Powder Technology 256 (2014) 285–292

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Processing of banded magnetite quartzite (BMQ) ore usingflotation techniques

Hrushikesh Sahoo, Bhagyalaxmi Kar, Swagat S. Rath, D. Srinivas Rao, Bisweswar Das ⁎CSIR-Institute of Minerals and Materials Technology, Bhubaneswar 751013, India

⁎ Corresponding author at: CSIR-IMMT, Bhubaneswar 7E-mail address: bdas@immt.res.in (B. Das).

http://dx.doi.org/10.1016/j.powtec.2014.02.0340032-5910/© 2014 Elsevier B.V. All rights reserved.

a b s t r a c t

a r t i c l e i n f o

Article history:Received 6 April 2013Received in revised form 3 December 2013Accepted 11 February 2014Available online 16 February 2014

Keywords:Banded magnetite quartziteFlotationOleic acidDodecylamineResponse surface methodologyCentral composite rotatable design

Recovery of iron values from bandedmagnetite quartzite (BMQ) ore by direct and reverse flotation technique ispresented. In direct flotation, with oleic acid as the collector, the iron grade in the concentrate that could beachieved is limited to 57% Fe from a feed containing ~47% Fe. The difficulty of concentrating iron values by directflotation technique is due to the fine coating of iron hydroxide over the particles at alkaline pH. In reverse flotation,better selectivity and collectability could be achieved using dodecylamine chloride as the collector. A statisticalmodeling approach called response surface methodology has been undertaken to optimize the reverse flotationprocess tomaximize the iron grade and recovery. All the experiments have been conducted as per the central com-posite rotatable design (CCRD) taking collector, frother, depressant and pH as the factors. The program predicted64.68% Fe with 66.38% recovery at a dodecylamine concentration of 271.88 g/T, MIBC: 40 g/t, starch: 400 g/T andat pH 9.5, which is also validated by the experimental results.

© 2014 Elsevier B.V. All rights reserved.

1. Introduction

Banded magnetite quartzite (BMQ) ore occurs as separate veins iniron ore mines and recovered while mining the natural hematite ore.In India, such ores are considered as low grade iron ores with Fe contentof 25–45%, SiO2 30–60% and Al2O3 1–5%. No commercial plant has beenset up so far to recover the iron values from such ores for any industrialapplications. However, due to the increasing demand of quality iron orefor iron and steel industries and depletion of high grade ores, it becomesmandatory to exploit the low grade ores by suitable beneficiation tech-niques. Recovery of iron values from such low-grade ores is generallyattempted by gravity concentration, magnetic separation and flotationtechniques. In flotation process, quartz from magnetite or hematite isseparated using amines and quaternary ammonium salts as the collector[1–6]. Wide varieties of other collectors such as oleates, sulfonates orsulfates are used in the direct flotation studies [7,8]. Inmost of the stud-ies, it has been observed that either liberation characteristics of themin-erals present in the ore or themolecular structure of the collector playsthe important role in separating the iron minerals from the gangueconstituents. Although flotation technique is a well established indus-trial practice for the separation of mineral values, limited investiga-tions have been made on low grade Indian banded iron ores. Das et al.[9] carried outmagnetic andflotation studies of Indian banded hematite

51013, India.

quartzite (BHQ) ore for the production of pellet grade concentrate.Upadhay et al. [10] presented an extensive study on the mineralogicaland beneficiation aspects of such banded ores available in the eastern re-gion of India. Using selective flocculation method, Panda et al. [11] havebeneficiated banded hematite quartzitewith a feed of 38% Fe to a concen-trate of 64.5% Fe with 92% iron recovery. Kar et al. [12] investigated thecomparative depressant actions of four different types of starches to de-press hematite in BHQ. However, to the best of our knowledge, literaturerelated to the flotation aspects of the BMQ ore is not available. The pur-pose of this investigation is, therefore, to find out a possible approach byflotation techniques, for the beneficiation of the typical BMQore availablein most of the iron mines in India.

