1.23 ± 0.002 2.59 ± 0.006 -0.4 ± 18.4PRZ 1.89 ± 0.007 0.47 ± 0.004 1.57 ± 0.013 3.79 ± 0.010 -16.3 ± 19.7AC 1.65 ± 0.348 0.41 ± 0.061 1.22 ± 0.078 3.31 ± 0.334 -19.5 ± 19.7


powder the broadest overall particle size distribution. TheFESEM micrographs in Figure 2 corroborate this, showingthat > 3 µm particles were present in both PRZ and ACpowders, while the NP powder particles reflect the narrowerdistribution range. Figure 2(c) shows that the AC powdercontained many extremely small particles, which is clearlyindicated in the overall particle size distribution curves(Figure 1) from which it can be seen the AC slurry containeda notable fraction of material less than 0.2 µm in diameter.

The zeta potential (Table I), which represents a slurry’sstability and tendency to agglomerate, indicated that the mostunstable (close to zero zeta potential) slurry was the NPpowder, while the PRZ and AC powders showed morenegative zeta potentials, which implies greater dispersion insuspension. Figure 3 shows the shear stress versus shear rategraph for the various slurries, in which apparent viscosity (inPa.s) is given by the gradient of each graph. NP slurriesexhibited a higher viscosity than the AC and PRZ slurries,which means increased capability of producing dense

granules when spray-dried; ideal for the compaction of greencomponents prior to sintering (Freemantle and Sacks, 2015;Walker and Reed, 1999).

The PRZ slurry recorded the lowest shear responsebecause of its coarser particle size distribution, andconsequently a lower volume per cent solids (due to a lowertotal surface area of the larger particles). The size of theparticulates within a slurry dominates slurry rheologybecause of the exponentially increasing surface area withdecreasing particle diameter and a corresponding exponentialincrease in slurry viscosity (Freemantle and Sacks, 2015; Heet al., 2004; Sun et al., 2010; Zhang et al., 2014). This,combined with the charge repulsion of the predominantly

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1210

negatively charged suspended particles within the slurry (asindicated by the zeta potential in Table I), reduced theviscosity of the PRZ slurry further. The AC slurry has asimilar zeta potential to the PRZ slurry, and thus thepresence of coarse particles (Mv) could lead one to expect theAC slurry to have a shear response close to that of PRZ.However, this was not found, and instead the shear responsewas close to that obtained for the NP slurry. This behaviourwas attributed to the large number of extremely fine partic-ulates, which greatly increased the surface area of the ACslurry (see Figure 2c) and hence the effective volume per centsolids, thereby increasing the slurry viscosity, despite thenegative zeta potential.

The yield stress of each slurry was extrapolated by usingthe y-intercept of the straight-line graphs in Figure 3, inaccordance with the Bingham-plastic model (Freemantle andSacks, 2015; He et al., 2004, 2006; Turian, 1997). Yieldstress is a dominant factor in determining whether spray-dried granules will emerge as solid or hollow particles(Bertrand et al., 2003; Walker and Reed, 1999). Previous

work found that a yield stress of approximately 10 Paresulted in solid granules, while values far below 10 Payielded granules with internal voids. The AC powder (yieldstress of 7.6 Pa) and the NP powder (yield stress of 9.2 Pa)both resulted in predominantly solid granules, while the PRZpowder (yield stress of 0.83 Pa) resulted in granules havinglarge internal voids. Ideal, dense spray-dried granules areknown to produce tools of a higher standard, compared totools produced from powders with a high internal porosity(Eckhard and Nebelung, 2011). Hence, the NP and ACslurries produce ideal powders, while the PRZ slurries requireoperational adjustment to produce suitable powder granules.

The sintered properties of the materials are listed in TableII, and the FESEM images of the microstructures are shownin Figure 4. The benchmark values for the commerciallyaccepted property ranges for a WC-6wt%Co mining tool gradeare also listed in Table II. As expected, the NP alloy is withinthe benchmark specifications, but with a slightly higher thanideal coercivity due to the fine grain size resulting from over-milling. The dependence of magnetic coercivity on grain size


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Table II

Material properties of the sintered alloys

Grade Magnetic saturation Coercivity (Oe) Vickers hardness Density (g/cc) Porosity rating* (wt% Co) (HV30)

NP 5.86 ± 0.04 158.7 ± 1.5 1433 ± 15 14.85 ± 0.01 <A02 B00 C00PRZ 5.52 ± 0.19 133.3 ± 1.5 1424 ± 8 14.97 ± 0.03 <A02 B00 C00AC 6.56 ± 0.10 98.0 ± 2.0 1282 ± 7 14.88 ± 0.02 A02 B00 C00Benchmark 5.2 - 6.1 120 - 160 1350 - 1450 14.80 - 15.00 A02 B00 C00* ISO standard 4505, 1978.


and its use in quality control is a well-documentedphenomenon in cemented carbides (Love et al., 2002;Upadhyaya, 1998; Vekinis and Bartolucci-Luyckx, 1987).The fine-grained WC microstructure of the NP material isvisible in Figure 4a. The PRZ alloy properties were within allthe benchmark ranges. The PRZ alloys had a coarsermicrostructure than the NP alloy, but finer than the AC alloy,with a few isolated large WC grains. The AC alloy propertiesdid not meet most of the benchmark values; they had anunacceptably high magnetic saturation value, low coercivityand Vickers hardness, but an acceptable density. Each of thesintered compacts had A02 porosity or less (which isacceptable commercially), and no B-type porosity or freecarbon present.

The magnetic saturation of the AC alloy was high due toiron contamination originating from the repeated millingcycles (in stainless steel mills) to which the powder wasexposed during its material lifespan. The first series ofmilling cycles were during production of the new alloy (beforerecycling), then the scrapped tool was subjected to the zincrecycling process which included crushing and milling tobreak down the recycled product, from which the oversizematerial was extracted and subjected to acid leaching, afterwhich the recycled product was milled to the requiredproduction grain size and further homogenized with theaddition of extra cobalt powder to achieve the requiredcomposition. The coercivity was low for two reasons, namelythe presence of too much magnetic material (Co and Fe), andthe coarse sintered grain size of the alloy. The large numberof very fine (< 0.5 µm) grains in the green compact, whichhave a large surface area and a tendency to react anddissolve, were consumed by the coarser grains during liquid-phase sintering, as per Ostwald ripening. This processresulted in the coarse-grained microstructure depicted inFigure 4c, which is directly responsible for the low Vickershardness. The AC alloy had an acceptable density andporosity (A02), which is attributed to the predominantly solidpowder granules produced from the slurries.

Based on the sintered material properties, the PRZpowders are suitable to be used for the production of thespecified mining-grade tools, but the AC powders areunsuitable for this specific mining tool application. However,based on the sintered properties, the AC powders may beused for alternative applications, e.g. components that requirehigh fracture toughness, where the coarser grainedhardmetals are generally used. Benchmark ranges forexisting hardmetal grades include a Vickers hardness of1150–1290 HV30 and a coercivity of 80–120 Oe. Thecomposition of the AC powders could be adjusted asnecessary to increase the cobalt content, to produce eventougher grades that are suitable for applications such asmilling media, shims, and possibly coal and hard-rock mining(Morrison, 2015).

The PRZ process has a high recovery rate, produces powderswith low impurity levels, and is an overall environmentallyfriendly process. The Zn may be re-used for multiplerecycling runs before requiring replacement. However, itsdisadvantages include high electricity consumption; the

material chemistry and composition can change throughmultiple recycling runs; and the material to be recycled doesnot always break down into powder in the first recycling run(Barnard et al., 1970; Karhumaa and Kurkela, 2013). Thelatter phenomenon was observed in the current study wherecoarse, oversize particles were produced from partial Zninfiltration. This would require a second recycling run (ormore) to reduce it to useable feedstock for manufacturing,thereby increasing powder consumption and productioncosts. Despite the negative aspects, it is a widely usedtechnique. From their work, Karhumaa and Kurkela (2013)predicted that the zinc recycling process will gain marketshare in the future as they believe that it has not yet realizedits full potential.

The advantages of the acetic acid leaching process arethat it can be conducted at low temperatures and pressures,and selectively leaches out the cobalt binder from betweenthe tungsten carbide grains. A further advantage is that theacetic acid can be regenerated by reclaiming the cobalt, usingoxalic acid addition to produce cobalt oxalates (which can beconverted back into cobalt) and leaving the acetic acidbehind. One of the main disadvantages of the leachingprocess used in the current study was the significant timeperiod (21 days) required to produce the recycled product.While the leaching process can be accelerated by, forexample, using pure oxygen, instead of air, and increasingthe pressure, this would increase the overall production costs(Edtmaier et al., 2005). Based on the current study, the mainadvantage in employing the current acetic acid leachingprocess is that it can be used in combination with the PRZprocess, where its primary function would be to recycle theoversize byproduct of the PRZ process. This byproductusually emerges from the PRZ process in a porous, semi-decomposed state, and would be easier to recycle than ‘pure’scrap metal. Using low energy input, the supplementaryacetic acid process could convert the oversize material intouseable powder without having to perform a second run inthe zinc recycling plant, which is very costly.

The zinc recycling process (PRZ) and the acetic acid leaching(AC) technique were successfully employed to recyclehardmetal mining tool scrap for re-use as production powder.The main success of the PRZ process was that it producedpowders that can be used to manufacture sintered alloyshaving properties within the commercial benchmark rangesfor WC-6wt% mining-grade tools. Although the powdersproduced from the AC process were deemed unsuitable formanufacturing the same grade of mining tools, the processcannot be viewed as a failure, since the recycled powders aresuitable for different commercial applications. Throughout thestudy comparisons were made between the two types ofrecycled powders and the results compared to the propertiesof newly purchased powder (NP). The NP powders producedthe narrowest grain size distribution during milling, had theleast ‘stable’ (i.e. most agglomerating) zeta potential, andhighest slurry viscosity and yield stress, which ultimately ledto ideal, dense powder granules after spray-drying; highlysuited for optimal compaction behaviour. The PRZ and ACpowders had coarser grain sizes than the NP powders, withbroader particle size distributions. Both recycled powders also

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had negative zeta potentials and were more dispersed withinthe slurry. The PRZ process produced hollow granules,requiring further slurry optimization to produce the correctgranules for further production. The fraction of extremelyfine grains in the AC powder increased the slurry viscosityand yield stress, producing high-quality solid spray-driedgranules ideal for compaction.

The authors wish to acknowledge the financial and technicalsupport received from Pilot Tools (Pty) Ltd, the Department ofScience and Technology, and the National ResearchFoundation, South Africa.

BARNARD, P.G., STARLIPER, A.G., and KENWORTHY, H. 1970. Reclamation ofrefractory carbides from carbide materials. US patent 3595484.

BERTRAND, G., FILIATRE, C, MAHDJOUB, H., FOISSY, A., and CODDETT, C. 2003.Influence of slurry characteristics on the morphology of spray-driedalumina powders. Journal of the European Ceramic Society, vol. 23. pp. 263-271.

BROOKES, K.J.A. 1990. Reclaimed tungsten powders with ‘virgin’ properties.Metal Powder Report, vol. 45, no. 2. pp. 131–132.

DARBOURET, M., COURNIL, M., and HERRI, J-M. 2005. Rheological study of TBABhydrate slurries as secondary two-phase refrigerants. InternationalJournal of Refrigeration, vol. 28, no. 5. pp. 663–671.

ECKHARD, S. and NEBELUNG, M. 2011. Investigations of the correlation betweengranule structure and deformation behavior. Powder Technology, vol. 206,no. 1-2. pp. 79–87.

EDTMAIER, C., SCHIESSER, R., MEISSL, C., SCHUBERT, W.D., BOCK, A., and SCHOEN, A.2005. Selective removal of the cobalt binder in WC/Co based hardmetalscraps by acetic acid leaching. Hydrometallurgy, vol. 76, no. 1-2. pp. 63–71.

FREEMANTLE, C.S. and SACKS, N. 2015. The impact of zinc recycling on the slurryrheology of WC–6wt.% Co cemented carbides. International Journal ofRefractory Metals and Hard Materials, vol. 49. pp. 99–109.

HE, M., WANG, Y., and FORSSBERG, E. 2004. Slurry rheology in wet ultrafinegrinding of industrial minerals: a review. Powder Technology, vol. 147,no. 1-3. pp. 94–112.

HE, M., WANG, Y., and FORSSBERG, E. 2006. Parameter studies on the rheology oflimestone slurries. International Journal of Mineral Processing, vol. 78,no. 2. pp. 63–77.

ISHIDA, T., ITAKURA, T., MORIGUCHI, H., and IKEGAYA, A. 2012. Development oftechnologies for recycling cemented carbide scrap and reducing tungstenuse in cemented carbide tools. SEI Technical Review, vol. 75. pp. 38–46.

ISO 4505. 1978. Hardmetals: Metallographic determination of porosity anduncombined carbon.

KARHUMAA, T. and KURKELA, M. 2013. Review of the hard metal recyclingmarket and the role of the zinc process as a recycling option. Proceedingsof the 18th Plansee Seminar, Reutte, Austria. Kneringer, G., Rodhammer,P., and Wildner, H. (eds). pp. 13/1–13/11.

KINSTLE, G.P. and MAGDICS, A.T. 2002. Process for recovering the carbide metalfrom metal carbide scrap. US patent 6395241.

KOJIMA, T., SHIMIZU, T., SASAI, R., and ITOH, H. 2005. Recycling process of WC-Cocermets by hydrothermal treatment. Journal of Materials Science, vol. 40,no. 19. pp. 5167–5172.

LEWIS, J.A. 2000. Colloidal processing of ceramics. Journal of the AmericanCeramic Society, vol. 83, no. 10. pp. 2341–2359.

LOVE, A., LUYCKX, S., and SACKS, N. 2010. Quantitative relationships betweenmagnetic properties, microstructure and composition of WC–Co alloys.Journal of Alloys and Compounds, vol. 489, no. 2. pp. 465–468.

MORRISON, J. 2015. Director, Pilot Tools Pty Ltd, South Africa. Personalcommunication.

NÜTZEL, H.G. and KÜHL, R. 1979. Process for decomposing hard metal scrap. USpatent 4349423A.

PAUL, R.L., TE RIELE, W.A.M., and NICOL, M.J. 1985. A novel process forrecycling tungsten carbide scrap. International Journal of MineralProcessing, vol. 15, no. 1-2. pp. 41–56.

REILLY, K.T. 1983. Recovery of refractory metal values from scrap cementedcarbide. US patent 4406866.

RITSKO, J.E., MACINNIS, M.B., and HENSON, T.L. 1982. Method of recovering metalcarbides. US patent 4348231A.

SEEGOPAUL, P. and WU, L. 1998. Reclamation process for tungstencarbide/cobalt using acid digestion. US patent 5728197A.

STEFFE, J.F. 1996. Rheological methods in food process engineering. 2nd edn.Freeman Press. Lansing, MI, USA.

SUN, L., ZHANG, X., TAN, W., ZHU, M., LIU, R., and LI, C. 2010. Rheology ofpyrite slurry and its dispersant for the biooxidation process.Hydrometallurgy, vol. 104, no. 2. pp. 178–185.

TRENT, E.M. 1946. Process of separating hard constituents from sintered hardmetals. US patent 2407752A.

TURIAN, R.M., MA, T.W., HSU, F.L., and SUNG, D.J. 1997. Characterization,settling, and rheology of concentrated fine particulate mineral slurries.Powder Technology, vol. 93, no. 3. pp. 219–233.

UPADHYAYA, G.S., 1998. Cemented tungsten carbides - production, propertiesand testing. Noyes Publications, New Jersey.

VANDERPOOL, C.D. and KIM, T.K. 1991. Electrolytic method for producingammonium paratungstate from cemented tungsten carbide. US patent5021133A.

VEKINIS, G. and BARTOLUCCI LUYCKX, S. 1987. The effects of cyclic precompressionon the magnetic coercivity of WC-6wt.%Co. Materials Science andEngineering, vol. 96. pp. L21-L23.

WALKER, W.J. JR., REED, J.S., and VERMA, S.K. 1999. Influence of granulecharacter on strength and Weibull modulus of sintered alumina. Journal ofthe American Ceramic Society, vol. 82, no. 1. pp. 50–56.

WALKER, W.J. Jr. and REED, J.S. 1999. Influence of slurry parameters on thecharacteristics of spray-dried granules. Journal of the American CeramicSociety, vol. 82. pp. 1711–1719.

ZHANG, X., DU, H., GONG, X., HU, X., and ZHANG, D. 2014. The importance ofsurface hydration and particle shape on the rheological property of silica-based suspensions. Ceramics International, vol. 40, no. 4. pp. 5473–5480. ◆


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For further information contact:Conference Co-ordinator, Yolanda Ramokgadi

SAIMM • Tel: +27 (0) 11 834-1273/7E-mail: [email protected] • Website: http://www.saimm.co.za

Metals play a significant role in industrialisation and technological advancements. Do you ever wonder then what life would be like without metal resources?

The depletion of natural rich ore deposits coupled with a fall ingrade, a decline in productivity, rising operational and energy costs,concerns on sustainability and environmental impact of mining andmetal related activities have been affecting the mining and metalsindustry in the recent past. Unless innovative methods that look at thesmart use and recovery of metals from metal resources are devel-oped, the world will be faced by a metal supply risk that will impact onfuture economic growth and technological development.

The SAIMM Hydrometallurgy Conference, 2016, will bring togetherinternationally and locally recognized experts, industries, R&D estab-lishments, academia as well as students to explore how future metaldemands can be met through modern hydrometallurgical technologiesthat can:

� Assist in sustainable metal extraction� Lower energy costs� Minimise the impact on the environment

TOPICSThe conference will include but not be limited to the following topics:

� Research and development in hydrometallurgy (novel andoptimised technologies)

� Processing of metallurgical and post-consumer waste� Removal of metals from effluent streams� Novel equipment and reagents in hydrometallurgical processing� Optimisation of energy use and energy recovery� Water management and utilisation in hydrometallurgical plants

First

Announcement

&

Call

for

Papers

The Southern African Institute of Mining and Metallurgyin collaboration with the SAIMM Western Cape Branch is hosting the

Hydrometallurgy Conference 2016

1–3 August 2016 · Cape Town

The conference will be of value to:

� Hydrometallurgical plant managers and metallurgists� Equipment and reagent suppliers to the

hydrometallurgical industry� Hydrometallurgical technology development companies� Mining industry consultants� Research and academic personnel

Companies wishing to sponsor or exhibit should contact the

Conference Co-ordinator.

SPONSORSHIP

• K. Osseo-Asare

• F. Crundwell

• M. Nicol

• M. Reuter

KEYNOTE SPEAKERS

Silicon nitride is among the new-hightechnology materials. It is usually synthesizedby reacting silicon with nitrogen. The productis a ceramic powder, and with sintering anddensification the structural ceramic isobtained. Resistance to thermal shock, high-temperature creep, erosion, and corrosionmake silicon nitride attractive for enginecomponents and cutting tools (Gnesin et al.,1978; Zilberstein and Buljan, 1984).

The main problem in production of siliconnitride is in the sintering and densification.Silicon nitride is very difficult to sinter to highdensities (Jack, 1976). Many additives havebeen used as sintering aids, many of which aredetrimental to the unique properties of siliconnitride, especially for high-temperatureapplications (Smith and Quackenbush, 1980;Govila, 1985; Kriz, 1983). Therefore, insteadof monolithic silicon nitride, compositematerials based on silicon nitride have beeninvestigated. In that respect, mixing siliconnitride powder with titanium carbide powderwill not only assist densification but also

enhance the properties further by combiningthe benefits of carbides and nitrides (Mah,Mendiratta, and Lipsitt, 1981). Si3N4-TiCcomposite materials are suitable for wear andmetal-cutting tool applications (Baldoni andBuljan, 1988).

Successful composite development requiresa detailed understanding of the chemicalinteractions between components of thecomposite materials. Chemical reactionsbetween the matrix phase and dispersedparticles during the sintering stage may alterthe properties relevant to performance insevere environments such as high-speed metalremoval (Buljan and Zilberstein, 1987).

However, little is known about thefundamental mechanistic of the reactionsbetween silicon nitride and titanium carbidethat assist property improvement. Thus, thepurpose of this paper is to report on theinvestigation related primarily to themechanism of the reactions between Si3N4 andTiC at temperatures between 1600°C and1700°C.

The reactions between silicon nitride andtitanium carbide in the powder compact underN2 and Ar atmospheres at temperatures of1600°C, 1650°C, and 1700°C were investigatedisothermally by thermogravimetric analysis(TGA).

Very high purity Si3N4 powder with lessthan 10 ppm Fe and 2 ppm Ca+Mg asimpurities, 1 μm average size, was mixed withvery high purity TiC powder with 6 ppm Fe and2 ppm Ca as impurities (both supplied byAldrich Chemical Company, Wisconsin, USA)under methanol with an agate mortar andpestle. The very low impurity levels were not

Titanium carbide—silicon nitridereactions at high temperatureby N. Can* and R. Hurman Eric*

The kinetics and mechanism of the chemical interaction between siliconnitride and titanium carbide were investigated using thermogravimetricanalysis (TGA). The samples were reacted isothermally at temperaturesbetween 1600°C and 1700°C under nitrogen and argon atmospheres. Theextent and rate of reaction increased with increasing temperature underboth atmospheres; however, both the extent and rate were higher underargon. Silicon nitride, in the presence of titanium carbide, was thermallystable under nitrogen and the reactions were confined to Si3N4/TiC andTiC/N2 interfaces. Under argon atmosphere silicon nitride dissociatedcompletely to liquid silicon and nitrogen gas within about four hours ofreaction time, depending on temperature, and a different reactionmechanism prevailed.

The kinetics of interaction between silicon nitride and titanium carbideunder nitrogen atmosphere was found to be controlled by the rate ofdiffusion of nitrogen into the titanium carbide/carbonitride phase. Underargon atmosphere the rate was found to be controlled by the rate ofdissociation of silicon nitride. For both cases the mechanisms of reactionswere determined in detail and then modelled.

silicon nitride, composite materials, densification, titanium carbide.