In this context, statistical design of experiments has been employed toconduct the flotation experiments using dodecylamine as the collector.Designed experiments save resources, and on the other hand, it estimatesthe effects of individual factors and their interactions in a precisemanner.Process optimization becomes more efficient as the optimal solution issearchedover entire factor space [13,14]. Recently Rath et al. [15] used re-sponse surface methodology to optimize the process variables for BHQflotation using oleic acid as the collector. Effect of different variablesand interactions were studied, and it was possible to recover the Fegrade of 65% at 67% recovery under optimum conditions. Optimizationof many flotation studies such as coal [16], celestite and calcite [17] hasbeen carried out to verify the response of different parameters. Thesestudies were able to achieve reliable solutions after carrying out the ex-periments as per statistical design. Statistical evaluation studies werealso employed to evaluate the effect of different flotation collectors

Fig. 1. Particle size distribution of roll crushed ore (a) and the ground sample (b).

286 H. Sahoo et al. / Powder Technology 256 (2014) 285–292

such as polyamine on complex sulfide ores [18], thionocarbamates incopper flotation [19] and sphalerite flotation from a low-grade Zn–Pbore [20].

The functional relationship of the flotation factors such as pH,collector, depressant and frother with the responses such as Fe gradeand Fe recovery has been established using the combined approach ofcentral composite rotatable design (CCRD) and response surface meth-odology (RSM). The main objective of the study is to obtain the maxi-mum iron grade and recovery by optimizing different operatingvariables.

2. Materials and methods

About 500 kg of low grade BMQ ore was obtained from Hospet,Karnataka, India for the detailed characterization and beneficiationstudies. The sample was visibly black and attracted to a bar magnet.The average size of the as received ore was around 35mm. All the char-acterization and beneficiation studies were carried out with the repre-sentative sample after crushing and grinding by standard laboratoryequipments to the desired size. Particle size distribution of the rollcrushed ore along corresponding iron content is shown in Fig. 1(a). It in-dicates that the size fraction of −100 + 45 μm contains the maximumiron content. Therefore, the sample was ground to below−100 μm forflotation experiments. Fig. 1(b) displays the particle size distribution ofthe ground ore.

Denver D-12 sub aeration flotation machine with 2 l capacity cellwas used for the batch flotation studies. For direct flotation studies,

Fig. 2. Schematic diagram of experimental set-up.

oleic acid, sodium silicate and MIBC were used as the collector, disper-sant and frother respectively. The reverse flotation studies were carriedout by using dodecylamine as the collector and starch as the depressant.All the studies were carried out at ~25% solids concentration. Theconcentrate and tailing were collected separately, dried, weighed andanalyzed for iron content to assess the product quality and yield. Aschematic diagram of the over all process is presented in Fig. 2.

3. Results and discussion

3.1. Physico-chemical characterization

The BMQ sample is hard, massive and laminated in nature. Thetextural and microstructural features of hand specimen are micro-bands and microfolds. The banded magnetite quartzite sample onan average contains ~47% Fe, 34.5% SiO2, and 1.15% Al2O3. The silicais found to be the major impurity present in the sample. The Bond'sgrindability index of the sample was determined as per the standardprocedure and found to be 12.1 kWh/t. The XRD studies of the BMQsample (Fig. 3) indicated that the sample mainly contains magnetiteand hematite as the iron bearing minerals along with quartz as themajor impurity.

Mineralogically the sample also contains three different phases viz.magnetite, hematite and quartz. The reflectedmicroscopic studies indi-cate the inclusion of both quartz and hematite with magnetite (Fig. 4a).Magnetite occurs either as independent crystals in the sample or as

Fig. 3. XRD analysis of banded magnetite quartzite sample.

Fig. 4. (a) The silicates and hematite inclusions with magnetite. (b) Magnetite crystals occur in the sample either as clusters/bunches of magnetite or are present as independent crystalswithin the silicate.

287H. Sahoo et al. / Powder Technology 256 (2014) 285–292

clusters within the quartz (Fig. 4b). Hence it was necessary to grind thesample to a very fine size to liberate the mineral values.

3.2. Direct and reverse flotation studies

The result of flotation studies using oleic acid as the collector isshown in Fig. 5. Effect of pH was studied at the particle size of 75 μmand oleic acid concentration of 200 g/t. Sodium silicate (200 g/t) andMIBC (40 g/t) were used as the dispersant and the frother respectively.Under these conditions, it was observed that a maximum Fe grade of55% with 58% recovery could be obtained at pH 9. Further, the effect ofoleic acid concentration at different particle sizes was studied atpH 8.5–9 using sodium silicate (200 g/t) and MIBC (40 g/t). MaximumFe grade that could be achieved was limited to 56–57% Fe, indicatingthat BMQ ore is less responsive to direct flotation tests. As the concen-tration of iron could not be enhanced further, reverse cationic flotationusing dodecylamine as the collector was attempted. In reverse flotation,amines as the functional group arewidely used as theflotation collector.The amines generally dissociate in water and induce strong adsorptionwith quartz particles [21]. It has been observed that the selectivityof amines is basically due to their large radical size and high electro-negativity [22]. In reverse flotation, the quartz particles are floatedwhile the hematite or goethite present in the ore is depressed withthe help of starch [23]. Soluble starch was used as the depressantfor iron oxide minerals as it is the universal depressant in iron oreflotation [24,25]. In the present study, the reverse flotation behaviorof BMQ ore at different dodecylamine (DDA) concentrations isshown in Fig. 6. All the experiments were conducted in natural pHusing 400 g/t of soluble starch as the depressant and 40 g/t of MIBC

Fig. 5. Direct flotation of BMQ ore with pH variation (a) and Oleic

as the frother while the concentration of DDA was varied from 16to 600 g/t. It was observed that the grade of iron increases from48.33% to 67.5%with an increase in DDA concentrationwhile the recov-ery of iron values decreased from93.69% to 28.55. AtDDA concentrationof 400 g/t, an iron concentration of 63%Fe with 68.9% recovery could beachieved and considered as the best result.

Investigations were carried out to find out the possible reason forless response of BMQore to directflotation using oleic acid as the collec-tor. In this regard, the morphology of different samples by scanningelectron microscopy was studied. The SEM photograph of groundBMQ ore and the ore treated with dodecylamine at pH 7.0 and oleicacid at pH 9.5 is shown in Fig. 7. It was observed that the morphologyof ground BMQ sample and the one treated with amine remain moreor less the same. The slight change of particle shape and size was dueto the coating of amines on the surface of quartz (Fig. 7a and b). Howeverthe SEM photograph of ground BMQ ore adsorbed with oleic acid(Fig. 7c) is completely different from those of the other two. Thedistorted morphology is due to the formation of finely divided ironhydroxides at alkaline pH and simultaneous coating of these fine pre-cipitates over the hematite, magnetite and other minerals surfaces.

Beside that the particle size of quartz and iron minerals in groundBMQ sample was measured using reflected light microphotographyand depicted in Fig. 8. The result suggests that quartz particles are com-paratively coarser than the magnetite and hematite. It was observedthat 40–50% of the quartz particles are in the range of 60 to 90 μmwhile most of the hematite and magnetite grains are below 20 μm insize.

As the iron particles are finer than the quartz particles andmoreoverthe separation by flotation at extremely finer size is not favorable, the

acid as the collector and sodium silicate as the dispersant (b).

0102030405060708090

100

0 100 200 300 400 500 600

Fe

grad

e/re

cove

ry, %

Dodecylamine, g/t

Grade, %

Recovery, %

Fig. 6. Reverse flotation of BMQ orewith dodecylamine as the collector and soluble starchas the depressant.

288 H. Sahoo et al. / Powder Technology 256 (2014) 285–292

grade of iron in direct flotation could not be enhanced tomore than 57%Fe using oleic acid as the collector. On the other hand since the quartzparticles are slightly coarser, they are amenable to flotation by reverseflotation technique.