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Titanium carbide—silicon nitride reactions at high temperature

considered to have any effect on the reactions. The averageparticle sizes of the TiC powders were 3, 5, 50, and 100 μm.After mixing Si3N4 and TiC powders at certain volume per centratios (20, 30, and 40 vol% TiC, balance Si3N4), the powdermixtures were pressed into disc shapes. The green density ofthe compact was kept constant at approximately 60% of theideal density based on the linear rule of mixtures by applyingconstant uniaxial pressure of 5 t. The approximate dimensionsof the pellets were 10 mm diameter and 5 mm thickness. Thekinetics of the reactions between Si3N4 and TiC wereinvestigated by measuring the weight change upon reactionstaking place in the powder compact at constant temperaturesand different time intervals using TGA.

The TGA set-up consisted of gas cleaning and regulatingfacilities, a vertical-tube furnace with six lanthanum-chromiteheating elements parallel to the recrystallized alumina worktube axis, and a balance positioned at the bottom of thefurnace assembly and linked to a computer for continuousweight change measurements. Although this set-up wassuitable for continuous weight change measurements, thedrift of the balance caused some experimental error.Therefore, in addition to continuous weight lossmeasurements, intermittent weight change measurementswere carried out by an outside balance.

Sample pellets were charged into the furnace and reactedunder flowing N2 or Ar gas streams at a flow rate of 800 ml/min at atmospheric pressure. Experiments werecarried out at the temperatures mentioned earlier. Sampleswere then lowered to the cool end of the furnace tube andquenched by the incoming stream of the gas.

The maximum reaction time for each set of experimentswas selected in such a way that after the longest holding timethere was no weight change; in other words the curve ofpercentage reaction completed versus reaction time levelledoff. This maximum holding time for any set of experimentsunder nitrogen atmosphere was 16 hours. Nevertheless, anidentical experimental run for each set of experiments wasperformed up to 36 hours to check if weight changes wouldoccur. All the experiments were performed twice, and if morethan 10% difference in mass loses was found the experi-mental system was checked for leaks by additional carbonblank runs. Normally, carbon blank runs were done afterevery 15 experiments for a period of two hours to ensure asound operating system.

The actual reactions between Si3N4 and TiC are complicated.Therefore, preliminary thermodynamic calculations werecarried out in the Si-Ti-C-N system with respect to purespecies in standard state to understand the chemicalinteractions in the composite during sintering. Table I showspossible reaction products after reaction of Si3N4 and TiC,including unreacted species.

Standard free energy changes of possible reactions werestudied at temperatures between 1300°C and 2000°C byusing a thermodynamic program, Thermo V2.03 (Mintek,South Africa) based on a free energy minimization technique.Only two reactions have been considered due to lowerstandard free energy change values: these are:

Si3N4 (s) + 4TiC(s) = 3SiC(s) + 4TiN(s) + C(s) [1]

Si3N4 (s) + 3TiC(s) = 3SiC(s) + 3TiN(s) + ½N2 (g) [2]

Poster (1988) has proposed that TiC and TiN can formTiC1-xNx solid solution at high temperatures by the followingreaction:

(1-x)TiC(s) + x TiN(s) = TiC1-xNx (s) [3]

Since the change in lattice parameter of the solid solutionobeys Vegard’s law (Goldschmidt, 1967) TiC1-xNx solidsolution was assumed to behave ideally in this investigation.The standard free energy of formation of TiC1-xNx ideal solidsolution may be calculated by the following equation:

G°f <TiC1-xNx> = (1-x) G°f <TiC> + x G° <TiN> + RT {xln(x) + (1-x) ln (1-x)} [4]

When the possibility of formation of TiC1-xNx solidsolution is considered, Equations [1] and [2] become

xSi3N4(s) + 4TiC(s) = 3xSiC(s) + 4TiC1-xNx(s) + x C(s) [5]

[6]

The stability regions of Equations [1], [2], [5], and [6]are illustrated in Figure 1. Clearly, reactions [5] and [6] arethermodynamically more stable than reactions [1] and [2] forthe temperature range of the study. Therefore, formation of

▲

1216

C N C SiCC2 N2 Ti Si3N4

C3 NCN TiC TiSiC4 Ti TiN TiSi2C5 Si Si Ti5Si2CN Si2CN2 Si3C2N SiCC2N2 SiC2

C4N2 Si2CCNN SiNSi2N

Δ

titanium carbonitride is thermodynamically more favourablethan formation of TiN as a reaction product. At temperaturesbetween 1600°C and 1700°C the difference in calculatedstandard free energy change of reactions [5] and [6] is verysmall, thus the kinetics will play a major role. However, if N2pressure is increased in the system (such as high-temperature gas pressure sintering), reaction [5] will be themain reaction in the system.

Kinetic analyses in the Si3N4-TiC system were carried outin N2 and Ar atmospheres in the temperature range of1600°C and 1700°C and the weight losses were observed.Therefore, it was assumed that Equation [6] is the dominantreaction in the system. Observed weight losses wereconverted into the per cent reaction completed values asfollows:

[7]

The maximum possible weight loss in Equation [7] isobtained from the stoichiometry of reaction [6] assuming amaximum possible attainable value of 1.0 for the factor ’x’.Then the maximum possible weight loss will be equal to1/6(WTiC)(MN2/MTiC), where WTiC is the mass of TiC in thesample powder compact, and MN2 and MTiC are the molecularmasses of the N2 gas (which leaves the sample and causesweight loss) and TiC respectively.

According to the kinetic results obtained, the most significantfactor influencing the reaction rate and extent of reactionunder nitrogen atmosphere was found to be temperature,with about five times increase between 1600°C and 1700°Cas illustrated in Figure 2. The effect of temperature increasefrom 1600C° to 1650°C on the reaction rate and extent ofreaction is not as significant as temperature increase from1650°C to 1700°C. This can be attributed to a decrease in thethermal stability of silicon nitride because the equilibriumnitrogen pressure above silicon nitride is one atmosphere at1900°C; its normal dissociation temperature. Therefore,partial dissociation of silicon nitride significantly increasesthe reaction rate.

Percentage reaction completed versus time curves attemperatures of 1600°C and 1650°C showed a marked slow-down in the reaction rate after approximately one hour ofreaction time (based on slopes of the curves in Figure 2).This change in the rate of the reaction is most probably dueto the nature of the solid-solid reactions where reactionproducts form a diffusion barrier (Zilberstein and Buljan,1984). However, for reactions at 1700°C, formation of thisdiffusion barrier takes longer, and the reason for this may bethe presence of liquid silicon due to partial dissociation ofsilicon nitride as found in this study. The presence of liquidsilicon (even if it exists temporarily under nitrogenatmosphere) enhances reactions by increasing the rate ofdiffusional mass transfer of nitrogen and carbon through theliquid phase in comparison to their diffusion in tightly boundsolid phases such as silicon carbide and titaniumcarbonitride.

The kinetic curves for three different volume percentagesof TiC in the initial pellet reacted under similar conditions aregiven in Figure 3. As can be seen, the increase in volumeconcentration of TiC increases the reaction rate and the extentof reaction. Since the amount of Si3N4 was always higher

than the stoichiometric amount dictated by Equations [5] and[6], saturation of the reaction with increasing TiC content isnot expected. An increase in TiC content in the preparedsamples increases the surface area where there is directcontact between Si3N4 and TiC particles, and consequentlyincreases the reaction rate. At 1700°C the extent of reactionincreases three times when the volume concentration of TiCincreases from 20 to 40 vol%. Therefore, concentration of TiCconstitutes the second largest effect (after temperature) onthe reaction kinetics between Si3N4 and TiC. This indicatesthat reactions between Si3N4 and TiC occur on the contactpoints or interfaces, which is common for solid-solidinteractions.

In order to elucidate the effect of particle size on thereaction kinetics, the particle size of the silicon nitride waskept constant and titanium carbide particle sizes wereincreased from 5 µm to 100 µm. The results are shown inFigure 4. The effect of increasing particle size of TiC on therate and extent of reaction was not very pronounced duringthe first 30 minutes, after which there is a large decrease inreaction rate and extent when the TiC particle size isincreased to between 50 and 100 µm.

Changing the particle size of TiC from 50 µm to 5 µmdoubled the extent of reaction. It seems that particle size isless critical for the extent and rate of the reaction thantemperature and volume concentration of TiC.

Figure 5 compares the XRD patterns that were obtainedfrom 30 vol% TiC reacted under N2 atmosphere at 1600°C fordifferent retention times. It is clear that the primary peaks ofsilicon nitride exist even after twelve hours of reaction time,and silicon carbide formation becomes noticeable after fourhours of reaction. The position of the titanium carbide peakon the XRD pattern has been marked, as shown in Figure 5,


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µ


and as the retention time increases, titanium carbonitrideformation is reflected by the gradual shift from the indicatedtitanium carbide peak position to higher 2Ө° values, towardthe hypothetical titanium carbonitride peak. The shape(broadness) of the titanium carbide peaks may indicate theexistence of a wide range of composition within the reactedpowder mixture. Since the starting powder contains a fairlynarrow size range of titanium carbide particles, the peakbroadening and shift can only be attributed to the formationof titanium carbonitrides. The maximum ‘x’ value in TiC1-xNxwas found to be 0.67 under nitrogen atmosphere. The ‘x’value was derived as follows. Titanium carbide and titaniumnitride have simple cubic crystal structures that are identicalto the NaCl structure. Therefore, the TiC1-xNx peaks in theXRD patterns lie between the positions of the titaniumcarbide and titanium nitride peaks. The shift of TiC1-xNxpeaks from (2 0 0) and (1 1 1) planes was measured bytaking into account the angular distance between titaniumcarbide and titanium nitride peaks from the same crystallo-graphic planes. After calculation of each shift from itsrespective plane, the ‘x’ value that represents titaniumcarbonitride composition was deduced by taking the averageof those two values. The ‘x’ values were also checked by SEMpoint analysis. The error in the calculations and measurementof the ‘x’ was approximately 4 per cent.

The nature of the interactions between Si3N4 and TiC changeddrastically when the experiments were carried out under Aratmosphere. Si3N4 is not stable under Ar atmosphere in thepresence of TiC and dissociates into liquid silicon andnitrogen. Therefore, the later stages of the interactions in thesystem involve to a large extent interactions with the liquidphase, which is rich in silicon.

The effect of temperature on the extent and the rate ofreaction between silicon nitride and titanium carbide isillustrated in Figure 6. As in the case of reactions undernitrogen atmosphere, increasing temperature increases theextent and the rate of the reaction. At 1600°C and 1650°C theextent of reaction increases gradually, whereas for samplesreacted at 1700°C there is a sharp increase in the rate andextent of reaction initially (0 to 120 minutes of reactiontime). This can be attributed to the decreasing stability ofsilicon nitride with increasing temperature and, consequentlyan increase in the liquid silicon-rich phase. The extent ofreaction at 1700°C reaches almost 100 per cent after sixhours of reaction time, indicating that almost all of the siliconnitride in the powder compact dissociated, whereas it takes

eight to ten hours to reach 100 per cent at 1650°C and1600°C respectively.

The effect of changing TiC concentration on the extentand rate of the interactions under Ar atmosphere is depictedin Figure 7. During the first hour, the reaction between Si3N4and TiC under Ar atmosphere at 1700°C is not affected bychanging TiC concentration. In the later stages of thereaction, however, decreasing TiC concentration increases thepercentage reaction completed. Since the reaction ratedepends predominantly on the dissociation of Si3N4 under Aratmosphere, this dissociation reaction takes place at a higherrate (see Figure 8) in the earlier stages of the interactions andobscures the effect of TiC concentration. The silicon-richphase is produced as a dissociation product of Si3N4. This

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µ

phase can also contain some dissolved Ti, C, and N. Duringthe later stages, the interactions occur by reaction of theremaining TiC with the Si-rich phase. Decreasing TiC concen-tration seems to increase the extent of chemical reactionswith this intermediate phase. However, differences inpercentage reaction completed are small.

Figure 8 compares the XRD patterns that were obtainedfrom 30 vol% TiC reacted under Ar atmosphere at 1650°C fordifferent retention times. The peaks representing siliconnitride phase in the XRD pattern disappeared after four hoursof reaction under Ar atmosphere, i.e. almost all of the Si3N4dissociated within four hours. The increase in the amount ofSiC, which may be noted from the increasing intensity of the(111) plane of the β-SiC diffraction peak, was much less inN2 atmosphere than in Ar atmosphere. This also confirmsthat silicon nitride dissociates much faster in an Aratmosphere and reaction between liquid silicon and TiCoccurs at a much higher rate than the reactions with Si3N4and TiC (both reactions produce SiC). The sharp shift in thediffraction peak of titanium carbide is also noticeable inFigure 8. The maximum ‘x’ value of the titanium carbonitridephase under argon atmosphere was calculated as 0.78.

Considering the results of the preliminary thermodynamic,TGA, and X-ray diffraction analyses, a unique reactionmechanism for the system Si3N4-TiC can be proposed. Thenature of the reaction in the Si3N4-TiC system dependsstrongly on the partial pressure of nitrogen gas in the system,thus two reaction mechanisms in the ceramic compositeduring sintering stage are proposed.

The situation just before the reaction between Si3N4 andTiC in in a N2 atmosphere is shown in Figure 9. TiC particlesare irregular in shape with average particle size of 3 µm, andSi3N4 particles are round with 1 µm average particle size.Nitrogen gas occupies the voids between the particles.

The initial stage of the reactions in N2 atmosphere(Figure10) commences by the direct contact of Si3N4 and TiCparticles as well as N2 reaction with TiC particles at thegas/TiC interface. Direct reaction between Si3N4 and TiC takesplace by Equation [6], in which nitrogen atoms diffuse fromthe Si3N4 matrix to the TiC matrix to form the thermodynam-ically stable TiC1-xNx phase and rejected carbon atoms fromthe TiC matrix react with Si3N4 to form SiC. Similarly, at thegas/TiC interface, nitrogen atoms from the gas phase diffusethrough the TiC matrix and form TiC1-xNx. Carbon atoms

from the formation of the TiC1-xNx phase diffuse through thegas/TiC interface or Si3N4/TiC reaction interface to the surfaceof the titanium carbonitride phase and are deposited thereuntil they eventually react further to form SiC.

As the reaction proceeds further (Figure 11) in N2atmosphere, reaction product layers form between thereaction interfaces. The SiC phase forms between the Si3N4and TiC1-xNx phases and grows by solid state diffusion ofcarbon atoms through SiC reaction product layer to theSiC/Si3N4 reaction interface. Some of the nitrogen gas, eitherfrom direct reaction of TiC and Si3N4 or reaction of carbonand Si3N4, leaves the system and causes weight loss. Thereaction interface between TiC1-xNx /TiC penetrates towardthe centre of the particle to consume unreacted TiC matrix bysimultaneous diffusion of carbon and nitrogen atoms.


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Since Si3N4 is not thermodynamically stable in an Aratmosphere within the experimental temperature range, it willdissociate into Si (l) and N2 (g). Therefore, Equation [6] willbe the main reaction in the Si3N4 -TiC system during sinteringin Ar atmosphere. Similar to the reactions in N2 atmosphere,interaction between Si3N4 and TiC starts at the direct contactsurfaces between the particles, in which nitrogen atomsdiffuse to the TiC matrix to form TiC1-xNx and carbon atomsfrom this reaction simultaneously diffuse through thereaction product layers and react with Si3N4 to form SiC(Figure 12). Reactions in the Si3N4 -TiC system enhance thedissociation of Si3N4 and thus liquid silicon and N2 gas coverthe TiC particles.

In the later stages of the reaction (Figure 13), siliconnitride particles become irregular due to dissociation. Thepartial pressure of N2 gas within the powder compact is equalto the equilibrium partial pressure of N2 gas above Si3N4particles. Reactions in the system proceed similar to reactionsin N2 atmosphere through diffusion of nitrogen atoms to thereaction interface between TiC1-xNx and unreacted TiC, andcarbon atoms that are rejected from TiC diffuse through thereaction product layers to the Si (l)/SiC reaction interface orundissociated Si3N4/SiC reaction interface.

High-temperature interactions between Si3N4 and TiC in N2and in Ar atmosphere are governed mainly by the reaction:

The reaction products consist of β-SiC and TiC1-xNx in N2atmosphere, as well as liquid silicon in Ar atmosphere. Si3N4 isnot stable in Ar atmosphere and completely dissociates intoliquid silicon and nitrogen, and interactions between Si3N4 andTiC increase the dissociation rate of Si3N4. After the reactionsin Ar atmosphere, the matrix phase consists of liquid siliconand SiC and all the TiC particles are converted into TiC1-xNx byreaction with nitrogen. However, in N2 atmosphere, even afterprolonged reaction periods, Si3N4 is the stable phase in thesystem and forms the matrix. The reaction rate and extent inAr atmosphere are considerably higher than in N2 atmospherebecause of the involvement of liquid silicon as an intermediatephase. The overall reaction between Si3N4 and TiC involves adirect chemical reaction at the reaction interface, and when thereaction product layers cover the particles, reactions arecontrolled by the diffusion of carbon and nitrogen atomsthough the reaction product layers.

The kinetics of interactions between silicon nitride andtitanium carbide was analysed in detail, resulting in acomplex and lengthy mathematical model involvingcontracting-volume model equations as well as non-steady-state diffusion equations. The details of the kinetic modellingare beyond the scope and subject of this paper. However, itcan be mentioned that the effective nitrogen diffusioncoefficient was found to change between 2.28×10-13 and6.29×10-14 cm2/s. The apparent activation energy forreactions under nitrogen atmosphere was 495.5 kJ/mol. Thespecific rate constant for reactions under argon atmospherewas calculated to change from 1.45×10-7 to 8.96×10-8 cm/s.The apparent activation energy was 432.0 kJ/mol.

BALDONI, J.G. and BULJAN, S.T. 1988. Ceramics for machining. Ceramic Bulletin,vol. 67, no. 2. pp. 381–387.

BULJAN, S.T. and ZILBERSTEIN, G. 1987. Microstructure development in Si3N4based composites. Material Research Society Symposium, vol. 78. pp. 273–281.

DUWEZ, P. and ODELL, F. 1950. Phase relationships in the binary systems ofnitrides, carbides of zirconium, columbium, titanium, and vanadium.Journal of the Electrochemical Society, vol. 97, no. 10. pp. 299–304.

GNESIN, G.G., OSIPOVA, I.I., YAROSHENKO, V.P., and RONTAL, C. 1978. Optimizationof the properties of a tool material based on silicon nitride. Journal ofMetallurgical Ceramics, vol. 17, no. 2. pp. 124–127.

GOLDSCHMIDT, H.J. 1967. Interstitial Alloys. Butterworth, London.

GOVILA, R.K. 1985. Strength characterization of yttria-doped sintered siliconnitride. Journal of Material Science, vol. 20. pp. 4345–4353.

JACK, K.H. 1976. Sialons and related nitrogen ceramics. Journal of MaterialScience, vol. 11. pp. 1135–1158.

KRIZ, K. 1983. The fracture behavior of hot-pressed silicon nitride betweenroom temperature and 1400°C. Progress in Nitrogen Ceramics. pp. 523–28.

MAH, T., MENDIRATTA, M.G., and LIPSITT, H.A. 1981. Fracture toughness andstrength of Si3N4-TiC composite. Ceramic Bulletin, vol. 60, no. 11. pp. 1229–1240.

Poster, H. 1988. Titanium-carbonitride-based hard alloys for cutting tools.Material Science Engineering, vol. A105/106. pp. 401–409.

SMITH, J.T. and QUACKENBUSH, C.L. 1980. Phase effects in Si3N4 containing Y2O3or CeO2. Bulletin of the American Ceramic Society, vol. 59, no. 5. pp. 529–537.

ZILBERSTEIN, G. and BULJAN, S.T. 1984. Characterization of matrix reactions inSi3N4-TiC composites. Advances in Materials Characterization II, MaterialScience Research. New York College of Ceramics, Alfred, New York. Vol.17. pp. 389–401. ◆

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Environmental pollution is better preventedthan remediated, but most often prevention isdifficult. The industrial revolution has hadadverse consequences as well as benefits. Forexample, countries with past and currentmining activities are facing challenges ofenvironmental pollution due to acid minedrainage (AMD). The mining sector in SouthAfrica is one of the main driving forces of thecountry’s economy. Despite the positivebenefits, the serious impact of miningactivities on the environment resulting fromAMD cannot be over-emphasized (Hughes andGray 2013). Acid mine drainage hassignificant effects on environmental sustain-ability and water security (Evangelou, 1998).

AMD is produced by oxidation of sulphideminerals, mostly iron sulphides. This could benatural through the breaking down ofsulphides by bacteria, as well as throughanthropogenic activity, which is mining (Akciland Koldas, 2006). Oxidation of sulphidesproduces sulphuric acid, which in turn leachesout a range of metals from rock and othermetal-containing materials. This makes AMDpotentially dangerous to the environment,since is not only highly acidic, but alsocontains high metal concentrations (Singh,1987).