3.3. Response surface methodology studies for reverse flotation

In order to study the effect of different operating variables and opti-mize the conditions for maximum Fe grade and recovery, the responsesurface methodology was employed. Collector, frother, depressant andpH were treated as the factors (A, B, C and D). Table 1 presents the

Fig. 7. SEM photographs of BMQ sample at different conditions. (a) BM

Fig. 8. Reflected light microphotographs of the BMQ sample showing

input design summary, where the factors have been coded to −1 aslower level, +1 as upper level and 0 as middle level.

The results of theflotation studies as per the central composite rotat-able design are shown in Table 2. As per the design, thirty number of ex-periments were carried out, which included sixteen 2-level factorialpoints, eight axial points and six central points. The axial points haveall of the factors set to 0, the midpoint, except one factor, which hasthe value ±α, where α represents the distance from the center of thedesign space to an axial point.

In order to study the relative influence of factors and their interactionsover the responses, half normal plots were drawn using the 2-levelfactorial points and shown in Fig. 9.

As evident from the half normal plot for the response Fe grade, theterm A: collector concentration has the largest absolute value and it isshowing in the upper right hand section of the graph. Hence it can betermed as the most significant factor for Fe grade. While moving fromright to left, the terms D, AD, AD, BD and BC can be leveled as the factorsor interactions with descending order of significance. Among all theterms, A, D, BD and C have positive effects, whereas the rest havenegative effects on the response. The program performed a Shapiro–Wilk hypothesis [26] test for the normality of the unselected terms onthe effects plot, which gave a p value of 0.233, indicating the proper se-lection of the statistically significant terms and the normal distributionof the remaining terms.

Similarly, half normal plot (Fig 9(b)) was used to choose significanteffects for the response Fe recovery. The term A was found to bethe most significant in deciding the recovery as well. Similarly,Shapiro–Wilk p value of 0.6 indicated the statistical significance of theeffects selection.

Q sample (b) BMQ + Amine (pH 7) (c) BMQ + Oleate (pH 9.5).

the shape and size of quartz, hematite and magnetite particles.

Table 1Design summary.

Factor Name Units Type Subtype Min. Max. −1 actual +1 actual Mean

A Collector, DDA g/t Numeric Continuous 50 850 250.00 650.00 450B Frother, MIBC g/t Numeric Continuous 0 160 40.00 120.00 80C Depressant, starch g/t Numeric Continuous 100 500 200.00 400.00 300D pH Numeric Continuous 7.5 9.5 6.50 10.5 8.5

Table 2Results of central composite rotatable design.

Factor 1 Factor 2 Factor 3 Factor 4 Response 1 Response 2

Std Type A: Collector B: Frother C: Starch D: pH Fe grade Fe recovery

g/t g/t g/t % %

1 Factorial 250 40 200 7.5 56.73 61.472 Factorial 650 40 200 7.5 66.47 32.683 Factorial 250 120 200 7.5 57.22 56.874 Factorial 650 120 200 7.5 63.77 45.235 Factorial 250 40 400 7.5 60.36 69.016 Factorial 650 40 400 7.5 68.77 36.427 Factorial 250 120 400 7.5 53.27 60.808 Factorial 650 120 400 7.5 64.72 41.289 Factorial 250 40 200 9.5 63.27 67.6110 Factorial 650 40 200 9.5 67.52 17.3211 Factorial 250 120 200 9.5 67.08 50.9312 Factorial 650 120 200 9.5 69.71 32.9013 Factorial 250 40 400 9.5 64.75 70.3014 Factorial 650 40 400 9.5 67.48 34.4915 Factorial 250 120 400 9.5 66.33 59.4416 Factorial 650 120 400 9.5 68.26 27.1417 Axial 50 80 300 8.5 55.40 73.6018 Axial 850 80 300 8.5 66.81 2.8619 Axial 450 0 300 8.5 68.68 32.5320 Axial 450 160 300 8.5 68.58 12.7321 Axial 450 80 100 8.5 68.78 17.3922 Axial 450 80 500 8.5 68.19 17.7123 Axial 450 80 300 6.5 52.91 47.5724 Axial 450 80 300 10.5 49.68 78.9025 Center 450 80 300 8.5 67.71 8.2326 Center 450 80 300 8.5 68.12 10.5027 Center 450 80 300 8.5 68.20 9.4128 Center 450 80 300 8.5 67.20 10.8029 Center 450 80 300 8.5 68.50 9.8030 Center 450 80 300 8.5 67.90 10.20