Research and development has beenchannelled towards source control andmitigation of AMD. Since oxygen and waterare required for the formation of AMD, sourcecontrol is targeted at preventing oxygen and/orwater from contacting the sulphide-bearingrock so as to prevent oxidation reactions fromproducing AMD (Kuyucak 2002; Johnson andHallberg, 2005; Luptakova et al., 2010;Egiebor and Oni, 2007). Preventing theformation and migration of AMD from itssource is not easy. Thus, research activities arenow focusing on collection, treatment, anddischarge of treated AMD. Treatmenttechniques can be divided into two categories:active and passive treatments (Johnson andHallberg 2005). This has been discussedextensively by many authors (Moses et al.,1987; Skousen et al., 1998; Johnson andHallberg, 2005; Kalin et al., 2006; Egiebor andOni 2007; Rötting et al., 2011). These days,various methods are employed for thetreatment of AMD. Lime (Ca(OH)2 or limestone(CaCO3) treatment is carried out to precipitatethe sulphate as gypsum and heavy metals as

Polyethersulphone-sodalite (PES-SOD)mixed-matrix membranes: prospects foracid mine drainage (AMD) treatmentby M.O. Daramola*, B. Silinda*, S. Masondo*, and O.O. Oluwasina*†

This article presents the outcome of a preliminary investigation theapplication of polyethersulphone (PES)-sodalite (SOD) mixed-matrixmembranes for acid mine drainage (AMD) treatment. PES-SOD membranesloaded with different amounts of SOD particles were fabricated using thephase inversion method, and evaluated for AMD treatment. Themorphology, phase purity, and surface properties of the SOD particles andthe membrane were checked using scanning electron microscopy (SEM),X-ray diffraction (XRD) and Fourier transform infrared (FTIR)spectroscopy, respectively. In addition, the mechanical strength of themembranes was evaluated using a texture analyser. Separationperformance (metal ion rejection) of the membranes and the effect of SODloading on the membrane performance during AMD treatment were alsostudied. The cations in the AMD (feed stream) and the permeate streamwere determined quantitatively using atomic absorption spectropho-tometry (AAS). The results of the investigation reveal that mechanicalstrength (Young’s modulus and tensile strength) of the membrane wasenhanced at increasing SOD loading. In addition, the membrane fluxincreased at increasing SOD loadings and the selectivity of the membranetowards Mn2+, Pb2+, Cu2+, Al3+, and Mg2+ also increased. The highestmembrane rejection of 57.44% was recorded for Pb2+, and the membranedisplayed a rejection of 6% towards Mn2+. All the PES-SOD membranesdisplayed better performance compared to an equivalent unloaded PESmembrane. As far as we know, this is the first report on the application ofPES-SOD mixed-matrix membranes to AMD treatment. However,optimization of the synthesis protocol and operational conditions isneeded to improve the performance of the membrane.

mixed matrix membranes, polyether sulphone, acid mine drainage,sodalite.

* School of Chemical and Metallurgical Engineering,Faculty of Engineering and the Built Environment,University of the Witwatersrand, Wits 2050,Johannesburg, South Africa.

† Department of Chemistry, Federal University ofTechnology, Akure, Nigeria.

© The Southern African Institute of Mining andMetallurgy, 2015. ISSN 2225-6253. Paper receivedMay 2015 and revised paper received Aug. 2015.

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Polyethersulphone-sodalite (PES-SOD) mixed-matrix membranes

hydroxides (Lyew et al., 1994; Hedin et al., 1994; Dempseyand Jeon, 2001; Sibrell and Watten, 2003; Santomartino andWebb, 2007). This has a disadvantage because of the greatquantities of gypsum sludge contaminated with metals thatare produced, and the high operating costs for disposal(Johnson and Hallberg, 2005). Another method that iscommonly used is two-step neutralization and ferriteformation, in which magnesium oxide or calcium carbonate isused for the first neutralization step to raise the pH to around4.8 to produce low-solubility heavy metal hydroxide sludge(Igarashi et al., 2006; Herrera et al., 2007). The second stageemploys sodium hydroxide to bring the pH to 8.5 toprecipitate ferrous and ferric hydroxides together with theremaining heavy metals (Al-Zoubi et al., 2010). Biologicaltreatment, which involves the use of sulphate-reducingbacteria, removes metals from AMD. This involves the use ofvarious carbon-containing substances (such as manure,wood chips, food waste) to reduce sulphate to sulphide andform a metal sulphide precipitate (Tuttle et al., 1969; Wakaoet al., 1979; Wildeman and Laudon, 1989; Ueki, 1991;Dvorak et al., 1992). The addition of the organic materialsgenerates hydrogen sulphide which elevates the reactiontemperature, which in turn decreases the effectiveness of themethod (Dvorak et al., 1992; Barnes et al., 1992).Furthermore, cation exchange processes have been proposedfor the removal of toxic metals from AMD. However, theoperating cost of the process is higher than the value of themetals recovered, and the exchange technology cannot copewell with the vast volumes of AMD discharge (Riveros, 2004;Al-Zoubi et al., 2010).

Recently, the application of membranes to treat AMD byselectively separating the heavy metals has been proposedand tested (Al-Zoubi et al., 2010; Jacangelo et al., 1997; Hilalet al., 2007; Escobar et al., 2000). A membrane is a barrierthat selectively allows the desired molecule to permeate whileundesirable molecules are retained (see Daramola et al.,2012, 2010 for detailed information on membranes and theirclassifications). Separation of mixtures by membranes can becarried out more efficiently and at lower energy consumptioncompared to distillation columns or absorbers (Ulbricht,2006; Daramola et al., 2012). In addition, membranetechnology is highly flexible, and the process can be adaptedin response to changes in volumes and concentration of themixture to be separated (Ulbricht, 2006). Furthermore,application of membrane systems in AMD treatment couldreduce the usage of chemicals and sludge production, therebymaking the treatment process environmentally benign. In thestudy by Al-Zoubi et al. (2010), three commercialmembranes, namely nanofiltration (NF), ultrafiltration (UF),and reverse osmosis (RO) membranes, were tested for AMDtreatment and the results yielded about 98% metal ionsrejection. However, for effective treatment of AMD for safedisposal using the aforementioned membranes, two or threestages involving two or three of the membranes would berequired, translating into additional capital and operatingcosts. To avoid this situation, a single-stage treatment ofAMD using mixed matrix membranes is proposed in thisarticle.

Mixed matrix membranes (MMMs) are compositemembranes containing zeolite crystals within the matrix ofthe polymer membranes. The presence of crystals within the

polymer chains improves separation performance, mechanicalstrength, and thermal stability of polymeric membranes.Advantages of MMMs over pure polymeric membranesinclude desirable mechanical properties, economical process-ability, unique structure of the dispersed inorganic phase,and good surface chemistry. However, the chemical structureof the inorganic fillers, type of inorganic fillers, and surfacechemistry are mitigating factors to obtaining high-qualityMMMs (Vu and Koros, 2003). In this study, synthesis andperformance evaluation of poyethersulphone(PES)-sodalitemixed matrix membranes for AMD treatment are reported.Sodalites are zeolites possessing a framework with cubicsymmetry structure, consisting of vertex linking of AlO4 andSiO4 into four- and six-membered oxygen rings (Breck,1974). Different types of sodalite can be synthesized fordifferent applications because they can accommodate a widerange of cations as a result of framework flexibility (Breck,1974). This could be exploited in the treatment of AMD, sinceAMD consists of dissolved substances (e.g. heavy metals)that are cationic or anionic in nature. Therefore, the sodaliteparticles could accommodate these substances duringselective treatment of AMD.

In a recent study, the separation performance ofsupported sodalite/ceramic membrane for seawater desali-nation was reported and ultra-pure water was produced fromseawater (Khajavi et al., 2010). Considering the outstandingperformance of this membrane for water treatment (Khajaviet al., 2010, 2007, 2008), it is expected that using sodalite(SOD) as fillers in PES to fabricate PES-SOD mixed matrixmembranes might result in a membrane with reasonableperformance, in terms of water fluxes and selectivity, forAMD treatment. Against this background, the results of thepreliminary investigation on the synthesis and application ofPES-SOD mixed matrix membranes for acid mine drainagetreatment are documented in this article.

Solvent (N,N-dimethylacetamide, 97%), polyethersulphone(PES), sodium silicate, sodium aluminate, and sodiumhydroxide were purchased from Sigma-Aldrich South Africa.Deionized water was prepared in-house. AMD samples weredirectly sourced from a small stream at the mine dumps inDobsonville in Gauteng Province, South Africa. All chemicalswere used as supplied without any further purification.

Hydroxysodalite (SOD) crystals were prepared viahydrothermal synthesis using sodium metasilicate, sodiumhydroxide pellets, anhydrous sodium aluminate, anddeionized water. These materials were mixed together in apolytetrafluoroethylene (PTFE) bottle and stirred for 1 houron a magnetic stirrer to yield a homogeneous mixture ofmolar composition ratio 5SiO2:Al2O3:50Na2O:1005H2O.Approximately 45 mL (or 48 g) of the vigorously mixedprecursor solution was poured into a Teflon-lined stainlesssteel autoclave and subjected to hydrothermal synthesis at413 K for 3.5 hours as described by Khajavi et al. (2010). Atthe end of the hydrothermal synthesis, the as-prepared SODcrystals were washed thoroughly with deionized water until

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the pH of the water was neutral. The washed crystalscollected on filter paper were dried overnight at 373 K in anoven.

A homogeneous mixture for the fabrication of eachmembrane was prepared by measuring specific amounts ofSOD crystals, polymer, and solvent with the ratio of SOD/PESto solvent in the mixture maintained at 1:9 throughout thesyntheses. The amount of the PES was kept at 0.40 gthroughout while the quantities of SOD particles and solventwere varied. Consequently, the weight percentages of theSOD crystals in the synthesized PES-SOD membranes were 5wt.%, 10 wt.%, and 15 wt.%. Membranes were fabricated byhand-casting the homogeneous mixture on a glass plateusing ‘DR BLADE’. Reproducibility of synthesis was ensuredby fabricating two batches under the same conditions, but atdifferent times and locations. In addition, pure PESmembrane (with 0 wt.% SOD) was synthesized forcomparison. Figure 1 depicts the steps involved in thesynthesis of the membranes.

The morphology and crystallinity of the synthesized SODcrystals were checked with scanning electron microscopy(SEM) using energy-dispersive X-ray spectroscopy (EDS)(Phillips XL 20), and X-ray diffractometry (XRD) (Bruker D8advance X-ray diffractometer) using CoKα radiation(λ=0.179 nm) at a scan rate of 0.25 seconds per step and astep size of 0.02°, respectively. Further confirmation of thepurity of the SOD crystals was obtained using Fouriertransform infrared (FTIR) spectroscopy, conducted with aBruker IFS spectrometer using KBr pellets as background.

Furthermore, the morphology of the fabricated mixed matrixmembranes was examined using SEM.

The performance of the membranes during AMD treatmentwas evaluated using a cross-filtration set-up depicted inFigure 2. Filtration tests were conducted at a feedtemperature of 298 K and a pressure of 1.1 bar, using themembrane of effective permeation area 45 cm2. Atomicabsorption spectrophotometry (AAS) was used to determinethe concentration of various metal ions in the AMD beforetreatment (feed stream) and after treatment (permeate andretentate streams). The concentration of the metal ions in rawAMD as per the AAS analysis is summarized in Table I. ThepH of the raw AMD obtained from the pH meter (model: HI2550 pH/ORP and EC/TDS/NaCl meter) was 2.28. Themembrane flux and the rejection (expressed in percentage) ofthe metal ions were obtained using Equation [1] andEquation [2]), respectively:

[1]

where Qp is the permeate mass flow rate (g/min), Jp is thepermeate flux (g.cm-2.min-1), and A is the effectivemembrane area (cm2).

[2]

where Ri is the percentage rejection of component i (%), andCf and Cp are the concentrations of component i in the feedand permeate streams (mg/L), respectively.


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The morphology of the synthesized particles is shown in theSEM image in Figure 3(a). Figure 3(b) and Figure 3(c)confirm the crystallinity and the purity of the synthesizedSOD crystals. The typical cubic shape of the SOD crystal isvisible in Figure 3(a), confirming the formation of SODcrystals during the synthesis. Other morphological shapessuch as nano-rod crystals were observed alongside the cubicSOD crystals in Figure 3(a). The same observation has beenreported in the literature (Kundu et al., 2010). Figure 3(b)reveals the formation of pure SOD crystals when compared tostandards developed by the Joint Committee on PowderDiffraction Standards (http://www.icdd.com), and the EDSanalysis of the SOD crystals showed a Si/Al ratio of 1–1.5,indicating a SOD framework. The FTIR patterns depicted inFigure 3(c) confirm the appearance of all characteristicvibrational bands of SOD crystals. The strong broad bandcentred at approximately 1000 cm-1 could be attributed to theasymmetric stretching vibration of T-O-T (T=Si, Al). Thesymmetric stretching vibration of T-O-T is vividly shownaround 740 and 660 cm-1. The results obtained from the FTIRanalysis of the SOD are consistent with the literature (Yao etal., 2006; Breck, 1974).

Figure 4 shows that SOD crystals were well distributed withinthe matrix of the polymer and that the ratio of the fractionalfree volume (FFV) of the polymer to the amount of sodaliteparticles within the polymer matrix decreased at increasingSOD loading. The observed difference between the loadedmembranes and the unloaded polymeric membrane can beseen by comparing Figure 4(a) with Figures 4(b)-(d). Thepresence of embedded SOD is clear from Figure 4(b)–Figure4(d), while there are no SOD particles in Figure 4(a). Thepresence of embedded SOD crystals in the PES confirmssuccessful fabrication of a PES-SOD mixed matrix membrane.The results of the mechanical property evaluation using aTA.XT Plus texture analyser at ambient temperature aredepicted in Figure 5. The tensile strength and the Young’smodulus of the synthesized membranes increased withincreasing SOD loading. This is consistent with the literature(Shen and Lua, 2012). The 15 wt.% loaded membranedisplayed the largest tensile strength of 10.62 MPa, an

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Cation Concentration (mg.L-1)pH= 2.28

Cu2+ 15.98Zn2+ 86.47Fe3+ 833.0Pb2+ 4.300Mn2+ 51.58Al3+ 1370Mg2+ 848.8

increase of about 213% compared to that of the PESmembrane (0 wt.% SOD loaded membrane). This observationfurther confirms the enhancement of the mechanical strengthof polymer membranes with the addition of fillers, and theincrease in strength with increasing filler loading (Wei et al.,2014). A slight increase in the Young’s modulus for 15 wt.%SOD loaded membrane compared to those for 5 wt.% and 10wt.% loaded membranes could be attributed to the ineffectivedispersion method adopted in the synthesis of themembranes. At higher particle loadings, agglomeration of theparticles may occur within the polymer matrix, causing aslight decrease in the Young’s modulus (Wei et al., 2014;Shen and Lua, 2012; Yu et al., 2013). However, this could beavoided if an effective dispersion method is used for thesynthesis of the membranes (Daramola et al., n.d.).

The AMD sample contained high concentrations of iron,aluminium, and magnesium ions, and moderate concen-trations of copper (Cu2+), zinc (Zn2+), lead (Pb2+), andmanganese (Mn2+) ions (see Table I). The high Fe3+ concen-tration could be attributed to continuous oxidation of Fe2+ to(Fe3+) as a result of a pH lower than 3 (Stumm and Morgan,1996). The AMD sample was considered hard since theconcentration of magnesium ions (848.78 mg/L) was greaterthan 120 mg/L (Al-Zoubi, et al., 2010).

The performance of each membrane was evaluated at apump speed of 12 revolutions per second. The concentrationsof metal ions and the pH of the permeate sample from eachmembrane were determined using AAS and a pH meter,respectively. Figure 6 shows the pH results of the permeatesample for each membrane after the treatment. A smallincrease in the pH from 2.28 for the feed sample to 2.50

(about 9.65% increase) was observed for the permeatesamples from the four membranes after the treatment. Thesmall change in the pH could be attributed to a smallerrejection of Fe3+ during the AMD treatment, because thepresence of Fe3+ lowers pH (Stumm and Morgan, 1996), anda higher rejection of Fe3+ is expected to increase the pH. In


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addition, an increase in the pH was observed at increasingSOD loading, implying that the performance of the PES-SODmembranes was enhanced with greater SOD loading.

Figure 7 shows that the permeate flux of the membranesincreased at increasing SOD loading (0 wt.% to 15 wt.%loading), reached a maximum of 1.85 g.cm-2.min-1 at 10wt.% loading, and then decreased to 1.43 g.cm-2.min-1 at 15wt.% loading. The observed increase in the membrane flux ofthe PES-SOD membranes when compared to that of the PES(0 wt.% loading) membrane could be attributed to thepresence of the SOD crystals and the hydrophilic nature of thecrystals. In addition, the kinetic diameter of water molecules(2.65 Å) and the average cage dimension of the SOD particle(2.6 Å) are comparable, implying that the SOD particlesprovide additional permeation channels for the watermolecules in the PES-SOD when compared to the membraneflux of the unloaded PES membrane.

The water transport mechanism in porous hydrophilicmembranes has been described by a sorption-diffusionmechanism and preferential sorption capillary flow (PSCF)model (Sourirajan, 1963). According to the sorption-diffusionmechanism, water molecules preferentially adsorb to thehydrophilic membrane surface, diffuse through themembrane pores, and desorb from the membrane. The PSCFmodel describes transport of water through such membranesas occurring by hydrogen bonding, during which watermolecules are attracted by the hydrogen bonds within themembrane and permeate through the membrane pores.Indeed, the separation efficiency of membranes depends ontheir surface properties (hydrophilicity or hydrophobicity)and pore dimensions (with respect to the molecular size ofthe adsorbates). The permeation of water molecules throughthe synthesized PES-SOD membranes is therefore expected tobe governed by the PSCF model because cages of SODcrystals are occluded with water, indicating that the transportof water molecules through the crystals could occur byhydrogen bonding. On the other hand, the observed decreasein the membrane flux at higher (15 wt.%) SOD loading couldbe attributed to membrane fouling due to the retention ofincreased numbers of particles from the AMD. However, it isnoteworthy to mention that the AMD sample was pre-treatedto remove the suspended particles before the filtration tests.Interestingly, the 15 wt.% loaded membrane did not lose itsselectivity, indicating few or no defects in the membrane.

Furthermore, the performance of the PES-SODmembranes was evaluated using selectivity of the membraneto the metal ions. Figure 8 depicts the percentage rejection ofeach metal ion by the membranes as a function of the SODloading. Lead (Pb2+) was the most rejected of all the metalions with a maximum rejection of 57.44%. This is expectedbecause the kinetic diameter of Pb2+ is 2.66 Å (Salam et al.,2012) and the average cage dimension of the SOD particles is2.6 Å (Breytenbach et al., 2007). Therefore, more Pb2+ wasretained by the membrane, thereby resulting in highselectivity of the membrane for Pb2+. Rejection of magnesium(Mg2+) increased from about 20% to about 50% withincreasing SOD loading. However, to soften the AMD, ahigher rejection of Mg2+ is required. Mn2+ was the leastrejected metal ion with a rejection from 1% to 6%. Themaximum percentage Cu2+ rejection of 17.6% displayed bythe membranes was not very encouraging. This performancecould be attributed to the smaller kinetic size of the Cu2+

(about 1.44 Å) compared to the average pore dimension ofSOD crystals (Breytenbach et al., 2007). Cu2+ could be easilyfiltered through the embedded SOD particles. It is evidentfrom the results that none of the metals ions in the AMDsample was well rejected with the synthesized membranes.However, modifications to the membranes by functionalizingthe SOD particles and optimizing the synthesis protocol coulddramatically enhance the performance of the PES-SODmembranes. Additionally, process conditions during thetreatment of AMD with the membranes could be optimized toenhance the flux and selectivity of the membranes.

Results of a preliminary investigation of the application ofPES-SOD mixed matrix membranes to AMD treatment arereported for the first time. The synthesis protocol adoptedresulted in the fabrication of selective and reproducible PES-SOD mixed matrix membranes. Three different PES-SODmixed matrix membranes were fabricated with different SODloadings, as well as a pure polymeric membrane forcomparison. The experimental results showed that theperformance of a pure polymeric membrane (selectivity andflux) is enhanced by loading SOD crystals within the matrixof the PES polymer. Results of the performance evaluation of

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the membranes for AMD treatment revealed the best waterflux at 10 wt.% SOD loading and a pump speed of 12revolutions per second. The PES-SOD loaded with 15 wt.%SOD crystals displayed the best selectivity towards Pb2+

(57.44% rejection). The results from this study have shownthe potential for application of PES-SOD membranes in thetreatment of AMD. However, optimization of the synthesisprotocol for the fabrication of the membrane and processconditions might be required to enhance the performance ofthe membranes for AMD treatment. Nevertheless, the resultsdocumented in this article could pave the way for furtherresearch and development in this area.

M.O.D. acknowledges Professor F. Kapteijn and Professor J.Gascon of the Delft University of Technology, TheNetherlands, for the opportunity to gain from their wealth ofexperience in the membrane field. The authors alsoacknowledge Dr D. Nkazi for assisting with the collection ofthe AMD sample. This work emanated from the results of the4th year BSc (Eng) chemical engineering research projectconducted by BS and SM.

AKCIL, A. and KOLDAS, S. 2006. Acid mine drainage (AMD): causes, treatmentand case studies. Journal of Cleaner Production, vol. 14. pp. 1139–1145.

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AL-ZOUBI, H., STEINBERGER, P., PELZ, W., HASENEDER, R., and HARTEL, G. 2010.Optimisation study for treatment of acid mine drainage using membranetechnology. Separation Science and Technology, vol. 45, no. 14. pp. 2004–2016.

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BREYTENBACH, J.C., JACO ZAHA, J., KRIEG, H.M., and VAN NIEKERK, A. 2007. Directcrystallisation of a hydroxy sodalite membrane without seeding using aconventional oven. Journal of Membrane Science, vol. 300. pp. 156–164.

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Between 1960 and the mid-1990s theLangelier Saturation Index (LSI) (Equation[1]) (Langelier, 1936) attracted adversecommentary from the municipal potable watercommunity. It was stated that the LSI had nocorrelation with corrosion rate (Stumm, 1960;Larson and Sollo, 1967; Singley, 1981;Schock, 1984; Piron et al., 1986; Pisigan andSingley, 1987), and based on the empiricalevidence it was suggested that the use of theLSI for corrosion prediction should beabandoned (AWWARF and DVGW, 1996). Thesame sentiment applied to the Ryznar StabilityIndex (RSI) (Ryznar, 1944) (Equation [2])and the various other ’corrosion predictionindices’ that emerged during this period andthat were also grounded on the same principle:

➤ Momentary Excess (ME) (Dye, 1958)➤ Calcium Carbonate Precipitation Potential

(CCPP) (Merrill and Sanks, 1978) ➤ Aggressiveness Index (AI) (Millette et

al., 1980)➤ Driving Force Index (DFI) (Rossum and

Merrill, 1983).

LSI (Langelier Saturation Index) = pH - pHs [1]

where the variables and their range of applica-bility are as follows:

pH: measured pH (7.0–9.5), temperature:25–80°C, total dissolved solids <800 mg/l.pHs: the pH at which the cooling water willbe saturated. This value is calculated basedon the solubility product for calcite, thesecond dissociation constant for carbonicacid and calcium concentrations, and totalalkalinity of the cooling waterPositive LSI values indicate ‘oversatu-ration’ and a tendency for a protectiveCaCO3 coating to form, whereas negativevalues indicate the tendency to dissolve anexisting CaCO3 coating.

RSI (Ryznar Stability Index) = 2(pHs) - pH [2]

PSI (Puckorius Scaling Index) = 2(pHeq) - pH [3]

Puckorius uses an equilibrium pH for thisindex rather than the actual cooling waterpH. The index applies for temperatures upto 93°C.

pHeq = 1.465 × log10 (total alkalinity) +4.54 [4]

Total alkalinity: mg/l CaCO3.RSI or PSI values 6 and higher indicateincreasingly severe corrosive tendencies,whereas values 6 and lower indicate moreCaCO3 scaling tendencies.The PSI (Puckorius and Brooke, 1990),

calculated using Equations [3] and [4], is arefinement of the RSI, in which an empiricalalkalinity function is derived to modify thecalculated pH of saturation for calciumcarbonate (pHs). In large industrial and powerstation cooling systems, either the LSI of PSI isstill used to control acid feed or the cycles ofconcentration for calcium carbonate scale

The accuracy of calcium-carbonate-based saturation indices in predictingthe corrosivity of hot brackish watertowards mild steelby A. Palazzo*, J. van der Merwe†, and G. Combrink‡

Industry has always relied on water’s inherent ability to inhibit mild steelcorrosion by virtue of its levels of calcium hardness and total alkalinity.This research seeks to verify the application of this principle to brackishwater used in industrial systems at moderately elevated temperatures. Abrief review is first given of the conventional calcium-carbonate-basedscale or corrosion predictive indices. Laboratory corrosion tests wereperformed at various levels of calcium hardness and total alkalinity,resulting in the generation of an empirically derived nonlinear regressionmodel. The newly developed model and the existing indices were thencompared statistically in predicting the corrosivity of brackish water incontact with mild steel at 45ºC. The accuracy, broader application, andrelevance of the indices are also discussed.

saline water, brackish water, cooling, corrosion prediction, computermodelling, Langelier Saturation Index, Ryznar Stability Index, mild steel,calcium carbonate saturation.

* Buckman Africa (Pty) Ltd, Hammarsdale, SouthAfrica and part-time MSc student at the School ofChemical and Metallurgical Engineering, Faculty ofEngineering and the Built Environment, Universityof the Witwatersrand, Johannesburg, South Africa.

† University of the Witwatersrand, Johannesburg,South Africa .

‡ University of Johannesburg, South Africa.© The Southern African Institute of Mining and

Metallurgy, 2015. ISSN 2225-6253. Paper receivedJuly 2014 and revised paper received Aug. 2015.

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The accuracy of calcium-carbonate-based saturation indices

control. This supports their continued role in predicting theimpact of water-soluble species on industrial water systems.

Early research (Larson and Skold, 1957) confirmed thatthe precipitation/dissolution of calcium carbonate is not theonly water quality parameter relevant to the corrosion ofdistribution systems. Other factors such as the ratios ofanions, flow velocity, pH, and calcium concentration alsocontribute to corrosion rates, but perhaps the best researchedis the Larson and Skold Index, also known as the LarsonRatio (LR) (Larson and Skold, 1957, 1958) (Equation [5]).This index includes the corrosive effects attributable to thechloride and sulphate concentrations.

Larson-Skold Index, Larson ratio (LR) or CorrosivityIndex (CI) = ([Cl-] + [SO4

2-]) / ([HCO3-]) [5]

where[Cl-], [SO4

2-] and [HCO3-]: meq/litre of chloride, sulphate,

and total alkalinity respectively. The water studied approximated the quality of the GreatLakes waters of North America. The higher the index themore corrosive the water.Feigenbaum et al. (1978) demonstrated poor correlation

between the already-mentioned calcium-carbonate-basedindices and the saline waters of the Negev Desert, andtherefore developed an empirical index that included theeffect of calcium carbonate solubility and the ions of the LR.

The reported lack of a definite correlation between the LSIand corrosion rates evident in both the drinking waterindustry and laboratory-scale closed-loop experimentsprompted Pisigan and Singley (1984) to embark on a seriesof jar tests. The results of the laboratory tests permitted themto empirically derive a four-variable model (Equation [6])and an eight-variable model (Equation [7]) that couldaccount for 98% of the variations in corrosion rate under theexperimental conditions explored. The equations hypoth-esized indicated that the corrosion rate of mild steel was infact influenced by factors beyond just the precipitation ordissolution of calcium carbonate.

Pisigan and Singley 4-variable equation:

CR4 = ((TDS)0.253 (DO)0.820)/((10SI)0.0876 (Day)0.373) [6]

Pisigan and Singley 8-variable equation:

CR8 = (Cl)0.509 (SO4)0.0249(Alk)0.423(DO)0.780) /((Ca)0.676(β)0.0304(Day)0.381(10SI)0.107) [7]

whereTDS (total dissolved solids): mg/l, Ca (calcium): mg/l asCa, Mg (magnesium): mg/l as Mg, Na(sodium): mg/l asNa, Cl (chloride): mg/l as Cl, SO4 (sulphate): mg/l as SO4,Alk (alkalinity): mg/l as CaCO3, β (buffer capacity): mg/las CaCO3/pH, DO (dissolved oxygen): mg/l as O2.Pisigan and Singley’s eight-variable model (1984)

suggests that increasing chloride, sulphate, alkalinity, anddissolved oxygen levels would accelerate corrosion, whereasincreases in calcium concentration, buffer capacity, saturationindex, and exposure time would lead to decreasing corrosionrates. In this hypothetical equation, the alkalinity is declaredto accelerate rather than reduce corrosion, as is commonlyknown. The authors attributed this contradiction to theoverwhelming influence of the increased ionic strength overthe effect of alkalinity with increasing dosages of sodiumbicarbonate while attempting to raise the alkalinity during thelaboratory experiments.

The first use of the buffer capacity (β) appeared in theliterature pertaining to the subject of corrosion prediction inthe work by Stumm (1960). Laboratory tests with syntheticsolutions helped explain the mutual interaction of corrosion-stimulating and -inhibiting factors of natural waters, namely:pH, buffer capacity, CaCO3 deposition, and alkalinity. Thisstudy was thought to at least partially explain the increase incorrosion rates with increasing pH between the values of 7.0and 8.5.

Several studies found that as the pH approached 8.4,either from a higher or lower pH value, the corrosion rate ofcast iron increased with decreasing buffer intensity. It ispresumed that this effect occurs as a result of there beingfewer but larger cathodic and anodic areas, therebyencouraging the electrochemical cell (Stumm, 1960).

Based on the independent studies reported by Pisigan andSingley (1987) and Imran et al. (2005a), it was possible topropose a modified Larson ratio (LRM) that wouldcompensate for the increase in total dissolved solids with theincreasing alkalinity by including the sodium ion concen-tration.

Imran continued his work on potable water distributionsystems and published an article (Imran et al., 2005a) thatincluded a wider range of parameters in an empiricallyderived nonlinear model. The model is based on the changein apparent colour (ΔC in cpu) as a measure of corrosion indistribution lines, as it was found to be a reliable surrogatemeasurement of total iron. Calcium and pH were not deemedsignificant during the statistical modelling, because all testswere performed in waters stabilized for CaCO3 solubility.Alkalinity was the only variable that could be effectivelycontrolled by chemical addition.

In the arena of oilfield brines, where the high salinityaffects the ionic strength and influences the calciumcarbonate solubility, the Stiff-Davis Index (SDI) (Equation[8]) has been used (Stiff and Davis, 1952) in place of theLangelier Index. Waters with total dissolved solids levelshigher than 4000 mg/l require that the SDI is used.

SDI = pH - pCa- pAlk – K [8]

wherepH: pH measured, pCa = -log (Ca in mg/l as Ca2+), andpAlk = -log (M alkalinity in mg/l as CaCO3), K = constantbased on the total ionic strength and temperature.

Is (O & T scaling Index) = log (TCa Alk) + pH – 2.78 +1.143 × 10-2 T – 4.72 × 10-6 T2 – 4.37 × 10-5 P – 2.05 × I½ +0.727 × I [9]

whereI (ionic strength): moles/l, TCa (calcium): moles/l as Ca,Alk (alkalinity): moles/l as HCO3

-, T (temperature):⁰F, P(pressure): psi.As with the Langelier Saturation Index, positive SDI or Isvalues indicate ‘oversaturation’ and a tendency for aprotective CaCO3 coating to form, whereas negativevalues indicate the tendency to dissolve an existingCaCO3 coatingHigher CR values indicate higher corrosion rates in milsper year (mpy).The Stiff-Davis (Stiff and Davis, 1952) method is one of

the easiest ways to calculate calcium carbonate scalingtendencies (Calcite Saturation Index) in brines and it is valid

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for temperatures from 0–90°C and ionic strengths from 0–4.This index does not take into account the pressure andcarbon dioxide concentration. It requires that the pH ismeasured on a fresh sample to avoid inaccuracies. As ionicstrength and/or the temperature increase, so the K valuedecreases, resulting in a higher SDI, indicating a highercalcium carbonate scaling tendency. Higher concentrations ofcalcium or alkalinity would also lead to higher SDI values,also resulting in increased scaling tendencies. Calculating theSDI requires a calculation of the ionic strength, knowing thetemperature of the operation, and looking up the K value in aK versus ionic strength graph (Stiff and Davis, 1952).

The Oddo-Tomson (1982) method is an alternative indexapplicable to high ionic strength waters for predicting theformation of calcium carbonate and various sulphate scales.It is valid between temperatures of 0–200ºC, ionic strengthsof 0–4.0, and pressures of 1–1380 bar (0–20000 psig)(Equation [9]). The calculation was reported by Oddo andTomson (1982) to be accurate at high and low temperaturesand pressures. The calculation can be easily performed in thefield and is said to work well when applied to geopressuredwells.

The prediction of the corrosivity of undergroundminewaters towards mild steel was also explored by Whiteand Higginson (1985). It was reported that the corrosiontakes place under cathodic control, with the metal acting as asubstrate for the cathodic reaction. Thus the corrosivity ofminewaters is largely dependent upon on the oxygen concen-tration and the pH of the water.

In determining the relationship between the calcium hardnessand alkalinity and the corrosion rate of mild steel in brackishwater at elevated temperatures (35–45˚C), numerouslaboratory tests were conducted with synthetic solutions.

The main aim of the laboratory evaluation was todetermine the impacts of temperature (between 35˚C and45˚C), calcium hardness (between 50 mg/l and 100 mg/l asCa2+), and total alkalinity (between 55 and 220 mg/l asCaCO3) on the corrosivity of brackish water towards mildsteel. Thus, the limiting conditions for the applicability of thisstudy are waters having a quality range defined in Table I.

C1010 (mild steel) corrosion coupons were subjected tosynthetic test solutions (4000 ml) stirred at 100–110revolutions per minute (r/min) for 72 hours. The couponswere then removed, cleaned with a water wash to finger-

touch, followed by an ethanol wipe; and then oven-dried,weighed and the corrosion rates calculated based on theirweight loss. The methods followed were based on ASTMmethods:

➤ G31-72 (Reapproved 1999): Standard Practice forLaboratory Immersion Corrosion Testing of Metals

➤ G1-90 (Reapproved 1999: Standard Practice forPreparing, Cleaning, and Evaluating Corrosion TestSpecimens.

A Corrater® (Rohrback Cosasco) was used to measure thegeneral corrosion rate and imbalance (i.e. indicator of thetendency for localized corrosion). The test solutions were alsotested for their total iron concentrations and comparedagainst the coupon method and Corrater® readings. Each setof tests was performed in a batch of six tests in a ’LaboratoryScale and Corrosion Test Station’, a Buckman proprietarycorrosion testing device, over a period of three days (refer toFigures 1 and 2).

Each of the six stations has its dedicated 5-litre beakerand an overhead paddle stirrer, dedicated temperature probe,hot plate, three coupon holders, and a Corrater® probe

Table II lists the target calcium and total alkalinity concen-trations, the temperatures explored, and the total ironconcentrations of the test solutions. Table III summarizes thecorrosion coupon results and the Corrater® readings takenover the three days.

Figure 3 compares the mild steel coupon corrosion rates(mm/a) for the two positions, and Figure 4 provides a three-dimensional view of the correlations between the threecorrosion measurements: the average coupon corrosion rate,the average Corrater® general corrosion rate, and the totaliron concentrations.

Figure 5 reflects the impact of a 10ºC difference intemperature on the corrosion rates as well as the impact ofhigher and lower alkalinity. It includes the error bars basedon the maximum standard deviation – that is, a value of 0.07mm/a – for the entire set of coupon data recorded during the30 test runs.

Statistical correlations were performed between theaverage coupon corrosion rate and the various parameters


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pH 7.8 (6.0–8.1)Calcium (mg/l as Ca2+) 50–100 (49–97)Total alkalinity (mg/l as CaCO3) 55–220 (19–228)Magnesium (mg/l as Mg2+) 27.3 (22–30)Chloride (mg/l as Cl-) 750 (717–822)Sulphate (mg/l as SO42-) 1125 (1100–1400)Fluoride (mg/l as F-) 10 (8–10)


measured during the experiment. Statistically significantlinear model correlations, with a 95% confidence level, werefound between the average coupon corrosion rate and thefollowing parameters: the initial and final calcium concen-

trations, the initial total alkalinity, the average Corrater®

general corrosion rates, and the total iron levels. Inverserelationships were evident between the average couponcorrosion rate and the calcium and total alkalinity values,

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Run Target concentrations/conditions Total ironCalcium Total Temperature

alkalinitymg/l as Ca2+ mg/l as ºC mg/l as Fe3+

CaCO3 (total)1 50 55 45 6.42 50 82.5 45 3.93 50 110 45 4.34 50 165 45 2.95 50 220 45 2.76 50 110 35 4.07 62.5 55 45 6.18 62.5 82.5 45 3.59 62.5 110 45 3.010 62.5 165 45 2.111 62.5 220 45 2.012 62.5 110 35 4.313 75 55 45 1.714 75 82.5 45 1.415 75 110 45 1.216 75 165 45 0.817 75 220 45 1.418 75 110 35 1.819 87.5 55 45 3.320 87.5 82.5 45 0.521 87.5 110 45 2.922 87.5 165 45 1.423 87.5 220 45 0.724 87.5 110 35 2.025 100 55 45 2.826 100 82.5 45 0.427 100 110 45 2.028 100 165 45 0.029 100 220 45 0.030 100 110 35 36.4

whereas direct moderate correlations were noted between theaverage coupon rates and both the average Corrater® generalcorrosion rates and the total iron concentrations. The averageCorrater® general corrosion rates did not correlate well withthe total iron values.

Contour plots (Figures 6 to 9) were drawn to reveal thecombined effect of the calcium hardness and total alkalinityon the average coupon corrosion rate. The initial or finalcalcium concentrations and initial or final total alkalinityvalues were plotted against the average coupon rate.


1233 ▲

1 0.45 0.48 0.46 36.8 4.3 36.1 4.1 34 1.1 35.5 2.62 0.31 0.38 0.35 15.5 8.6 13.4 8.1 12.6 4.4 12.1 5.33 0.25 0.32 0.28 14 7.4 14.2 6.6 11.1 3.4 10.9 3.74 0.16 0.25 0.21 8.7 6.9 8.4 6.6 8.3 2.1 9.3 7.15 0.16 0.24 0.20 10.1 3.5 8.6 1.1 8.7 0.1 8.7 7.16 0.23 0.30 0.26 13 7.1 14.4 2.6 10.1 2.4 10.4 2.37 0.41 0.50 0.46 36.6 1.2 33.9 1.9 34.4 6.3 33.5 5.58 0.37 0.39 0.38 28.6 1.1 26.4 6.5 21.1 12.5 22.8 0.89 0.29 0.30 0.29 30.5 1.5 29.2 9.2 29.9 6.8 20.7 5.610 0.10 0.28 0.19 19.3 1.3 20.3 1.0 21.3 7.4 19.5 5.211 0.16 0.32 0.24 21.6 9.8 19.8 3.7 19.8 5.3 19.5 3.312 0.19 0.34 0.26 17.3 9.3 16.8 1.3 17.8 6.4 17.7 3.413 0.30 0.37 0.34 30.1 6.2 31.4 2.2 30.5 6.6 30.4 2.114 0.23 0.26 0.25 8.1 2.2 7.9 6.6 9.2 6.6 12.1 3.115 0.22 0.19 0.20 28.6 2.2 29.6 3.1 31.4 6.6 32.4 3.816 0.21 0.14 0.18 25.7 6.2 28.2 4.4 30.4 6.2 33.4 9.817 0.22 0.25 0.24 31.4 2.9 30.4 13.3 30.1 8.6 33.4 6.718 0.15 0.25 0.20 38.4 6.2 37.4 9.6 39.4 6.7 38.9 1.119 0.24 0.34 0.29 12.6 1.1 10.1 3.4 11.4 2.2 14.4 6.620 0.21 0.23 0.22 15.4 1.8 14.1 0.3 14.9 1.0 15.2 2.221 0.13 0.16 0.15 9.8 3.4 10.7 6.1 10.4 0.9 8.1 0.922 0.17 0.22 0.20 9.4 0.6 8.3 1.7 7.6 0.8 7.7 1.323 0.21 0.29 0.25 12.2 0.1 10.0 0.9 10.6 2.6 9.5 0.224 0.14 0.16 0.15 22.4 0.8 18.8 0.7 19.0 1.0 16.7 1.525 0.23 0.26 0.24 9.9 3.3 8.9 1.1 6.4 2.2 - -26 0.13 0.13 0.13 4.7 2.2 5.4 0.1 4.6 3.2 - -27 0.14 0.14 0.14 8.4 0.2 8.2 3.5 7.6 4.4 - -28 0.19 0.22 0.21 5.2 0.9 4.4 2.6 4.1 0.2 - -29 0.33 0.37 0.35 7.7 0.4 7.9 1.1 8.6 2.6 - -30 0.61 0.69 0.65 4.4 10.9 13.6 0.4 15.6 5.5 - -


A nonlinear multivariate regression analysis wasconducted to predict the relationship between couponcorrosion rate and various predictors in order to determine

how the response variable changes as the particular predictorvariables change. This was done without taking into accountthe impact of the 10ºC temperature difference (refer toEquation [10]):

Corrosion (mm/a) = 4.58E-6 Ca2 - 8.85E-3 Ca + 4.64E-5 (Ca × Malk) - 9.30E-3 × M alk + 1.90E-5 M alk2 + 1.26 [10]

where Ca = mg/l calcium as Ca and M alk = mg/l totalalkalinity as CaCO3.Figure 10 serves to confirm the accuracy of the

empirically derived nonlinear regression equation bycomparing it to the laboratory coupon corrosion data. An R2

adjusted value of 90.06% was obtained. The graph alsoindicates where large residuals and an unusual resultoccurred, explicitly at the upper section of curve.

The empirically derived equation was then comparedstatistically against the predictive indices discussed in theliterature survey. This was performed by using the testsolution target values and the comparison performed at both35ºC and 45ºC. The results of the comparison are given inTable IV and shown by the scatter plot correlations in Figure11. The statistical analysis indicated that the calculated rate

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1234

had the statistically significant moderately strongrelationships at a 95% confidence level shown in Table V.

A contour plot (Figure 12) of the derived multivariatenonlinear regression equation (Equation [10]) was includedto facilitate a visual comparison with the contour plots of thelaboratory coupon corrosion data (Figures 6–9). Contourplots (Figures 12–19) of statistically significant indices takenfrom the literature, as per Table V, were also included forfurther comparisons.

In order to first determine the correlation between the twocoupon positions in the test vessel it was necessary tocompare their results by means of a paired t-test. The pairedt-test for the mean of coupon 1 versus the mean of coupon 2


1235 ▲

Ca -0.4080.093

TOT Alk (SGO) -0.3440.162

CR8 Corrosion In -0.0530.833

Buffer Capacity -0.3440.162

CR4 Corrosion In 0.5290.024

CCPP (mg/l) -0.2590.300

Is (Oddo &Tomson, 1982) -0.5360.022

Ionic Strength (M) -0.5310.023

(Stiff and Davis,1952) -0.5700.013

CaCO3 -0.1800.474

CaF2 0.1760.485

Langelier -0.5320.023

RSI 0.5260.025

PSI 0.5390.021

Larson Skold 0.5450.019

CaCO3 FIME -0.0380.880

Note: the top number is the Pearson coefficient of correlation, r. As a rule of thumb, r > 0.65 or R < 0.65 indicate correlation.The bottom number is the p-value. P-values ≤ 0.05 indicate correlationat the 95% confidence level.

Is(Oddo), Oddo-Tomson CR4, 4 variable model (Pisigan(1982) method and Singley, 1984)Ionic strength RSI, Ryznar Stability Index

(Ryznar, 1944)SDI, Stiff Davis Index PSI, Puckorius or Practical (Stiff and Davis, 1952) Scaling Index (Puckorius and

Brooke, 1990)LSI, Langelier Saturation Index LR, Larson Skold Index, also (Langelier, 1936) known as the Larson Ratio

(Larson and Skold, 1957, 1958).


▲

1236

showed that the two coupon positions were statisticallydifferent at a 95% confidence level. The two coupon positionsdid, however, demonstrate similar trends, as apparent inFigure 3; hence the average coupon rate was adopted as theresult for each test.

A comparison of the plots of the average coupon rateagainst either the average Corrater® readings or the testsolution total iron concentrations (Figure 4) demonstratedmoderate direct correlations. The strength and direction ofthese correlations therefore supported the use of the averagecoupon rate for the continued corrosion studies. There was,however, a substantial discrepancy between the coupon-based rates and the Corrater® readings, with the latterindicating rates that were approximately 54 times higher. Thefindings of this investigation were addressed by Van derMerwe and Palazzo (2015), and similar concerns over thelack of correlation between linear polarization resistanceprobe measurements and coupon immersion tests have alsorecently been investigated by Wu et al. (2015).

Figure 5 reflects the impact of a 10ºC difference intemperature, where the higher temperature produced higher

corrosion rates at the lower targeted calcium hardness valuesof 50 and 62.5 mg/l (as Ca). At the higher calcium hardnessvalues both temperatures resulted in similar corrosion rates.Figure 5 depicts the impact of different total alkalinities. It isapparent that higher alkalinity resulted in lower couponcorrosion rates, with the exception of the increased corrosionevident for the points corresponding to the combination of ahigh target calcium hardness (above 75 mg/l as Ca) and hightarget alkalinity (165 mg/l as CaCO3).