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Results of the designed experiments were used to develop regres-sion models for both responses. Two quadratic empirical models weredeveloped for the responses Fe grade and Fe recovery. Table 3 presentsthe ANOVA for Fe grade. The Model-F value of 105.079 implies that the

Fig. 9. Half normal plot for a) Fe

model is significant. There can be only 0.01% probability that this“Model F-value” could occur because of noise. Values of “Prob N F” lessthan 0.05 implies that the model terms are significant. The “Lack of FitF” value is 2.054. This hints the model to be significant as the lack of

grade and b) Fe recovery.

Table 3ANOVA for Fe grade.

Sum of Mean F p-Value

Source Squares df Square Value Prob N F

Model 400 11 36.33683294 105.079459 b0.0001 SignificantA — collector 168 1 168.4477129 487.119903 b0.0001B — frother 0.06 1 0.055971172 0.16185837 0.6931C — depressant 0.94 1 0.940079862 2.71853861 0.1200D — pH 83.7 1 83.67237577 241.96517 b0.0001AB 2.36 1 2.356579332 6.81479538 0.0197AD 23.3 1 23.29379868 67.3613951 b0.0001BC 4.04 1 4.042922278 11.69139 0.0038BD 17.2 1 17.20683296 49.7590063 b0.0001CD 3.21 1 3.2072601 9.2748082 0.0082A2 83.5 1 83.53243744 241.560494 b0.0001D2 26.7 1 26.71708705 77.2609175 b0.0001

Residual 5.19 15 0.345803388Lack of fit 4.17 10 0.417173254 2.05439643 0.2209 Not significantPure error 1.02 5 0.203063657Cor total 405 26

Table 4Details of the models developed.

Name of the response Model developed

Fe grade Fe grade = 68.18 + 2.77A − 0.05B + 0.21C + 2.44D − 0.41AB −1.29AD − 0.54BC + 1.11BD − 0.48CD − 1.77A2 − 2.06D2

Std. dev. 0.59 R2 0.987Mean 65.8 Adj. R2 0.977C.V. % 0.89 Pred. R2 0.955PRESS 18.08 Adeq. precision 36.17

Fe recovery Fe recovery = 11.88 − 15.17A − 2.5B + 1.26C − 2.37D +4.48AB − 3.1AD + 6.59A2 + 2.69B2 + 26.2D2

Std. dev. 5.3 R2 0.962Mean 34.06 Adj. R2 0.945C.V. % 15.56 Pred. R2 0.865PRESS 1797.96 Adeq. precision 20.38

290 H. Sahoo et al. / Powder Technology 256 (2014) 285–292

fit is not significantly relative to the pure error, which is good for themodel. The predicted R2 value for the model was found to be 0.955.This is in reasonable agreement with adjusted R2 i.e. 0.977. “AdeqPrecision”, which measures signal to noise ratio, should be greaterthan 4. For Fe grade model, the “Adeq Precision” was found to be36.17, which indicates an adequate signal, which further suggests thatthis model can be used to navigate the design space. Similar studieswere carried out for the model developed for Fe recovery and thequadratic model was found to be significant. Details of both the modeldeveloped are shown in Table 4.

Predicted vs. actual plots for both the responses have been given inFig. 10, which show reasonably good agreement between the experi-mental and predicted data.