The contour plots (Figures 6 and 7) for the averagecoupon rate versus calcium and total alkalinity for thecorrosion tests performed at 35ºC demonstrated:

➤ Lowest corrosion rates at high calcium (>70 mg/l asCa) and high total alkalinity (>90 mg/l as CaCO3)

➤ Highest corrosion rates at high total alkalinity (>90mg/l as CaCO3) and low calcium (<60 mg/l as Ca).

The contour plots (Figures 8 and 9) for the averagecoupon rate versus calcium and total alkalinity for thecorrosion tests performed at 45ºC demonstrated:

➤ Lowest corrosion rates at:• High calcium (80–100 mg/l as Ca) and moderately

high total alkalinity (65–110 mg/l as CaCO3) • Moderate calcium (60–80 mg/l as Ca) and moderate

total alkalinity (150-200 mg/l as CaCO3➤ Highest corrosion rates at low total alkalinity (<50 mg/l

as CaCO3) and either low calcium (<50 mg/l as Ca) orhigh calcium (>85 mg/l as Ca).

The regions of either low or high corrosivity are similarfor both the lower temperature of 35ºC and highertemperature of 45ºC.

The empirically derived nonlinear regression equation,based on only the solution’s initial calcium and initial totalalkalinity, was confirmed to account for 90.06% of thevariations in the average corrosion coupon data.

Statistically significant moderately strong relationships,at a 95% confidence level, were evident between the derivednonlinear regression equation and the various establishedindices, namely: LSI, Langelier Saturation Index (Langelier,1936), RSI, Ryznar Stability Index (Ryznar, 1944), LR,Larson Skold Index also known as the Larson Ratio (Larsonand Skold, 1957, 1958), SDI, Stiff Davis Index (Stiff andDavis, 1952), Is (Oddo), Oddo-Tomson (1982) method, ionicstrength, CR4, four-variable model (Pisigan and Singley,1984), and PSI, Puckorius, or Practical Scaling Index(Puckorius and Brooke, 1990).

A comparison of the contour plot of the new model versusthose of other indices, for the set of target values consideredrevealed some subtle differences between them. One of themore obvious differences was the impact of the calciumconcentration on the corrosivity, as evident by the relativelysteeper diagonal contour lines for some of the indices, partic-ularly in the new model, LSI, RSI, and PSI (Figures 12, 16,17, and 18, respectively). As per the literature, it appears thata number of the authors included calcium in their empiricallyderived predictive models: LSI, RSI, SDI, and CCPP. The samecan be said of pH for the LSI, RSI, PSI, SDI, and Is indices.Linear regression analysis of the correlation between theaverage coupon corrosion rates and the various predictorsconfirmed the role of the initial pH and the initial calciumconcentration.


1237 ▲


Although the average coupon rate, the total iron concen-trations, and the Corrater® general corrosion rate readingsappeared closely related, it was possible to find statisticallysignificant linear correlations, at a 95% confidence level, onlybetween the average coupon rate and total iron concentrationas well as the average coupon rate and the Corrater® generalcorrosion readings.

It was also confirmed that raising the calcium hardnessand/or total alkalinity within the range of chemistriesexplored for the application of the brackish water in a coolingsystem does reduce mild steel corrosion. It did, however,become apparent that calcium carbonate saturation orsupersaturation can lead to precipitation, resulting in reducedlevels of calcium and alkalinity which in turn leads toincreased corrosion rates.

The empirically derived equation was at best capable ofonly moderately strong correlations with any of thenumerous calcium-carbonate-based models found in theliterature. A comparison of the formulae of the statisticallysignificant eight indices and a comparison to the remainingsix non-statistically significant and weakly correlated indicesrevealed that the latter six were linearly related to either thecalcium concentration or total alkalinity, whereas the formereight indices are a function of either the log or the inverse ofeither the calcium concentration and/or total alkalinity. Thenewly proposed empirically derived nonlinear regressionmodel differes from both sets of indices in that it is based ona quadratic equation incorporating both the calcium concen-tration as Ca2+ and total alkalinity in mg/l as CaCO3.

As stated in the introduction, it would be grosslyinaccurate to base the calculation of the corrosivity ofbrackish water solely on its calcium concentration, totalalkalinity, and temperature without giving any considerationto the many other factors or conditions prevailing in a typicalindustrial system. What is, however, apparent from thestudy, since it is based only on changes in the calciumhardness and total alkalinity, is that the empirically derivedmodel may prove more accurate than most of the existingcommonly found indices at estimating the corrosivity ofbrackish water, of similar characteristics to the chemistryexplored, on mild steel between 35 and 45ºC.

AWWARF and DVGW-TZW. 1996. Internal Corrosion of Water DistributionSystems. 2nd edn. American Water Works Association, Denver, CO. pp. 29–70.

DYE, J.F. 1958. Correlation of the two principle methods of calculating the threekinds of alkalinity. Journal of the American Water Works Association, vol.50, no. 6. pp. 801–820.

FEIGENBAUM, C., Gal-Or, L., and Yahalom, J. 1978. Scale protection criteria innatural waters. Corrosion, vol. 34, no. 4. pp. 133–137.

IMRAN, S.A., DIETZ, J.D., MUTOTI, G., TAYLOR, J.S., and RANDALL, A.A. 2005a.Modified Larsons ratio incorporating temperature, water age, andelectroneutrality effects on red water release. Canadian Journal ofEnvironmental Engineering, vol. 131, no. 11. pp. 1514–1520.

IMRAN, S.A., DIETZ, J.D., MUTOTI, G., TAYLOR, J.S., RANDALL, A.A., and COOPER, C.D.(2005b). Red water release in drinking water distribution systems. Journalof the American Water Works Association, vol. 97, no. 9. pp. 93–100.

LANGELIER, W.F. 1936. The analytical control of anti-corrosion water treatment.Journal of the American Water Works Association, vol. 28, no. 10. pp. 1500–1521.

LARSON, T.E. and SKOLD, R.V. 1957. Corrosion and tuberculation of cast iron.Journal of the American Water Works Association, vol. 49, no. 10. pp. 1294–1302.

LARSON, T.E. and SKOLD, R.V. 1958. Laboratory studies relating mineral waterquality of water to corrosion of steel and cast iron. Corrosion, vol. 14. pp. 285–288.

LARSON, T.E. and SOLLO Jr., F.W. 1967. Loss in water main carrying capacity.Journal of the American Water Works Association, vol. 59, no. 12. pp. 1565–1572.

MERRILL, D.T. and SANKS, R.L. 1978. Corrosion control by deposition of CaCO3

films: Part 3, a practical approach for plant operators. Journal of theAmerican Water Works Association, vol. 70, no. 1. pp. 12–18.

MILLETTE, J.R., HAMMONDS, A.F., PANSING, F.J., HANSEN, C.E., and CLARK, P.J. 1980.Aggressive water: assessing the extent of the problem. Journal of theAmerican Water Works Association, vol. 72, no. 5. pp. 262–266.

ODDO, J.E. and TOMSON, M.B. 1982. Simplified calculation of CaCO3 saturation athigh temperatures and pressures in brine solutions. Journal of PetroleumTechnology, July. pp. 1583–1590.

PIRON, D.L., DESJARDINS, R., BRIERE, F., and ISMAEL, M. 1986. Corrosion rate ofcast iron and copper pipe by drinking water. Corrosion Monitoring inIndustrial Plants Using Nondestructive Testing and ElectrochemicalMethods, ASTM STP 908. Morgan, G.C. and Labine, P. (eds). AmericanSociety for Testing and Materials, Philadelphia.

PISIGAN Jr., R.A. and SINGLEY, J.E. 1987. Influence of buffer capacity, chlorineresidual, and flow rate on corrosion of mild steel and copper. Journal ofthe American Water Works Association, vol. 79, no. 2. pp. 62–70.

PISIGAN, R.A. and SINGLEY, J. E. 1984. Evaluation of the corrosivity using theLangelier Index and relative corrosion rate models. Material Performance,vol. 24, no. 4. pp. 26–36.

PUCKORIUS, P.R. and BROOKE, J.M. 1991. A new practical index for calciumcarbonate scale prediction in cooling tower systems. Corrosion, vol. 47, no.4. pp. 280–284.

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VAN DER MERWE, J.W., and PALAZZO, A. 2015. Investigating the correlationbetween linear polarization resistance corrosion monitoring probereadings and immersion test results for typical cooling water conditions.Journal of the Southern African Institute of Mining and Metallurgy, vol.115, no. 3. pp. 173–178.

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Nickel deposits can be classified into two maingroups: laterites and sulphides. Even thoughnearly 70% of nickel resources are containedin laterites, the bulk of production comes fromsulphides due to the complex and high-costprocessing required for laterite. The sulphideores are universally treated by flotation, andthe major gangue components include a hostof MgO minerals, such as serpentine.

MgO minerals (e.g. serpentines) breakreadily. Thus grinding produces fines orslimes, particles less than approximately 10µm. These gangue slimes can interfere withflotation by forming a coating on thepentlandite surfaces (Edwards et al., 1980;Pietrobon et al., 1997; Wellham et al., 1992).This has two consequences: dilution of theconcentrate when pentlandite partially coatedwith fines remains floatable, and loss ofpentlandite when extensively coatedpentlandite becomes hydrophilic (Learmontand Iwasaki, 1984; Trahar, 1981). In order toimprove the flotation of the pentlandite,sodium hexametaphosphate, sodium silicate,carboxymethyl cellulose (CMC), and otheragents are used to disperse slime particles ofMgO-type minerals from sulphide surfaces(Bremmell et al., 2005; Kirjavainen andHeiskanen 2007; Lu et al., 2011). Adsorptionof these reagents on serpentine reverses the

positive surface charge, so attraction forcesbetween pentlandite and serpentine areeliminated (Bremmel et al., 2005).

Sodium carbonate is a reagent thatcommonly used to modify the pulp pH.However, the carbonate ions will not onlychange the pH, but can also increase nickelflotation selectivity over MgO minerals(Pietrobon et al., 1997). Sodium carbonatemay have an influence on both the mineralsurfaces and solution chemical species. Themechanism by which sodium carbonateimproves nickel flotation recovery has notbeen elucidated to date. In this study, theeffect of sodium carbonate on the flotationperformance of a nickel ore was studied andthe mechanism investigated.

The serpentine lizardite used for the FTIRstudy was obtained from Donghai, JiangsuProvince, China. The mineral composition ofthe lizardite as determined by XRD was:lizardite 98%, chlorite 2%.

The ore sample used in this study is ofhigh nickel grade (1.35% Ni). Approximately96% of the nickel content is in the form ofpentlandite and can be recovered by trueflotation. The remaining 4% of nickel isdistributed in non-sulphide minerals, and canbe recovered only by entrainment or ascomposites with pentlandite. The ore contains37% w/w MgO, distributed mainly in lizardite(46% w/w) and olivine (19% w/w), asdetermined by X-ray diffraction.

The effect of sodium carbonate on thedispersion behaviour and froth flotationof a nickel oreby B. Feng*†, Q.M. Feng†, Y.P. Lu†, and H.H. Wang*

The effect of sodium carbonate on the flotation performance of a nickel orewas studied and the mechanism investigated. The flotation results showthat lizardite minerals in the ore interfere with the flotation of pentlandite,and the addition of sodium carbonate improves pentlandite flotationrecovery. The pulp pH did not change with increasing sodium carbonatedosage. Drawing on the literature in this area, combined with the sedimen-tation test results, sieving test results, and infrared spectra study, it isproposed that carbonate ions, derived from sodium carbonate, interactwith lizardite slime and change the interparticle force from attraction torepulsion, resulting in the removal of adhering slimes from pentlanditesurfaces.

sodium carbonate, nickel flotation, lizardite, pentlandite.

* Jiangxi Key Laboratory of MiningEngineering,Jiangxi University of Science andTechnology, Ganzhou, China.

† School of Mineral Processing and Bioengineering,Central South University, Changsha, China.

© The Southern African Institute of Mining andMetallurgy, 2015. ISSN 2225-6253. Paper receivedApr. 2015 and revised paper received July 2015.

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The effect of sodium carbonate on the dispersion behaviour and froth flotation of a nickel ore

PAX (potassium amyl xanthate) and MIBC (methylisobutyl carbinol) were used as collector and frother respec-tively. All the reagents used in this study were of analyticalgrade.

Ore samples were crushed to -2 mm, riffled into represen-tative samples of 500 g, purged with nitrogen, and frozenduring storage. For each flotation experiment, samples wereground in a mild steel rod mill to a P70 of 74 μm. Sodiumcarbonate was added at the grinding stage.

The flotation tests were performed in a XFD-63 flotation cell(self-aeration) with a flotation volume of 1.5 L, using anagitation speed of 2800 r/min. The solid concentration in theflotation cell was 35% by weight. The pulp pH wasmaintained at 9 owing to the buffer effect of the mineralswithin the pulp. During the conditioning, collector (150 g/t)and frother (30 g/t) were added and conditioned for 5minutes respectively to allow for collector and frotheradsorption. After conditioning, flotation was started with theinjection of air into the flotation cell. The air flow rate wasmaintained at 0.1 Nm3/h, monitored with a flow meter.Flotation was performed for 15 minutes and five concentrateswere collected after cumulative times of 1, 3, 6, 10, and 15minutes (Feng et al., 2012).

To study the effect of sodium carbonate on the settlingbehaviour of the pulp, sedimentation tests were performed.Ore samples were ground to a P70 of 74 μm. Sodiumcarbonate was added at the grinding stage when needed. 100ml aliquots of ground pulp were transferred to a 100 mlmeasuring cylinder, and the height of the upper clear layerrecorded at fixed times.

The floatability of pentlandite depends on the amount ofslimes on its surface. To study the effect of sodium carbonateon the amount of slimes removed from the surfaces of coarsesulphide particles, sieving tests were performed. Pulps weresampled from the flotation cell before and after the additionof sodium carbonate and sieved to remove -75 μm particles.The particle size distribution of the +75 μm pulp samples wasmeasured using a Malvern Master Sizer X (using tap water asa carrier for the measurements). The samples were measuredafter sonication (in a sonication bath attached to the MalvernMaster Sizer X) for 4 minutes at the maximum sonicationintensity (Chen et al., 1999a, 1999b). Portions of the +75 μmsamples were treated by sonication and re-sieved at 75 μm,and the -75 μm particles collected for XRD analysis.

In order to study the interaction of carbonate with lizardite,the IR (infrared) spectra of lizardite before and after sodiumcarbonate treatment were measured using a Nexus 670 seriesFourier transform infrared spectrometer in the range 4000–350 cm−1. For the analysis of pure sodium carbonate orlizardite, a 20 mg sample was added to 200 mg KBr, for aconcentration of approximately 10 wt%. To test the infraredspectra of lizardite treated with sodium carbonate, 0.5 g

samples of pure lizardite were individually suspended in 200ml of sodium carbonate solution for 5 minutes. The pulpswere then centrifuged and washed at least three times withdistilled water and dried in a vacuum oven at 40°C. Theinfrared spectra were obtained as for the pure lizarditesample.

The ore contained a large amount of lizardite slimes aftergrinding. The slimes interfered with the pentlandite flotationby adsorbing onto its surface. In the past, the concentratorused carboxymethyl cellulose to disperse and depress theslime. Sodium carbonate is a reagent that is commonly usedto modify the pulp pH, and it can also be used to precipitatemetal ions and disperse slime. To further improve theflotation recovery of pentlandite, sodium carbonate wasconsidered as a dispersing agent on the basis of the originalreagent regime.

The effect of sodium carbonate on the recovery and gradeof the nickel ore is shown in Figure 1, and the effect offlotation time on the recovery with different sodiumcarbonate dosages is shown in Figure 2. The flotation resultsindicate that the addition of 5 kg/t sodium carbonateincreased the nickel recovery from 82% to 90%, while the Nigrade did not change.

To study the mechanism by which sodium carbonateincreased the flotation recovery of pentlandite, the effect ofsodium carbonate on the settling behaviour of the nickel orewas investigated. The results (Figure 3) show that theaddition of sodium carbonate reduced the settling velocity ofthe nickel ore, indicating that sodium carbonate has adispersion effect on the pulp.

The effect of sodium carbonate on surface cleaning of thecoarse particlea was investigated by the sieving tests and theresults are shown in Figure 4. Pulps were sampled from theflotation cell before and after the addition of sodiumcarbonate and sieved at 75 μm to remove -75 μm particles.Ideally, no particles less than 75 μm should remain in the+75 μm fraction after sieving, unless those particles areadhering to the +75 μm coarse particles through slimecoating. Thus, the change of size distribution of the fines(–75 μm fraction) in the +75 μm sample after the addition of

▲

1240

sodium carbonate can be used to indicate the change in theamount of slimes on the coarse particle surfaces.

The results show that the amount of slimes removed fromthe surfaces of the coarse particles increased with increasingsodium carbonate dosage, and the coarse particle surfaceswere free of particles less than 4 μm in size when 5 kg/tsodium carbonate was used. This shows that sodiumcarbonate is effective in assisting the removal of adheringslime particles from pentlandite surfaces.

The mineral composition of the slimes removed fromlarge particles was investigated using XRD analysis. Theresults (Figure 5) suggest that the slimes attached to thesurfaces of large particles were mainly lizardite, chlorite, andtalc. The magnesium silicate gangue minerals are soft andmore easily broken than the sulphide minerals in thegrinding and conditioning processes. Thus the slimesconsisted mainly of magnesium silicate gangue minerals.

The pH of the pulp after the addition of sodium carbonateis shown in Figure 6. The pulp pH remained essentiallyconstant with the increase of sodium carbonate concen-tration. This result shows that sodium carbonate does notplay a role in modifying the pulp pH.

The pH regulators are divided in two main groups:reagents that produce hydroxyl (OH-) by dissociation and

reagents which form OH- by hydrolysis. Sodium carbonatebelongs to the latter group. Equations [1]-[3] showhydrolysis of carbonate. The ore contains 46% lizardite(w/w), which will consume carbonate; thus, there will not besufficient carbonate ions left in the pulp to alter the pH.

Na2CO3→2Na+CO32- [1]

CO32-+H2O HCO3

-+OH- [2]

HCO3-+H2O H2CO3+OH- [3]

In a previous study, it was demonstrated that sodiumcarbonate can effectively disperse lizardite and pyrite,improving the flotation performance of pyrite, which isdepressed by lizardite (Feng and Luo, 2013). In order to studyhow the carbonate interacted with the lizardite surface, the IR(infrared) spectra were measured, and the results are shown inFigure 7. The IR spectrum of lizardite shows a peak at 3686.3cm-1 due to external Mg-OH stretching vibration, and theadsorption band of 984.6 cm-1 is assigned to stretchingvibration of Si-O. The peaks at 580 cm−1 and 443.6 cm−1

corresponding to deformation of the Mg-OH bond and shearvibration of Mg-OH, respectively. The IR spectrum of sodiumcarbonate has a strong adsorption peak at 1441.5 cm−1, and


1241 ▲


there also exists a peak at 1621.1 cm−1, both of which areattributed to the C-O asymmetric stretching vibration results.

After treatment with sodium carbonate, a new adsorptionpeak of 1423.8 cm−1 appeared in the infrared spectrum oflizardite, which is the result of carbonate adsorbed on thesurface of lizardite.

The particles finer than 5 μm in diameter are generallydescribed as ‘slimes’. The detrimental effect of slimes onflotation is encountered in many mineral systems. One of thereasons is related to their coating on valuable mineral particles.The dominant component in this nickel ore is lizardite, whichis soft and easily broken during the grinding process to formslimes.

Surface charge is an important factor in controlling particle-particle interactions. The formation of slime coatings is directlyrelated to the surface potentials of the sulphide minerals andlizardite particles. The lizardite has a positive potential at thepH range in which the flotation of nickel sulphide ore isperformed; it is therefore likely that it will attach throughelectrostatic attraction to the negatively charged sulphidesurface and form slime coatings. A coating of hydrophiliclizardite slimes will decrease the hydrophobicity of the sulphideparticle and result in lower sulphide mineral recovery.

The sodium carbonate can interact with lizardite andchange the surface charge to a negative value. The repulsiveforces due to like charges are greater than the attractive vander Waals forces and some slimes are removed from thesulohide surface. The amount of slime removed is related tothe dosage of sodium carbonate.

The valuable mineral of the nickel ore is pentlandite and themain gangue mineral is lizardite. The lizardite breaks readilyduring the grinding process and produces slimes, which arepositively charged at the pH where flotation of nickelsulphide ore is performed. Thus the slime will adsorb ontothe negatively charged pentlandite surface through electro-static attraction and depress pentlandite flotation. Sodiumcarbonate interacts with slime particles and removes adheringslimes from pentlandite surfaces. The coarse particle surfaceswere free of particles less than 4 μm in size at a sodiumcarbonate addition of 5 kg/t. This work has shown thatcarbonate can improve pentlandite flotation performance.

The authors acknowledge the support of the National NaturalScience Foundation of China (Nos.51404109), and theNational Basic Research Program of China (Nos.2014CB643400).

BREMMELL, K.E., FORNASIERO, D., and RALSTON, J. 2005. Pentlandite–lizarditeinteractions and implications for their separation by flotation. Colloids andSurfaces A – Physicochemical and Engineering Aspects, vol. 252, no. 2/3.pp. 207–212.

CHEN, G., GRANO, S., SOBIERAJ, S., and RALSTON, J. 1999a. The effect of highintensity conditioning on the flotation of a nickel ore, Part 1: Size by sizeanalysis. Minerals Engineering, vol. 12, no. 10. pp. 1185–1200.

CHEN, G., GRANO, S., SOBIERAJ, S., and RALSTON, J. 1999b. The effect of highintensity conditioning on the flotation of a nickel, part 2: Mechanisms.Minerals Engineering, vol. 12, no. 11. pp. 1359–1373.

EDWARDS, G.R., KIPKIE, W.B., and AGAR, G.E. 1980. The effect of slime coatingsof the serpentine minerals, chrysotile and lizardite on pentlanditeflotation. International Journal of Mineral Processing, vol. 7, no. 1. pp. 33–42.

FENG, B. and LUO, X. 2013. The solution chemistry of carbonate andimplications for pyrite flotation. Minerals Engineering, vol. 53. pp. 181–183.

FENG, B., FENG, Q., LU, Y., and LV, P. 2012. The effect of conditioning methodsand chain length of xanthate on the flotation of a nickel ore. MineralsEngineering, vol. 39. pp. 48–50.

KIRJAVAINEN, V. and HEISKANEN, K. 2007. Some factors that affect beneficiation ofsulphide nickel–copper ores. Minerals Engineering, vol. 20, no. 7. pp. 629–633.

LEARMONT, M.E. and IWASAKI, I. 1984. Effect of grinding media on galenaflotation. Mineral and Metallurgical Processing, vol. 1. pp. 136–143.

LU, Y.P., ZHANG, M.Q., FENG, Q.M., LONG, T., OU, L.M., and ZHANG, G.F. 2011.Effect of sodium hexametaphosphate on separation of serpentine frompyrite. Transactions of the Nonferrous Metals Society of China, vol. 21. pp. 208–213.

PIETROBON, M.C., GRANO, S.R., SOBIERAJ, S., and RALSTON, J. 1997. Recoverymechanisms for pentlandite and MgO-bearing gangue minerals in nickelores from Western Australia. Minerals Engineering, vol. 10, no. 8. pp. 775–786.

TRAHAR, W.J. 1981. A rational interpretation of the role of particle size inflotation. International Journal of Mineral Processing, vol. 8. pp. 289–327.

WELLHAM, E.J., ELBER, L., and YAN, D.S. 1992. The role of carboxy methylcellulose in the flotation of a nickel sulphide transition ore. MineralsEngineering, vol. 5. pp. 381–395. ◆

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Mineral processing can be considered as one ofthe most intensive water-consumingprocesses. To reduce fresh water consumption,numerous research works have focused on theuse of recycled process water. However, inflotation, recycling water can have adverseeffects on the mineral separation. The contentof organic reagents (frothers, collectors,depressants) as well as inorganic constituents(suspended matter, base metals, calcium,magnesium, sodium, sulphite, sulphate etc.)(Leavay et al., 2001; Johnson, 2003; Slatter etal., 2009) builds up and consequently affectsthe flotation performance (Lui et al., 1993;Leavay et al., 2001; Seke et al.,2006; Kelebekand Nanthakumar, 2007; Haran et al., 2008;Bıçak et al., 2012; Ikumapayi et al., 2012).Generally, the hydrolyzed metallic ions in thealkaline recycled water form a hydrophilicprecipitate (metal hydroxides, sulphates, orcarbonates) on the mineral surfaces, resultingin the formation of a hydrophilic barrier thatprevents adsorption of the collector (Senior

and Trahar, 1991; Fornasiero and Ralston,2006).

Cu2+ in copper sulphate form is known as asphalerite activator, and Zn recovery byflotation is enhanced by increasing concen-trations of Cu2+ ions in synthetic water (Bıçaket al., 2012). Cu2+ can also enhance therecovery of galena, chalcopyrite, and pyrite(Coetzer et al., 2003). However, the effect ofincreasing copper concentration on flotation isnot evident above pH 12 and below pH 5,where Cu(OH)3

- and Cu2+ are respectively thestable copper species (Fornasiero and Ralston,2006).

The hydrophobicity of the sphaleritesurface is controlled by the Zn(OH)2 formed(Prestidge et al., 1997; Fornasiero and Raston,2006). For sphalerite in alkaline media, thesurface Cu(OH)2 directly interacts with thexanthate (Leppinen,1990).

Cyanide ions used as depressant in apolymetallic ore can produce cupric ions byreaction with copper minerals and causeinadvertent activation of sphalerite. Theactivation process is enhanced at higher pHvalues (Seke et al., 2006; Rao et al., 2011).

The presence of Zn2+ in recycled waterstrongly depresses the recovery of sphalerite,and slightly depresses chalcopyrite and pyrite,but favours the recovery of galena (Coetzer etal., 2003). The use of zinc sulphate at alkalinepH decreases the recovery of galena due tocoating by hydrophilic Zn(OH)2 (Trahar et al.,1997; Seke, 2005).

The influence of water quality on theflotation performance of complex sulphideores: case study at Hajar Mine, Moroccoby K. Boujounoui*, A. Abidi†, A. Bacaoui*, K.El Amari‡, andA. Yaacoubi*

As part of the process optimization project of CMG (Mining Company ofGuemassa-Marrakech, Morocco), a preliminary study on the effect ofwater quality on the flotation of galena, sphalerite, chalcopyrite, andpyrrhotite was carried out using asymmetrical fractional factorial design.The multivariable analysis showed that of ten studied factors, six (Cu2+,Zn2+, Mg2+, Ca2+, SO42-, and PAX) have a significant influence on theflotation of these sulphide minerals. Graphical analysis showed that highconcentrations of Cu2+ (7–14 mg/L) in synthetic process water increasedthe recovery of galena, chalcopyrite, sphalerite, and pyrrhotite. At lowCu2+ concentrations (0–7 mg/L), sphalerite was depressed. Zn2+ at lowconcentrations (0–20 mg/L) decreased the recovery of all studied minerals.However, at high concentrations (20–40 mg/L), an increase inchalcopyrite, sphalerite, and pyrrhotite recoveries was observed. Mg2+

(100–200 mg/L) decreased the recovery of galena, chalcopyrite, andsphalerite. Ca2+ (1200–2000 mg /L) depressed sphalerite flotation.Sulphate ions (SO42-) enhanced recovery of all the studied minerals.Potassium amyl xanthate (PAX) promoted sphalerite recovery at highconcentrations (10–20 mg/L).

flotation, process water chemistry, complex sulphide ore, screening design.

* Faculty of Sciences Semlalia, department ofchemistry, BP 2390 Marrakech, Morocco.

† Mining Institute of Marrakech (IMM), B.P. 2402,Marrakech, Morocco.

‡ Laboratoire Géoressources, Unité associée auCNRST (URAC 42), Faculté des Sciences etTechniques Marrakech,. Marrakech, Morocco.

© The Southern African Institute of Mining andMetallurgy, 2015. ISSN 2225-6253. Paper receivedMar. 2015 and revised paper received July 2015.

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The influence of water quality on the flotation performance of complex sulphide ores

Ca2+ and Mg2+ are the most cited cations in the literatureas precipitated species with a negative effect on mineralrecoveries. Sphalerite recovery is significantly reduced in thepresence of these ions; the decrease is more pronounced forMg at pH 9 than for Ca at pH 12. This is due to the formationof the metal hydroxides on mineral surfaces (Lascelles et al.,2003). The adsorption of calcium and other metal ions induring flotation leads to the reduction of negative surfacecharges and consequently inhibits the adsorption of xanthateon the mineral surfaces (Ikumapayi et al., 2012).

Generally, the presence of SO42- in process water

containing numerous species, including SO32- and Ca2+, in

addition to dissolved iron, could form hydrophilic layers onthe surface mineral (CaSO4

2- or CaSO32-) (Ikumapayi et al.,

2012). Furthermore, a high concentration of SO42- ions has

the same depressing effect by competing with collectormolecules for adsorption on mineral surfaces (Wu et al.,2002; Lefèvre and Fédoroff, 2006).

In Morocco, the semi-arid to arid climate makes water alimited and precious resource. According to data from theHaouz Tensift Basin Agency (HTBA), the Marrakech region ofMorocco is characterized by low and irregular rainfall (250mm/a) with a high evaporation rate (2500 mm/a). The MiningCompany of Guemassa (CMG), located 30 km southwest ofMarrakech, is affected by this issue of water shortage.

CMG uses a selective flotation flow sheet to produce agalena concentrate (with Aerophine A3418 using NaCN at pHof 11.3), then a chalcopyrite concentrate (with AerophineA3418 at pH of 8.9), and finally a sphalerite concentrate(with potassium amyl xanthate; PAX, at pH of 12-12.5) froma complex polymetallic sulphide ore.

To reduce the consumption of fresh water and to test thepossibility of using a single process water in the overall CMGflotation process, this study focused on the effect ofsimulated process water quality on the recovery of Pb, Cu,and Zn during the galena flotation step. The study consideredthe effect of various ions in the water, as well as the particlesize of the feed. The goal was to achieve a better recoveryand selectivity of galena over sphalerite, chalcopyrite, andpyrrhotite. The results will assist in the flotation optimizationexercise by identifying the most important factors influencinggalena recovery and the interactions between them.

In this study, flotation tests were carried out on acomplex sulphide ore provided by CMG. The results were

subjected to statistical analysis to assess the relative signif-icance of the main factors affecting flotation performance asevaluated from the experimental results. The statisticaldesign of the experiments allows a full study of the effects ofall parameters on a given process and their optimization,providing maximum information from a minimum ofexperiments by implementing a simple mathematical model torepresent the studied phenomenon (Box et al., 1978;Akhanazarova and Kafarov, 1982; Obeng et al., 2005;Napier-Munn, 2012; Ennaciri et al., 2014).

To study the effect of water quality on the flotation of zinc,lead, and copper, the focus was on the parameters listedbelow and presented in Table I. These variables, with theirrespective ranges of values, were chosen on the basis of datafrom the literature and preliminary experiments.

➤ Water quality. Process water was synthesized fromMarrakech drinking water. Cations and anions wereadded to simulate the composition of recycled water inthe CMG zinc process. These ions are: Cu2+, Fe2+, Zn2+,Pb2+, Ca2+, Mg2+, SO4

2-, and PAX• Marrakech drinking water was used during grinding.

Once the pulp was introduced into the flotation cell,the desired synthesized water quality was adjusted byadding the salts of the relevant ions

• The grinding step was also performed usingsynthesized water directly

➤ Particle size – to distinguish the effect due to waterquality and mineralogical mixing.

Screening of these ten studied parameters reduced thenumber tests required to 27 (Table I and II) and enabled thefactors influencing the investigated responses: galena,chalcopyrite, sphalerite and pyrrhotite recoveries to beidentified.

Flotation tests were carried out on a representative sample ofcomplex sulphide ore composed of 6.43% sphalerite (Sp:ZnS), 2.22% galena (Gl: PbS), 0.95% chalcopyrite (Cp:CuFeS2), 41.57% pyrrhotite (Po: Fe9S10), and 48.82% gangue(Gg) consisting mainly of silica, carbonates, and chlorides.

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Table I

Parameter limits for the flotation tests on water quality effect on Ga, Cp, Sp, and Po recoveries

Coded variables Natural variables Medium components Levels1 2 3

X1 A Level of addition of In grinding In flotation --synthesized water

X2 B Cu2+, mg/L 0 7 14X3 C Fe2+, mg/L 0 350 700X4 D Zn2+, mg/L 0 20 40X5 E Pb2+, mg/L 0 0.25 2.5X6 F Ca2+, mg/L 400 1200 2000X7 G Mg2+, mg/L 0 100 200X8 H SO2-4, mg/L 200 1500 6000X9 I PAX, mg/L 0 10 20X10 J d80, μm 200 100 80

A sample of 120 kg was taken from the feed belt of theprimary ball mill of the CMG flotation plant and crusheddown to 2 mm using roll crushers in the laboratory of theInstitute of Mines in Marrakech. The crushed sample wassieved at 2 mm and the undersize split using a riffle dividerinto 500 g batch samples for the flotation experiments. Thebatch samples were stored in vacuum sealed bags to preventoxidation of the sulphide minerals.

Prior to the flotation tests, samples of 500 g were milledin 250 ml of synthetic water using a Denver carbon steel ballmill of 9.5 litres internal volume. The size fractions studied inthis work were d80 = 200 μm, 100 μm, and 80 μm (Figure 1).

Flotation tests were carried out in a Denver flotation cell of1.5 litre capacity. Solid concentration was about 27% byweight, using synthetic water at the required quality.

The natural pH was about 7. NaOH was used as pHregulator for all tests to pH=11.3. Sodium cyanide (NaCN)was used as a depressing reagent for Sp, Cp, and Po for alltests at a specific addition of 350 g/t. Diisobutyl phosphinate(Aerophine 3418A) (40 g/t) and methyl isobutyl carbinol(MIBC) (40 g/t) were used as galena collector and frotherrespectively. The impeller rotation speed was a constant 700r/min. The level of the pulp was constantly adjusted by theaddition of synthetic water at the required quality. Theflotation time was 10 minutes for each test, and theconcentrate was recovered by manual scraping every 30seconds. All concentrates and tails were filtered, dried, andweighed, and then analysed by atomic adsorptionspectroscopy (AAS) for Cu, Pb, Zn, and Fe. Metal recoveriesto the concentrates were calculated according to the followingequation:

where R is the metal recovery; tc the concentrate metal grade;tf the feed metal grade; C the concentrate weight, and A thefeed weight.

Waters used for the tests were synthesized by usingvarious salts: CaCl2 (97%), ZnSO4.7H2O (98%), and


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1 GR 0 0 0 0 400 0 200 0 200 47.13 50.37 35.93 23.152 GR 0 0 0 0.25 1200 100 1500 10 100 69.10 70.05 56.08 41.293 GR 0 0 0 2.5 2000 200 6000 20 80 70.40 70.93 53.32 42.954 GR 7 350 20 0 400 0 1500 10 100 52.81 47.65 33.17 22.665 GR 7 350 20 0.25 1200 100 6000 20 80 64.02 64.57 53.53 42.306 GR 7 350 20 2.5 2000 200 200 0 200 47.88 48.26 33.23 19.767 GR 14 700 40 0 400 0 6000 20 80 75.90 77.59 66.12 51.548 GR 14 700 40 0.25 1200 100 200 0 200 51.52 53.14 43.27 43.279 GR 14 700 40 2.5 2000 200 1500 10 100 54.42 56.51 42.37 31.8310 FL 0 350 40 0 1200 200 200 10 80 56.73 55.65 39.64 30.3611 FL 0 350 40 0.25 2000 0 1500 20 200 53.18 55.36 42.67 26.5212 FL 0 350 40 2.5 400 100 6000 0 100 71.39 73.10 54.95 38.6613 FL 7 700 0 0 1200 200 1500 20 200 55.23 54.48 33.58 22.3614 FL 7 700 0 0.25 2000 0 6000 0 100 66.83 63.51 39.55 26.2315 FL 7 700 0 2.5 400 100 200 10 80 58.83 58.35 44.38 30.5416 FL 14 0 20 0 1200 200 6000 0 100 57.50 57.58 41.84 26.6017 FL 14 0 20 0.25 2000 0 200 10 80 49.87 36.31 28.29 22.6218 FL 14 0 20 2.5 400 100 1500 20 200 57.94 57.31 43.14 28.4819 GR 0 700 20 0 2000 100 200 20 100 43.61 45.48 32.81 21.1120 GR 0 700 20 0.25 400 200 1500 0 80 38.54 41.61 32.18 24.0521 GR 0 700 20 2.5 1200 0 6000 10 200 55.40 56.32 37.91 24.3222 GR 7 0 40 0 2000 100 1500 0 80 61.93 61.72 43.29 28.9823 GR 7 0 40 0.25 400 200 6000 10 200 32.62 44.92 38.20 21.0224 GR 7 0 40 2.5 1200 0 200 20 100 51.71 56.39 50.60 31.1225 GR 14 350 0 0 2000 100 6000 10 200 55.49 63.22 48.36 27.1826 GR 14 350 0 0.25 400 200 200 20 100 62.59 61.67 49.67 30.9127 GR 14 350 0 2.5 1200 0 1500 0 80 50.29 56.10 42.33 27.08

FL: water addition in flotation step; GR: water addition during grinding step; WAL: water addition level


FeCl2.6H2O (97%) from Prolabo; Na2SO4 (99%) and PbCl2(98%) from Fluka; Cu(NO3)2.3H2O (99.5%) from Merck; andMg(NO3)2.6H2O (99-102%) from Panreac. Flotation reagents(Aerophine 3418A, PAX, and MIBC) were provided by CMG.

The effect of water addition was also studied. Water canbe introduced at the grinding or at the flotation stage. Table IIsummarizes the designed experiments and operatingconditions.

To assess the effect of each factor on the flotation of Pb, Cu,Zn, and Fe during the lead flotation step, the operatingconditions of the tests were established according to anasymmetrical fractional factorial matrix. These kinds ofmultivariate experimental designs are powerful tools for theoptimization of such procedures. Compared to traditionalunivariate approaches, based on the study of the effect of onevariable at a time on the selected response, multivariatetechniques allow the simultaneous evaluation of severalfactors with a minimum number of experiments.Furthermore, they provide additional data about the system,with the estimation of interactions between the influencingfactors.

The screening experiment for several factors enablesestimation of K factors in N experiments (K=10 and N= 27 inour case) with a variance of σ²/27. The model applied in this

study is a polynomial empirical model of the first degree,which contains only the terms (bi) that will reflect the effectof each of the ten factors on the four responses: recovery ofgalena (R-Pb), of chalcopyrite (R-Cu), of sphalerite (R-Zn),and of pyrrhotite (R-Fe).

The model can be written as:

Y = b0 + b1A*(X1A) + b2A*(X2A) + b2B*(X2B) +b3A*(X3A) + b3B*(X3B) + b4A*(X4A) + b4B*(X4B) +b5A*(X5A) + b5B*(X5B) + b6A*(X6A) + b6B*(X6B) +b7A*(X7A) + b7B*(X7B) + b8A*(X8A) + b8B*(X8B) +

b9A*(X9A) + b9B*(X9B) + b10A*(X10A) + b10B*(X10B)

whereY: the studied response, which could be the recovery of

lead (R-Pb), Y1: of copper (R-Cu), Y2: of zinc (R-Zn), Y3; orof iron (R-Fe), Y4

Xi: the investigated factor (i varies from 1 to 10)A: the domain delimited by levels 1 and 2 of the factor XiB: the domain delimited by levels 2 and 3 of the factor XibiA: Xi effect in the domain AbiB: Xi effect in the domain B.Tables I and II describe the approach of this study. The

design matrix (fractional factorial), generated by thescreening design resulted in the development of a series of 27flotation tests (Table II). The experimental sequence was

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Y1 (R-Pb) B2-3 : Cu2+ 7 - 14 -13.076 2.954 -4.43 1.27 *D1-3 : Zn2+ 0 - 40 11.227 2.954 3.80 2.02 *D1-2 : Zn2+ 0 - 20 18.039 2.954 6.11 0.479**G1-3 : Mg2+ 0 - 200 10.397 2.842 3.66 2.27 *G2-3 : Mg2+ 100 - 200 11.673 2.842 4.11 1.60 *H1-3 : SO42- 200 - 6000 -14.091 2.842 -4.96 0.899 **H1-2 : SO42- 200 - 1500 -9.992 2.842 -3.52 2.55 *J1-3 :d80,μm 200 - 80 -12.090 2.954 -4.09 1.61 *B2-3 : Cu2+ 7 - 14 -9.117 2.465 -3.70 2.19 *

Y2 (R-Cu) D1-2 : Zn2+ 0 - 20 17.340 2.465 7.04 0.317 **D2-3 : Zn2+ 20 - 40 -11.211 2.321 -4.83 0.972 **G2-3 : Mg2+ 100 - 200 10.001 2.372 4.22 1.47 *H1-3 : SO42- 200 - 6000 -15.644 2.372 -6.60 0.382 **H1-2 : SO42- 200 - 1500 -9.397 2.372 -3.96 1.78 *J1-3 : d80, μm 200 - 80 -8.420 2.465 -3.42 2.78 *

Y3 (R-Zn) B1-2 : Cu2+ 0 - 7 4.499 1.612 2.79 3.82 *B2-3 : Cu2+ 7 - 14 -8.661 1.652 -5.24 0.392 **D1-2 : Zn2+ 0 - 20 12.132 1.652 7.34 0.111 **D2-3 : Zn2+ 20 - 40 -12.171 1.612 -7.55 0.100 **F2-3 : Ca2+ 1200 - 2000 8.553 1.652 5.18 0.411 **G2-3 : Mg2+ 100 - 200 8.923 1.612 5.53 0.318 **H1-3 : SO42+ 200 - 6000 -11.166 1.612 -6.93 0.137 **H1-2 : SO42+ 200 - 1500 -5.898 1.652 -3.57 1.65 *I2-3 : PAX 10 - 20 -6.338 1.538 -4.12 0.972 **J1-3 : d80 ,μm 200 - 80 -9.876 1.652 -5.98 0.238 **J1-2 : d80 ,μm 200 - 100 -7.698 1.612 -4.77 0.559 **

Y4 (R-Fe) B2-3 : Cu2+ 7 - 14 -7.443 2.560 -2.91 4.42 *D1-2 : Zn2+ 0 - 20 9.241 2.463 3.75 2.10 *D2-3 : Zn2+ 20 - 40 -8.346 2.463 -3.39 2.85 *H1-3 : SO42- 200 - 6000 -10393 2.560 -4.06 1.65 *J1-3 : d80, μm 200 - 80 -14.297 2.560 -5.59 0.626 **J1-2 : d80, μm 200 - 100 -8.881 2.560 -3.47 2.66

** Statistically significant at the 99% level (p-value < 0.01)* Statistically significant at the 95% level (p-value < 0.05)

randomized in order to minimize the effects of theuncontrolled factors. The results were analysed usingNemrodw Software (New Efficient Methodology for Researchusing Optimal Design from LPRAI, Marseille, France)(Mathieu et al., 2000). The interpretation of the coefficientsand the main effects of factors (bi), was performed fromstatistical tests on the coefficients using Student’s test(t /2,d).

The results of the flotation tests conducted according to theexperiments in Table II are presented in Figures 2–5 andTables II and III. The standard errors calculated for theresponses (R-Pb), (R-Cu), (R-Zn), and (R-Fe) were 3.215,4.10, 2.240, and 3.338 respectively.

Table II shows that despite the flotation conditions(reagents, depressant, pH etc.) being favourable for good leadrecovery and selectivity over Cu, Zn, and Fe, the flotationresponses are affected by the quality of the process water.Lead recovery seems to be inversely related to the flotationrecoveries of the other elements. This could be due to thecomposition of the process water, where dissolved speciescould depress galena and/or activate the other mineralphases. Their effects could be assessed from Figures 2–5,which are useful for identifying the statistically significantfactors at level 99% (p-value < 0.01) and 95% (p-value <0.05) (Table III). The limits of significance are represented bydashed lines in Figures 2a–5a, which depict the differences inthe weight of the different levels for each response. Non-significant effects are those located between the two limits ofsignificance.