Fig. 10. Predicted vs. actual plot for the model

The models were used to predict the effect of different factors overFe grade and recovery while varying only one of them and keepingthe rest constant. The factors were fixed at collector: 250 g/t, frother:40 g/t, depressant: 200 g/t, and pH: 8.5 unless otherwise stated.Fig. 11 shows the effect of collector, frother, depressant and pH as pre-dicted by the model.

The Nelder–Mead multidimensional pattern search technique, in-built with the software design expert, was used for the optimizationstudy to achieve the maximum grade as well as recovery. The programpredicted an Fe grade of 64.68% and Fe recovery of 66.38% with condi-tions such as collector concentration: 271.88 g/t, frother: 40 g/t, depres-sant concentration: 400 g/t and pH: 9.5. Fig. 12 shows the threedimensional quadratic response surface for Fe grade with the collector

developed for a) Fe grade b) Fe recovery.

0

5

10

15

20

25

30

35

40

45

50

62

63

64

65

66

67

68

250 300 350 400 450 500

Fe

reco

very

, %

Fe

grad

e, %

Collector conc, g/t

Fe grade

Fe recovery

25

27

29

31

33

35

37

39

41

43

45

60

60.5

61

61.5

62

62.5

63

63.5

64

64.5

65

40 60 80 100 120 140

Fe

reco

very

, %

Fe

grad

e, %

Frother conc, g/t

Fe grade

Fe recovery

42

42.2

42.4

42.6

42.8

43

43.2

43.4

62

62.5

63

63.5

64

64.5

200 250 300 350 400 450

Fe

reco

very

, %

Fe

grad

e, %

Depressant, g/t

Fe grade

Fe recovery

30

35

40

45

50

55

60

65

70

75

80

55

56

57

58

59

60

61

62

63

64

65

7.5 8 8.5 9 9.5 10

Fe

reco

very

, %

Fe

grad

e/re

cove

ry, %

pH

Fe grade

Fe recovery

Fig. 11. Effect of individual factors over the responses as predicted by the model.

291H. Sahoo et al. / Powder Technology 256 (2014) 285–292

and frother concentration as X1 and X2 axes, whereas dispersant andpH have been taken as the actual factors. Similarly, Fig. 13 representsthe contour diagram for the Fe recovery. The collector and frotherconcentration have been taken as X1 and X2 axes. The diagramshows different contour lines, across which the response functionhas a constant value. Contour lines for Fe recoveries such as 30%,40%, 50% and 60% have been shown. The prediction for themaximumvalue of 66.38% has been flagged. Experimental verification of thestudy was done by carrying out an experiment with the suggestedvalues of different parameters. Results for Fe grade and Fe recoverywere found to be 65% and 67% respectively, which validated themodel very well.

Fig. 12. 3D diagram showing th

4. Conclusions

The flotation studies of BMQ ore containing 47% Fe, 34.5% SiO2, and1.15% Al2O3 using oleic acid and dodecylamine as the collectors have in-dicated that the ore ismore favorable to cationic collector in comparisonto anionic one. In anionic flotation, the maximum iron that could beachieved is limited to 57% Fe only. The preliminary studies usingdodecylamine has indicated that it is possible to achieve 63% Fe with68.9% iron recovery. A systematic approach to get the maximum irongrade and recovery was carried out by response surface methodology.The results indicated that flotation response is strongly dependent onthe collector concentration andpHof the slurry, whereas the interaction

e optimization of Fe grade.

Fig. 13. Contour diagram showing the optimization of Fe recovery.

292 H. Sahoo et al. / Powder Technology 256 (2014) 285–292

of frother with the collector and pH also played a key role. The modelpredicted a Fe grade of 65% and Fe recovery of 66% with a collectorconcentration: 271.88 g/T, frother: 40 g/t, depressant concentration:400 g/T and pH: 9.5. Results predicted by the statistical modelingstudies were almost found to be in good agreement with the experi-mental observations.

Acknowledgments

The authors are thankful to the Director of CSIR-Institute of Mineralsand Materials Technology, Bhubaneswar, India for his kind permissionto publish this paper.

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