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From these figures, the more important factorsinfluencing Pb, Cu, Zn, and Fe recoveries during the leadflotation step were derived and are presented in Table III. Theeffect of Cu2+ is clear on the responses of R-Pb, R-Cp, R-Sp,and R-Po. Increasing the Cu2+ concentration from 7 to 14mg/L (B2 to B3) has a positive effect on the recovery of allstudied minerals. It also affects the selectivity for galena overchalcopyrite, sphalerite, and pyrrhotite. This selectivity couldbe enhanced at 0–7 mg/L Cu2+ (B1 to B2), where a negativeeffect on the sphalerite recovery was observed.

The positive influence of high concentrations of Cu2+ onthe recoveries of Ga, Sp, and Po could be due to theadsorption of Cu2+, Cu(OH)2, and Cu(OH)3

- on the surfaces ofthese minerals (Prestidge et al., 1997; Fornasiero andRalston, 2006; Chandra and Gerson, 2009). Low concen-trations of Cu2+ depress only the recovery of sphalerite. Thisdepressing effect might be due to weak absorption of copper

onto the sphalerite surface due to competition with Cu2+ foradsorption sites (Deng et al., 2013). Moreover, the cyanideions could cause inadvertent activation of sphalerite by cupricions produced by the action of cyanide on copper minerals(Seke and Pistorius, 2006; Rao et al., 2011).

Zinc ions at concentrations from 0 to 40 mg/L (D1 to D3)have a negative effect only on the recovery of galena, but thisnegative effect is very pronounced from 0 to 20 mg/L (D1 toD2) on the recoveries of galena, chalcopyrite, sphalerite, andpyrrhotite. However, at Zn2+ concentrations from 20 to 40mg/L (D2 to D3), the effect becomes positive except forgalena. Both recovery and selectivity of galena over the otherminerals are poor at zinc concentrations up to 40 mg/L.

The positive effect of Zn2+ could be due to the formationof hydrophobic precipitated species on the mineral surfaces(Znn–xCux.xZn(OH)2(surface), for example). Generally, Zn2+

ions (as zinc sulphate) in alkaline conditions are used to

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depress sphalerite to increase lead/zinc selectivity.High concentrations of Ca2+ in the synthesized water

(1200–2000 mg/L) (F2 to F3) depress sphalerite and have nonotable depressant effect on the other minerals, especiallygalena. The presence of Ca2+ might be considered beneficialwithin the lead circuit.

Mg2+ at high concentrations (100–200 mg/L) (G2 to G3)has a very important negative effect on galena, chalcopyrite,and sphalerite recoveries, but no effect on pyrrhotite. TheMg2+ concentration in water process in the lead circuit musttherefore be controlled.

The depressive effect of Ca2+ and Mg2+ could be due tothe formation of hydrophilic layers such as CaCO3 on themineral surfaces in alkaline conditions, which prevents theadsorption of the collector onto mineral surfaces (Lascelles etal., 2003; Deng et al., 2013; Ikumapayi et al., 2012).

Sulphate ions (SO42-) from 200 to 6000 mg/L (H1 to H3)

have a significant positive effect on the recovery of allstudied minerals, consequently affecting the lead selectivity.This positive effect is weak from 200 to 1500 mg/L SO4

2- (H1to H2) on the recoveries of galena, chalcopyrite, andsphalerite.

The positive effect of sulphate on recoveries could be dueto the formation of heavy metal sulphite salts, which areslightly soluble in water (e.g. PbSO4, Ks = 1.8*10-8 at 25°C inpure water), on the mineral surfaces.

High concentrations of PAX (1020 mg/L) in synthesizedwater (I1 to I2) promote sphalerite recovery. The positiveeffect of PAX is due to the formation of Cu(I)-xanthate andadsorption of dixanthogen (when Cu2+ concentration is low)on the surface of the sphalerite (Leppinen, 1990; Popov andVucinc, 1990). Xanthates are widely used in sulphide mineralflotation, especially in the selective flotation of sphalerite(Finkelstein, 1997).


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The particle size (d80 from 200 to 80 μm) (J1 to J3) has apositive effect on the recovery of all studied minerals. Theseeffects are more pronounced between 200 to 100 μm (J1 toJ2). Decreasing the particle size promotes the recovery of allstudied minerals and affects the lead selectivity over Cu, Feand Zn, due to the fact that the smaller the particle size, thegreater the probability of adhesion to the air bubbles (Jowettet al., 1980), and the less the probability of detachment(Holtham et al., 1991).

Batch-scale flotation tests were performed on a complex Pb-Cu-Zn-Fe sulphide ore to investigate the influence of recycledwater quality on the flotation of galena, chalcopyrite, andsphalerite during the lead flotation step. Screening

experiments were conducted to study the effects of ten factors(Cu2+, Fe2+, Zn2+, Pb2+, Ca2+, Mg2+, SO4

2-, and PAX concen-tration, grain size, and water addition) on Pb, Cu, Zn, and Ferecoveries. The results showed that the influence of processwater on lead flotation depends on its composition andconcentrations of constituents.

➤ The addition level of recycled water (during thegrinding or at the start of flotation) has no significanteffect on the flotation of the studied minerals

➤ A small particle size enhances the recoveries of all theminerals studied

➤ Sulphate ions (SO42-) also have a positive effect on

recoveries, but the domains of influence varies fromone mineral to another

➤ High concentrations Cu2+ increase the recovery of the

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all studied minerals. Cu2+ has a depressing effect ofsphalerite at low concentrations

➤ Zn2+ at low concentrations has a depressant effect onthe recovery of all the mineral phases, but at highconcentrations improves the recovery of chalcopyrite,sphalerite, and pyrrhotite

➤ Mg2+ depresses galena, chalcopyrite, and sphalerite atthe high concentrations

➤ Ca2+ has a depressant effect on sphalerite at concen-trations

➤ Potassium amyl xanthate at high concentrationsenhances sphalerite recovery.

These factors, with their ranges of influence, will be thesubject of further investigations to determine the nature ofthe interactions between them and their effects on recoveries.An optimization study will be carried out to determine theparameters that have the greatest influence on recoveries.

The authors thank the Mining Company of Guemassa forproviding the sulphide ore sample and the flotation reagents,and Reminex Society for the chemical analyses.

AKHANAZAROVA, S. and KAFAROV, V. 1982. Experiment Optimization inChemistry and Chemical Engineering. Mir Publishers, Moscow.

BICAK, O., EKMEKCI, Z., CAN, M., and OZTURK, Y. 2012. The effect of waterchemistry on froth stability and surface chemistry of the flotation of a Cu–Zn sulfide ore. International Journal of Mineral Processing, vol. 102–103.pp. 32–37.

BOX, G.E.P., HUNTER, W.G., and HUNTER, J.S. 1978. Statistics for Experiments.Wiley, New York.

CHANDRA, A.P. and GERSON, A.R. 2009. A review of the fundamental studies ofthe copper activation mechanisms for selective flotation of the sulfideminerals, sphalerite and pyrite. Advances in Colloid and Interface Science,vol. 145. pp. 97–110.

COETZER, G., DU PREEZ, H.S., and BREDENHANN, R. 2003. Influence of waterresources and metal ions on galena flotation of Rosh Pinah ore. Journal ofthe South African Institute of Mining and Metallurgy, vol. 103, no. 3. pp. 193–207.

DENG, M., LIU, Q., and XU , Z. 2013. Impact of gypsum supersaturated water onthe uptake of copper and xanthate on sphalerite. Minerals Engineering,vol. 49. pp. 165–171.

ENNACIRI, K., BAÇAOUI, A., SERGENT, M., and YAACOUBI, A. 2014. Application offractional factorial and Doehlert designs for optimizing the preparation ofactivated carbons from Argan shells. Chemometrics and IntelligentLaboratory Systems, vol. 139. pp. 48–57.

FINKELSTEIN, N.P. 1997. The activation of sulphide minerals for flotation: areview. International Journal of Mineral Processing, vol. 52. pp. 81–120.

FORNASIERO, D. and RALSTON, J. 2006. Effect of surface oxide/hydroxide productson the collectorless flotation of copper-activated sphalerite. InternationalJournal of Mineral Processing, vol.78. pp. 231–237.

HARAN, N.P., BOYAPATI, E.R., BOONTANJAI, C., and SWAMINATHAN, C. 2008. Kineticsstudies on effect of recycled water on flotation of copper tailings fromBenambra Mines. Developments in Chemical Engineering and MineralProcessing, vol. 4, no. 3–4. pp. 197–211.

HOLTHAM, P.N. and CHENG, T-W. 1991. Study of probability of detachment ofparticles from bubbles in flotation. Transactions of the Institution ofMining and Metallurgy Section C, vol. 100, Sep-Dec. pp. 147–153.

IKUMAPAYI, F., MAKITALO, M., JOHANSSON, B., and RAO, K.H. 2012. Recycling ofprocess water in sulphide flotation: effect of calcium and sulphate ions onflotation of galena. Minerals Engineering, vol. 39. pp. 77–88.

JOHNSON, N.W. 2003. Issues in maximization of recycling of water in a mineralprocessing plant. Proceedings of Water in Mining 2003, Brisbane, 13–15October. Publication Series No. 6/2003. Australian Institute of Mining andMetallurgy, Melbourne. pp. 239–245.

JOWETT, A. 1980. Formation and disruption of particle-bubble aggregates inflotation. Fine Particles Processing. Somasundaran, O. (ed.). AmericanInstitute of Mining, Metallurgical and Petroleum Engineers. pp. 721–751.

KELEBEK, S. and NANTHAKUMAR, B.2007. Characterization of stockpile oxidationof pentlandite and pyrrhotite through kinetic analysis of their flotation.International Journal of Mineral Processing, vol. 84. pp. 69–80.

LASCELLES, D., FINCH, J.A., and SUI, C. 2003. Depressant action of Ca and Mg onflotation of Cu activated sphalerite. Canadian Metallurgical Quarterly, vol.42, no. 2. pp 133-140.

Leavay, G.R.St., Smart, C., and Skinner, W.M., 2001. The impact of waterquality on flotation performance. Journal of the South African Institute ofMining and Metallurgy, vol. 101, no. 2. pp. 69–75.

LEFÈVRE, G. and FÉDOROFF, M. 2006. Sorption of sulfate ions onto hematitestudied by attenuated total reflection-infrared spectroscopy: kinetics andcompetition with other ions. Physics and Chemistry of the Earth, PartsA/B/C, vol. 31, no. 10–14. pp. 499–504.

LEPPINEN, J.O. 1990. FTIR and flotation investigation of the adsorption of ethylxanthate on activated and non-activated sulfide minerals. InternationalJournal of Mineral Processing, vol. 30. pp. 245–263.

LIU, W., MORAN, C.J., and VINK, S. 2013. A review of the effect of water qualityon flotation. Minerals Engineering, vol. 53. pp. 91–100.

LUI, L., RAO, S.R., and FINCH, J.A. 1993. Laboratory study effect of recycle wateron flotation of a Cu/Zn Sulphide ore. Minerals Engineering, vol. 6, no. 11.pp. 1183–1190.

MATHIEU, D., NONY, J., and PHAN TAN LUU, R. 2000. Software NEMRODW.LPRAI-Marseille, France

NAPIER-MUNN, T.J. 2012. Statistical methods to compare batch flotation grade-recovery curves and rate constants. Minerals Engineering, vol. 34. pp. 70–77.

OBENG, D.P., MORRELL, S., and NAPIER-MUNN, T.J. 2005. Application of centralcomposite rotatable design to modelling the effect of some operatingvariables on the performance of the three-product cyclone. InternationalJournal of Mineral Processing, vol. 76. pp. 181–192.

POPOV, S.R., VUCINIC, D.R., and KACANIC, J.V.1989. Floatability and adsorption ofethyl xanthate on sphalerite in an alkaline medium in the presence ofdissolved lead ions. International Journal of Mineral Processing, vol. 27.pp. 205–219.

PRESTIDGE, C.A., SKINNER, W.M., RALSTON, J., and SMART, R.C. 1997. Copper (II)activation and cyanide deactivation of zinc sulphide under mildly alkalineconditions. Applied Surface Science, vol. 108. pp. 333–344.

RAO, S.R., NESSET, J.E., and FINCH, J.A. 2011. Activation of sphalerite by Cu ionsproduced by cyanide action on chalcopyrite. Minerals Engineering, vol. 24.pp. 1025–1027.

SEKE, M.D. 2005. Optimization of the selective flotation of galena andsphalerite at Rosh Pinah Mine. PhD thesis, University of Pretoria, SouthAfrica.

SEKE, M.D. and PISTORIUS, P.C. 2006. Effect of cuprous cyanide, dry and wetmilling on the selective flotation of galena and sphalerite. MineralsEngineering, vol. 19. pp. 1–11.

SENIOR, G.D. and TRAHAR, W.J. 1991. The influence of metal hydroxides andcollector on the flotation of chalcopyrite. International Journal of MineralProcessing, vol. 33. pp. 321–341.

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WILLIAMS, S.R. and PHELAN, J.M. 1985. Process development at WoodlawnMines. Complex Sulphides, Processing of Ores, Concentrates, and By-products. Zunkel, A.D., Borman, R.S., and Wesely, R.J. (eds). AIME, NewYork. pp. 293–304.

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The 2nd School onManganese Ferroalloy

Production

Topics to be presented will include:� Commercial production� Overview of manganese production in South Africa� Manganese raw materials - mineralogy and other

properties� Geology, and mining, of the Kalahari manganese

ore body� Overview and fundamental thermodynamics� Slag fundamentals � Pre-reduction zone � Cokebed zone� Electrical current paths and resistance in furnace� Energy consumption� Lining concepts in the manganese ferroalloy

production � Environmental considerations.

The intention is to include in the programme, paneldiscussions on identification of techno-economicchallenges faced by role players in the South Africanmanganese industry, and finding ways to address thesechallenges.

INTRODUCTIONSouth Africa has the largest, land-based, Mn-ore reserves, exploited by anumber of mining companies. Although the country is primarily an exporter ofmanganese-bearing ores, it has four smelter complexes beneficiating ore byproducing high carbon ferromanganese, medium carbon ferromanganese, andsilico-manganese. In South Africa, four smelter complexes are operated byMetalloys and Assmang (ferromanganese producers), and Transalloys andMogale Alloys (silicomanganese producers).

In order to support the smelters, and foster collaboration betweenresearchers in the field, the SAIMM hosted in 2012, a School on ManganeseFerroalloy Production. The school was presented by Prof. Merete Tangstad,and co-workers.

The 2nd School on Manganese Ferroalloy Production will build on thecollaboration between South Africa and Norway, and between role playerswithin the South African manganese industry, by including a larger number oflocal participants. The focus of the event will be the identification of techno-economic challenges faced by role players in the South African manganeseindustry, and finding ways to address these challenges.

WHO SHOULD ATTENDDelegates from the manganese ferro-alloy industry, or those who support them:� Existing and potential industry role players� Engineering companies� Research/academic institutions� Companies providing funding for new manganese

projects.

EXHIBITION/SPONSORSHIPSponsorship opportunities are available. Companies wishing to sponsor orexhibit should contact the Conference Co-ordinator.

For further information contact:Conference Co-ordinator, Yolanda RamokgadiSaimm, P O Box 61127, Marshalltown 2107

Tel: +27 (0) 11 834-1273/7 · E-mail: [email protected]: http://www.saimm.co.za

MAIN PRESENTER—MERETE TANGSTADProfessor at NTNU (Norwegian University of Science and Technology).

Merete took her Master degree and PhD degree atNTNU. In the following years, she worked for Elkemand Eramet, mostly within ferromanganese andsilico-manganese production, and mainly withresearch within these processes. Since 2004, shehas been a professor at the Norwegian Universityof Science and Technology within Material Scienceand Engineering, with the main emphasis onmanganese ferro-alloy production, and upgrading

metallurgical silicon to solar-grade silicon. Merete is co-author of thedefinitive textbook on manganese ferroalloy production: Production ofManganese Ferroalloys, published by Tapir Press in Norway.

27–28 June 2016

The Kansanshi Mine (First Quantum Minerals)treats a mixed oxide/sulphide copper-gold veindeposit with very variable mineralization. Allthe copper minerals constituting the alterationsequence from primary sulphides to carbonatesor silicates are present in various proportions(Table I).

The alteration of primary sulphides startswith an impoverishment in iron to formcovellite. Further oxidation generates animpoverishment in sulphur and enrichment in

copper to form digenite then chalcocite (Dunnand Muzenda, 2001). The ultimate steps ofalteration leading to the formation of copperoxide minerals, such as malachite orchrysocolla, depend on the composition of thegangue or fluid. The iron liberated during thealteration sequence can remobilized and formgoethite or limonite. These iron oxides andhydroxides are particularly prejudicial for theflotation if they precipitate on the surface ofthe copper minerals because they are notcollectable with xanthates (Woods, 2003).

Since the beginning of the operations in2004, millions of tons of mixed oxide/sulphidecopper-gold ores with a high gangue acidconsumption (GAC) were disposed onstockpiles, as they were uneconomic to treatthrough the old circuit configuration. Thisconventional flow sheet incorporated the useof xanthate flotation of the sulphide minerals,followed by acid leaching of the oxides.

The traditional method applied for theflotation of copper oxide or mixed ores issulphidization, which was first developed withindustrial success on Pb-Zn oxide ores inAustralia (Crozier, 1991). The methodinvolves multistage addition of sodiumsulphide (Na2S), sodium hydrosulphide(NaHS), or ammonium sulphide (NH4)2S as asulphidizing agent, together with xanthatecollectors such as potassium amyl xanthate(PAX) (Mwema and Mpoyo, 2001; Kongolo etal., 2003). The effectiveness of sulphizationfor flotation of oxidized sulphides has alsobeen demonstrated (Newell et al., 2006).When introduced in the slurry, the sulphidizerdissociates into the species H2S, HS-, S2-

depending of the pH. These ions react with thecopper oxide minerals, to form a sulphide layeron the surface of the mineral particles (Zhou

Development and optimization of mixedsulphide/oxide copper ore treatment atKansanshiby F.X. Paquot* and C. Ngulube*

The Kansanshi Mine (First Quantum Minerals Ltd) treats a mixedsulphide/oxide copper-gold vein deposit. Until June 2009, the sulphide andoxide minerals were respectively recovered by the well establishedxanthate flotation of sulphides and acid leaching of soluble oxide copper.The mixed (transitional) sulphide/oxide ores were stockpiled in theabsence of an economic processing route due to their poor flotationresponse and high gangue acid consumption.

Since June 2009, these mixed ores have been treated by flotation usingcontrolled potential sulphidization. This paper describes the developmentof the process and its optimization. The effect of the complex mineralogyon the flotation performance is also depicted.

copper flotation, mixed sulphide/oxide ore, controlled potentialsulphidazition.

* First Quantum minerals Ltd, Kansanshi Mine,Solwezi, Zambia.

© The Southern African Institute of Mining andMetallurgy, 2015. ISSN 2225-6253. Paper receivedJan. 2013 and revised paper received June 2015.

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Chalcopyrite CuFeS2

Bornite Cu5FeS4Covellite CuSDigenite Cu9S5

Chalcocite Cu2SMalachite CuCO3.Cu(OH)2Azurite Cu2(CO3)2.Cu(OH)2Cuprite Cu2OTenorite Cu0Chrysocolla (Cu,Al)2H2Si2O5(OH)4.nH2ONative copper Cu

Development and optimization of mixed sulphide/oxide copper ore treatment at Kansanshi

and Chander, 1992).The sulphidizer concentration can becontrolled by measuring the Es potential of the pulp, using asulphide ion-selective electrode. The reaction between thesulphidizer and the malachite is optimum at an Es potentialof -500 mV (Jones and Woodcock, 1978). However, xanthateflotation is depressed at this potential. Oxidation of sulphideions in excess by aeration (running air through a laboratorycell as the potential is allowed to rise) for two minutes is thennecessary to reach the optimal potential of -300 mV (Ferronand Manu, 1994). This leads to the formation of reducingagents such as thiosulphates, which are not necessarilyindifferent in the flotation process (Soto and Laskowski,1973; Castro et al., 1974).

Direct collectors such as fatty acids and hydroxamateshave also been developed for the flotation of oxide minerals(Lee et al., 1998, 2009). The fatty acids have the drawbackof being unselective over the carbonated gangue mineralsand are therefore unsuitable for the Kansanshi mixed ores.Paquot et al. (2009) demonstrated the advantage of thesulphidization route over direct hydroxamate flotation.

In June 2009, a new processing route involving controlledpotential sulphidization (CPS) was successfully commissionedfor the treatment of the Kansanshi transitional ore. Since thecommissioning of the CPS plant, hundreds of flotation testshave been conducted on flotation feed and final tails, undervarious plant conditions, in order to compare the performanceof the plant with that under ideal conditions in the laboratory.Based on this test work, the decision was taken to increasethe flotation capacity. In 2011, an extension of the CPS plantwas commissioned to increase the number of sulphidizationsteps. This presentation describes the effect of the mineralogyon the variability of the plant performance, and explains thephilosophy that led to the extension of the plant.

Figure 1 depicts the flow sheet of the plant. The first twocells, which are 150 m3, are dedicated for the flotation ofsulphides in the mixed ores. The tailings from these two floatcells are then fed into a 50 m3 sulphidization tank for two

minutes of conditioning at Es of -500 mV. This isimmediately followed by a similarly sized collectorconditioning tank. This assemblage of sulphidizerconditioning tank, collector conditioning tank, and two floatcells essentially forms a CPS stage. The whole bank of sixcells and two sets of conditioning tanks results in residencetime of around 25 minutes. The rougher and scavengerconcentrates produced are further treated to match therequisite final concentrate grade at a minimum of 25% copperin concentrate.

Semi-quantitative mineralogical analyses were performed byoptical microscopy, under crossed polarized light, at thelaboratory of Minerals Engineering and Recycling of theUniversity of Liege (Belgium). Different sets of compositesamples, corresponding to various styles of mineralizationand plant performances, were examined. Only the particlesize fractions coarser than 38 μm were analysed.Mineralogical classes were defined according to mineralogy,textures, and gangue relationships. A specific gravity andcopper content was attributed to each class in order tocalculate the copper distribution between the different classesfor each sample and within the flotation circuit.

For each flotation test, NaHS from the batch mixed in theplant during the corresponding day was dissolved in rawwater to obtain a 2% solution. The xanthate (PAX or SIBX)was used as a 1% w/v solution, 2 minutes’ conditioning time,and the frother (dipropylene glycol methyl ether) was dosedby drops, as supplied.

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The flotation tests were done using a laboratory Essaflotation machine with a 2.5 L cell. Charges of 1 kg were usedin order to obtain a pulp density of 32% solids. The impellerspeed was fixed at 800 r/min. The Es of the slurry wascontrolled with a silver/sulphide combination electrode.

Grab samples of flotation feed and final tails were collected atthe same time to evaluate the hourly plant performance. Fortests on flotation feed, the number of flotation stages wasequal to the number of plant flotation stages. To reflect theplant conditions, no sulphidizer was added in the firstflotation stage. The first flotation stage on the final tails wasdone without adding any reagents, and the second stage withan extra suphidization step. The flotation time for each stageof the laboratory tests was determined applying a scale-downfactor of 2.5 to the plant residence time. For each CPS stage,the pulp Es potential was maintained at -500 mV for apredetermined time, in order to obtain the same dosage as inthe plant, before adding the collector and frother. Air wasadded at no particular rate but just at a practical andadequate level to have froth flowing over.

Air was not particularly controlled and was used to oxidizeexcessive NaHS (sulphide ions) to maintain the Es in thenormal range for xanthate flotation, which is around -300mV. Despite excessive oxidation of sulphidizer, consumptionfor NaHS was still 20% lower.

Table II shows the main mineralogical classes that wereestablished on the plant composite samples, according tomineralogy, textures, and gangue relationships.

Figures 2–5 illustrate some of the classes established anddemonstrate the high variability of the Kansanshi transitionalore mineralization. Liberation in fractions coarser than 38 μmis between 90 and 95%. Only very small amount of dissem-inated chalcopyrite can be locked in gangue minerals.Chalcopyrite can be liberated, or in association with covelite,


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Chalcopyrite CpChalcocite CcCovellite CvChalcopyrite partially replaced by secondary sulphides (covelite, digenite and chalcocite) Cp+Cv+Dg+CcChalcopyrite partially replaced by secondary sulphides and associated with iron oxides and hydroxides Cp+Cv+Dg+CcNon-liberated chalcopyrite Cp+gangueMalachite malMalachite associated with iron oxides and hydroxides mal+FeoxChrysocolla Ch


digenite, chalcocite, goethite, and even malachite. Liberatedporous or non-porous chalcocite is observed. Malachite canalso be liberated or associated with Iron hydroxides, and theproportion of native copper, partially altered to cuprite, is notalways negligible.

Table III compares the average recovery in the plant forparticles coarser than 38 μm of the main classes in theroughing stage, where no sulphidizer is added, with the totalrecovery obtained after controlled potential sulphidization.

For the sulphide minerals, the best recoveries in theroughing stage are achieved for chalcocite or chalcopyritepartially altered to secondary sulphides (64 to 65%).Liberated chalcopyrite has an intermediate floatability, withonly 43% recovered in the roughing stage. Covellite also hasa poor floatability (48% recovered in the roughing stage).

Even after sulphidization, liberated chalcopyrite and covelliteare the sulphide species displaying lower recovery.

Formation of iron oxides and hydroxides on some of theparticles of chalcopyrite, altered to secondary sulphides,affects their floatability. Only 50% of the liberated malachiteis recovered. Malachite associated with iron oxides andhydroxides is not recoverable. Table IV shows the contri-bution of each mineralogical class to the copper losses in thefinal tails of the plant.

Copper losses in final tails, attributed to liberatedchalcopyrite and malachite that should be recoverable ifproperly sulphidized, are 16% and 28% respectively.Malachite associated with iron oxides and hydroxides alsocontributes to a significant proportion of losses (20%). Theselosses are attributed mainly to sulphidization efficiency.

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1256

Cp 42.95 86.59Cc 63.63 90.32Cv 47.51 70.54Cp+Cv+Dg+Cc 65.44 92.52Cp+Cv+Dg+Cc+Fe 26.91 74.41Cp+gangue 0.00 0.00mal 1.73 49.75mal+Feox 0.00 0.00Ch 1.35 28.68

Cp 14.57Cc 3.86Cv 7.33Cp+Cv+Dg+Cc 3.30Cp+Cv+Dg+Cc+Fe 6.02Cp+gangue 9.75mal 28.03mal+Feox 19.98Ch 6.16Total 99.00

The very high variations in grades of the Kansanshi transi-tional ores (from 0.5% to 3% for the TCu and from 0.1% to1.5% for the AsCu) are ideal for modelling. Multivariablestatistical analysis showed that the laboratory and plantperformance, in terms of TCu grade of the final tails, isdependent on TCu and AsCu feed grades.

Robust multilinear regressions, using iterativelyreweighted least squares, were used for the modelling of theplant flotation final tails and laboratory flotation tails. Thecombined correlation coefficients are given in Table V.Modelling of the recoveries can be done based on theestimation of the TCu tails grade and the well-known two-products formula assuming a constant concentrate grade.

Figure 6 shows the difference between the modelsestablished for the laboratory and plant recoveries. Thedifference after refloating the tails is very low for the low feedgrades and reaches a maximum of 10% for the highest feedgrades and lower AsCu proportions, the average being 9%.This difference is explained mainly by the more optimalhydrodynamic conditions of the laboratory flotation cell. Forthe same TCu feed grade, the difference decreases with theincrease in the AsCu feed grade. Unit laboratory reagentdosages were similar to plant dosage rates. The fact that theimprovement in recoveries is lower for higher proportions ofAsCu shows that more sulphidization steps are necessary toachieve the optimal recovery.

The same considerations as for the modelling of the plant andlaboratory performance on the feed were applied for the testson the final tails. Flotation test tails grade, obtained when re-floating the plant final tails with or without an additionalsulphidization step, still depends of the TCu and AsCu feedgrades. Multilinear regressions, using iteratively reweightedleast squares, were used for the modelling of the laboratoryflotation tails grades. Correlation coefficients are given inTable VI. Recoveries were estimated using the two-productformula assuming a constant final concentrate of 26% copper.

Figure 7 shows the additional recovery obtained when

floating the plant flotation tails without any additionalreagents and with an additional sulphidization step.

Plant recovery can be increased by an average of 5%when re-floating plant final tails in one flotation step withoutadding any reagents, the upgrade being 15. The lower thefeed grades and the higher the AsCu proportion, the less isthe improvement. After an additional sulphidization step,recovery can be increased by an average of 10%, the upgradebeing 16. The higher the AsCu proportion the greater theimprovement. These observations confirm the resultsobtained when comparing the laboratory and the plantperformances on the flotation feed. Performance of the plantis then affected not only by the hydrodynamics of the cellsand the residence time, but also by a lack of sulphidizationsteps. An increase of 5% recovery is achievable by increasingplant residence time by 20 minutes and a further 5% byadding two more sulphidization stages.

The very variable performances of the new Kansanshi transi-


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Plant final tails 0.72Laboratory flotation tails 0.73

Without additional reagents 0.70With additional sulphidization step 0.62


tional ore processing route are explained by the complexity ofthe mineralization. All the minerals constituting the alterationsequence, from primary copper sulphide minerals to oxideminerals, are present in the Kansanshi ores in variableproportions. A detailed optical mineralogical analysis on plantcomposite samples, corresponding to various mineralizationclasses and plant performance, showed that the sulphideminerals displaying the best floatability in the roughingstage, where no sulphidizer is added, are the chalcocite orchalcopyrite partially altered in chalcocite and othersecondary sulphides. Liberated chalcopyrite is mainlyrecovered together with the malachite in the controlledpotential sulphidization section. Final copper losses areattributed mainly to liberated chalcopyrite and malachite thatshould be recoverable. Flotation tests on the plant flotationfeed and final tails were used to establish models of thedifference between laboratory and plant performance, and ofthe improvement in recoveries when re-floating the plantfinal tails with and without an additional sulphidization step.The difference between laboratory and plant performanceaverages 9% and decreases with low feed grades and highAsCu feed grade proportions. The improvement when re-floating the plant final tails without additional reagentsaverages 5%, and decreases with low feed grades and highAsCu feed grade proportions. The improvement when re-floating the plant final tails with an additional sulphidizationstep averages 10% and increases with high AsCu proportions.This test work showed that an increase of 10% of recoveryshould be achievable by increasing plant residence time andthe number of sulphidization stages.

CASTRO, S., SOTO, H., GOLDFARB, J., and LASKOWSKI, J. 1973. Sulphidizingreactions in the flotation of oxidized copper mineral, II. Role of theadsorption and oxidation of sodium sulphide in the flotation ofchrysocolla and malachite. International Journal of Mineral Processing,vol. 1. pp 151–161.

CROZIER, R.D. 1991. Flotation, Theory, Reagents and Ore Testing. PergamonPress.

DUNN, J.G. and MUZENDA, C. 2001. Thermal oxidation of covellite (CuS).Thermochimica Acta, vol. 369, no. 1-2. pp 117–123.

FERRON, C.J. and MANU, N.N. 1994. Recovery of copper oxide minerals bysulfidization flotation. Lakefield Research, Canada. 11 pp.

Lee, J.S., Nagaraj, D.R., and Coe, J.E. 1998. Practical aspects of oxide copperrecovery with alkyl hydroxamates. Minerals Engineering, vol. 11, no. 10.pp. 929-939.

LEE, K., ARCHIBALD, D., MCLEAN, J., and REUTER, M.A. 2009. Flotation of mixedcopper and sulphide minerals with xanthate and hydroxamate collectors.Minerals Engineering, vol. 22. pp. 395–401.

JONES, M.H. and WOODCOCK, J.T. 1978. Optimization and control of laboratorysulphidization of oxidized copper ores with an ion selective electrode.Proceedings of the Australasian Institute of Mining and Metallurgy, no.266. pp. 11–17.

KONGOLO, K., KIPOKA, M., MINANGA, K., and MPOYO, M., 2003. Improvingefficiency of oxide-cobalt ores flotation by combination of sulphidisers.Minerals Engineering, vol. 16. pp. 1023–1026.

MWENA, M.D. and MPOYO, M., 2001. Improvements of cobalt recovery inflotation of cupro-cobaltiferous ore at Gecamines. Proceedings of theCopper Cobalt Nickel and Zinc Recovery Conference, Victoria Falls,Zimbabwe, 16–18 July, 2001. Southern African Institute of Mining andMetallurgy (Zimbabwe Branch). pp. 1–9.

NEWELL, A.J., SKINNER, W.M., and BRADSHAW, D.J. 2006. Restoring the floatabilityof oxidized sulfides using sulfidisation. International Journal of MineralProcessing, vol. 84. pp. 108–107.

PAQUOT, F.X., BASTIN, D., MUKUTUMA, A., and DELANEY, A. 2009. Metallurgicalperformances of the sulphidization route and the direct alkyl hydrox-amates flotation of mixed carbonated copper-gold ores of the Kansanshideposit. Flotation 09, Cape Town, South Africa, 9–12 November 2009.Minerals Engineering International, Falmouth, UK.

RAGHAVAN, S., ADAMEC, E., and LEE, L. 1984. Sulfidization and flotation ofchrysocolla and brochantite. International Journal of Mineral Processing,vol. 12. pp. 173–191.

WOODS, R. 2003. Electrochemical potential controlling flotation. InternationalJournal of Mineral Processing, vol. 72. pp. 151–162. ◆

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201615–16 February 2016 — Global MiningStandards and Guidelines Group ‘GMSG—SAIMM Forum 2016: Building towards thefuture of mining’Emperor’s Palace, Johannesburg, GautengContact: Raymond van der BergTel: +27 11 834-1273/7Fax: +27 11 838-5923/833-8156E-mail: [email protected]: http://www.saimm.co.za

14–17 March 2016 — Diamonds still Sparkle2016 Conference Gaborone International Convention CentreContact: Yolanda RamokgadiTel: +27 11 834-1273/7Fax: +27 11 838-5923/833-8156 E-mail: [email protected]: http://www.saimm.co.za

17–18 May 2016 — The SAMREC/SAMVALCompanion Volume ConferenceJohannesburgContact: Raymond van der BergTel: +27 11 834-1273/7Fax: +27 11 838-5923/833-8156E-mail: [email protected]: http://www.saimm.co.za

21–28 May 2016 — ALTA 2016Perth, Western AustraliaContact: Allison TaylorTel: +61 (0) 411 692 442E-mail: [email protected]: http://www.altamet.com.au

9–10 June 2016 — New technology andinnovation in the Minerals Industry ColloquiumMintek, RandburgContact: Camielah JardineTel: +27 11 834-1273/7Fax: +27 11 838-5923/833-8156 E-mail: [email protected]: http://www.saimm.co.za

27–28 June 2016 — The 2nd School onManganese Ferroalloy ProductionJohannesburgContact: Yolanda RamokgadiTel: +27 11 834-1273/7Fax: +27 11 838-5923/833-8156 E-mail: [email protected]: http://www.saimm.co.za

13–15 July 2016 — Resilience in the MiningIndustry Conference 2016University of PretoriaContact: Camielah JardineTel: +27 11 834-1273/7Fax: +27 11 838-5923/833-8156 E-mail: [email protected]: http://www.saimm.co.za

1–3 August 2016 — HydrometallurgyConference 2016‘Sustainability and the Environment’in collaboration with MinProc and the WesternCape BranchCape TownContact: Yolanda RamokgadiTel: +27 11 834-1273/7Fax: +27 11 838-5923/833-8156 E-mail: [email protected]: http://www.saimm.co.za

16–18 August 2016 — The Tenth InternationalHeavy Minerals Conference ‘Expanding thehorizon’Sun City, South AfricaContact: Camielah JardineTel: +27 11 834-1273/7Fax: +27 11 838-5923/833-8156 E-mail: [email protected]: http://www.saimm.co.za

12–14 September 2016 — 8th InternationalSymposium on Ground Support in Mining andUnderground ConstructionKulturens Hus – Conference & Congress, Luleå,SwedenContact: Erling NordlundTel: +46-920493535Fax: +46-920491935E-mail: [email protected]: http://groundsupport2016.com

7–11 November 2016 — AMI Ferrous and BaseMetals Development Network Conference 2016MSC Sinfonia Cruise, Durban-Mozambique-DurbanContact: Raymond van der BergTel: +27 11 834-1273/7Fax: +27 11 838-5923/833-8156E-mail: [email protected]: http://www.saimm.co.za

INTERNATIONAL ACTIVITIES

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Company AffiliatesThe following organizations have been admitted to the Institute as Company Affiliates

AECOM SA (Pty) Ltd

AEL Mining Services Limited

Air Liquide (PTY) Ltd

AMEC Mining and Metals

AMIRA International Africa (Pty) Ltd

ANDRITZ Delkor(Pty) Ltd

Anglo Operations Ltd

Anglo Platinum Management Services (Pty) Ltd

Anglogold Ashanti Ltd

Atlas Copco Holdings South Africa (Pty) Limited

Aurecon South Africa (Pty) Ltd

Aveng Moolmans (Pty) Ltd

Axis House (Pty) Ltd

Bafokeng Rasimone Platinum Mine

Barloworld Equipment -Mining

BASF Holdings SA (Pty) Ltd

Bateman Minerals and Metals (Pty) Ltd

BCL Limited

Becker Mining (Pty) Ltd

BedRock Mining Support (Pty) Ltd

Bell Equipment Company (Pty) Ltd

Blue Cube Systems (Pty) Ltd

Bluhm Burton Engineering (Pty) Ltd

Blyvooruitzicht Gold Mining Company Ltd

BSC Resources

CAE Mining (Pty) Limited

Caledonia Mining Corporation

CDM Group

CGG Services SA

Chamber of Mines

Concor Mining

Concor Technicrete

Council for Geoscience Library

CSIR-Natural Resources and theEnvironment

Department of Water Affairs and Forestry

Deutsche Securities (Pty) Ltd

Digby Wells and Associates

Downer EDI Mining

DRA Mineral Projects (Pty) Ltd

DTP Mining

Duraset

Elbroc Mining Products (Pty) Ltd

Engineering and Project Company Ltd

eThekwini Municipality

Exxaro Coal (Pty) Ltd

Exxaro Resources Limited

Fasken Martineau

FLSmidth Minerals (Pty) Ltd

Fluor Daniel SA (Pty) Ltd

Franki Africa (Pty) Ltd Johannesburg

Fraser Alexander Group

Glencore

Goba (Pty) Ltd

Hall Core Drilling (Pty) Ltd

Hatch (Pty) Ltd

Herrenknecht AG

HPE Hydro Power Equipment (Pty) Ltd

Impala Platinum Limited

IMS Engineering (Pty) Ltd

JENNMAR South Africa

Joy Global Inc. (Africa)

Leco Africa (Pty) Limited

Longyear South Africa (Pty) Ltd

Lonmin Plc

Ludowici Africa

Lull Storm Trading (PTY)Ltd T/A WekabaEngineering

Magnetech (Pty) Ltd

Magotteaux(PTY) LTD

MBE Minerals SA Pty Ltd

MCC Contracts (Pty) Ltd

MDM Technical Africa (Pty) Ltd

Metalock Industrial Services Africa (Pty)Ltd

Metorex Limited

Metso Minerals (South Africa) (Pty) Ltd

Minerals Operations Executive (Pty) Ltd

MineRP Holding (Pty) Ltd

Mintek

MIP Process Technologies

Modular Mining Systems Africa (Pty) Ltd

MSA Group (Pty) Ltd

Multotec (Pty) Ltd

Murray and Roberts Cementation

Nalco Africa (Pty) Ltd

Namakwa Sands (Pty) Ltd

New Concept Mining (Pty) Limited

Northam Platinum Ltd - Zondereinde

Osborn Engineered Products SA (Pty) Ltd

Outotec (RSA) (Proprietary) Limited

PANalytical (Pty) Ltd

Paterson and Cooke Consulting Engineers (Pty) Ltd

Polysius A Division Of ThyssenkruppIndustrial Solutions (Pty) Ltd

Precious Metals Refiners

Rand Refinery Limited

Redpath Mining (South Africa) (Pty) Ltd

Rosond (Pty) Ltd

Royal Bafokeng Platinum

Roymec Tecvhnologies (Pty) Ltd

Runge Pincock Minarco Limited

Rustenburg Platinum Mines Limited

SAIEG

Salene Mining (Pty) Ltd

Sandvik Mining and Construction Delmas(Pty) Ltd

Sandvik Mining and Construction RSA(Pty) Ltd

SANIRE

Sasol Mining(Pty) Ltd

Scanmin Africa (Pty) Ltd

Sebilo Resources (Pty) Ltd

SENET

Senmin International (Pty) Ltd

Shaft Sinkers (Pty) Limited

Sibanye Gold (Pty) Ltd

Smec SA

SMS Siemag South Africa (Pty) Ltd

SNC Lavalin (Pty) Ltd

Sound Mining Solutions (Pty) Ltd

South 32

SRK Consulting SA (Pty) Ltd

Technology Innovation Agency

Time Mining and Processing (Pty) Ltd

Tomra Sorting Solutions Mining (Pty) Ltd

Ukwazi Mining Solutions (Pty) Ltd

Umgeni Water

VBKOM Consulting Engineers

Webber Wentzel

Weir Minerals Africa

WorleyParsons (Pty) Ltd

2016� FORUM

Global Mining Standards and Guidelines Group ‘GMSG—SAIMM Forum 2016: Building towards the future ofmining’15–16 February 2016,Emperor’s Palace, Johannesburg, Gauteng

� CONFERENCEDiamonds still Sparkle 2016 Conference 14–17 March 2016, Gaborone International Convention Centre

� CONFERENCEThe SAMREC/SAMVAL Companion Volume Conference17–18 May 2016, Johannesburg

� COLLOQUIUMNew technology and innovation in the Minerals IndustryColloquium9–10 June 2016, Mintek, Randburg

� SCHOOLThe 2nd School on Manganese Ferroalloy Production27–28 June 2016, Johannesburg

� CONFERENCEResilience in the Mining Industry Conference 201613–15 July 2016,University of Pretoria

� CONFERENCEHydrometallurgy Conference 20161–3 August 2016, Cape Town

� CONFERENCEThe Tenth International Heavy Minerals Conference16–18 August 2016, Sun City, South Africa

� CONFERENCEAMI Ferrous and Base Metals Development Network Conference 20167–11 November 2016, MSC Sinfonia Cruise, Durban-Mozambique-Durban

SAIMM DIARY

For further information contact:Conferencing, SAIMM

P O Box 61127, Marshalltown 2107Tel: (011) 834-1273/7

Fax: (011) 833-8156 or (011) 838-5923E-mail: [email protected]

For the past 120 years, theSouthern African Institute ofMining and Metallurgy, has

promoted technical excellence inthe minerals industry. We strive tocontinuously stay at the cuttingedge of new developments in themining and metallurgy industry. TheSAIMM acts as the corporate voicefor the mining and metallurgyindustry in the South Africaneconomy. We actively encouragecontact and networking betweenmembers and the strengthening ofties. The SAIMM offers a variety ofconferences that are designed tobring you technical knowledge andinformation of interest for the goodof the industry. Here is a glimpse ofthe events we have lined up for2016. Visit our website for moreinformation.

Website: http://www.saimm.co.za

EXHIBITS/SPONSORSHIP

Companies wishing to sponsor

and/or exhibit at any of these

events should contact the

conference co-ordinator

as soon as possible

CREATING A SAFE OPERATING ENVIRONMENT WITH OUR SAFETY SPECIALISTS

Sasol places safety at the heart of our workplace. Technology like the Close Proximity Detection System shuts down mining machinery if an employee gets too close, and industry projects which improve methane dilution have been co-developed, initiated and rigorously tested by our specialists.

It’s just a few of the many steps we have taken to create a working environment which is safe, responsible and productive.

www.sasol.com

Saimm 201512 dec

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