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UNCORRECTED PROOFS

Adsorptive Removal of Dyes from Synthetic and Real Textile

Wastewater Using Magnetic Iron Oxide Nanoparticles:

Thermodynamic and Mechanistic Insights

Q1Nashaat N. Nassar,1,2* Nedal N. Marei,1,2 Gerardo Vitale1 and Laith A. Arar2

1. Department of Chemical and Petroleum Engineering, University of Calgary, 2500 University Drive Northwest, Calgary, AB,T2N 1N4, Canada

2. Department of Chemical Engineering, An-Najah National University, P.O. Box 7, Nablus, Palestine

Magnetic iron-oxide nanoparticles exhibit high efficiency in wastewater treatment for many important reasons, including that they can removecontaminants from wastewater rapidly owing to their high external surface area/unit mass and interstice reactivity. Additionally, this type of ironoxide can easily be separated using a magnet after finishing the treatment process, can be used as a catalyst for the decomposition of adsorbedcontaminants and thus reduce sludge formation, and can cost-effectivelymeet the environmental regulations for wastewater treatment since it canbe prepared in situ where treatment is needed via various techniques. In this study, we use magnetic iron oxide nanoparticles for dye removal fromsynthetic and real textile wastewater for the first time. The effects of different experimental parameters on dye removal, such as contact time, initialconcentration, solution pH, and coexisting ions, were investigated. Computational modelling of the interaction of different dye molecules withdifferent surfaces of g-Fe2O3 nanoparticles is performed to obtain more mechanistic insights on the adsorption behaviour. The results showed thatdye adsorptionwas fast, as external adsorptionwas dominated. The adsorption equilibriumdata fit very closely to the Langmuir adsorption isothermmodel, confirming monolayer adsorption, which is supported by the adsorption computational calculations. The adsorption was spontaneous,endothermic, and physical in nature.

Keywords: textile, adsorption, nanoparticles, iron oxide, wastewater, maghemite

INTRODUCTION

The textile industry is one of the traditional and most-widelypracticed industries in theMiddle East. This industry, whichis a major consumer of fresh water, discharges significant

amounts of colours and organic dyestuffs in its effluents.[1] Thepresence of these compounds in wastewater presents an environ-mental concernbecause these compounds arenot just toxic (evenatvery low concentrations, < 1mg/L), but also non-biodegradable,thus, theywill exist for a long time in theenvironment.[2] Therefore,removing dye compounds from wastewater is essential beforedischarging them into water bodies. Various dyes with complexchemical structures primarily based on aromatic, heterocyclic, andazo compounds, such as aromatic amine (C6H5-NH2), phenyl(C6H5CH2), naphthyl (C10H7CH2), and azo (-N¼N-) groups, arewell-known in literature.[3–8] These compounds are hard to removeor treat with conventional biological treatment methods.[9] Anumber of conventional chemical and physical treatment methodshave been reported for decolourization of textile wastewater,including coagulation-flocculation, precipitation, advanced oxida-tion, ion exchange, membrane filtration, adsorption onto activatedcarbon and low cost adsorbents, etc.[1,4–6,10–12] However, theseconventional treatmentmethods suffer from high cost and inabilityto meet permissible disposal levels. Sorption has been widely usedfor the removal of different dyes and other hazardous species fromwastewater using common sorbents, including activated carbon,zeolites, and those prepared from industrial solid byproducts.[13]

However, some common adsorbents suffer from low adsorptionaffinity, selectivity, and capacity.[13,14] In addition, most of thesetypes of adsorbents show unsatisfactory regeneration and cyclingability,[14] which limits their application on an industrial scale.Magnetic assisted-nanoparticle adsorption technology (i.e., the

technology related to the application of materials at nanoscale,1–100nm) has emerged as an alternative method to commonadsorbents in treating effluentwastewater.[9,15–21]Hence,magneticnanoadsorbents could be employed to rapidly adsorb pollutantsfrom wastewater, and then be easily separated from the mediumusinga simplemagneticfield.Recently, becauseof their unique andunexpected chemical and physical properties compared to itscounterparts, iron-based nanoadsorbents have emerged as analternate source for conventional adsorbents. Properties such asexcellent magnetic behaviour, chemical stability, biocompatibility,amphoteric surface activity, high adsorption capacity, enhancedcatalytic activity, and dispersability have been reported.[20,22–30]

Further, several researchers have reported on the employment ofiron-based nanoadsorbents in removing various pollutants fromwastewater.[19–21,23,31,32] However, to the best of our knowledge,there have been no reports on the application of magnetic assisted-nanoparticle adsorption technology to dye removal from real textilewastewater.

In this work, g-Fe2O3 (maghemite) nanoadsorbents areemployed for the first time in dye removal from a real textilewastewater solution. To understand the adsorption mechanisms,twomodel dyeswith known chemical structureswere explored fortheir adsorptive removal by g-Fe2O3 nanoadsorbents. Further, we

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* Author to whom correspondence may be addressed.E-mail address: nassar@ucalgary.caCan. J. Chem. Eng. 9999:1–11, 2015© 2015 Canadian Society for Chemical EngineeringDOI 10.1002/cjce.22315Published online in Wiley Online Library(wileyonlinelibrary.com).

Journal MSP No. Dispatch: August 21, 2015 CE: Sharin

CJCE 22315 No. of Pages: 11 PE: Tom O'Brien

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carried out computational modelling to provide insights into theinteraction of the model dye molecules with different maghemitesurfaces. The following factors were investigated to find theoptimum conditions for enhancing treatment efficiency:solution pH, contact time, initial concentration, coexistingcontaminants, and temperature. This study provides the potentialapplication of magnetic assisted-nanoparticle technology for dyeremoval from textile wastewater effluent.

EXPERIMENTAL

Adsorbent

Magnetic nanoparticles (g-Fe2O3) purchased from (Alfa Aesar,ON, Canada) were used as an adsorbent. The nanoparticles wereused as received without further purification. The nanoparticleshave a size of 10� 2nm and surface area of 93m2/g. Structure andparticle size were determined using an X-ray Ultima III Multi-Purpose Diffraction System from Rigaku Corp., (The Woodlands,TX)with Cu Ka radiation operating at 40 kV and 44mAwith a u-2ugoniometer. Surface area and pore size distribution weremeasured using a Tristar II 3020 from Micrometrics (Norcross,GA) by performing N2-Physisorption at 77K. Surface area wascalculated using the Brunauer-Emmett-Teller (BET) equation.External surface area was also measured with the t-plot method,and there was no significant difference between the surface areasobtained by BET and t-plot methods, indicating that the selectednanoparticles are non-porous. An estimation of the particle size(assuming spherical particles) was accomplished using the BETmeasured specific surface area and the derived equation d¼ 6000/(SA� roxide);

[33] where d is the particle size in nm, SA is theexperimentally-measured specific surface area (93m2/g), androxide is the density of the maghemite oxide (5.49 g/cm3),producing a value of 11.7 nm which agrees very closely withthe XRD-obtained value.

Figure 1 shows the X-ray diffraction pattern of the selectednanoparticles. The identification of the pattern confirms thematerial to be maghemite, as reported by the manufacturer.The structure was identified by comparing the XRD signals with

those reported in the pdf card 01-073-9835 of the 2005 ICDD(International Centre for Diffraction Data) database included inthe JADEV.7.5.1 program (Materials Data XRD Pattern ProcessingIdentification & Quantification).

Adsorbate

A real textile wastewater sample obtained from Al-Aqad TextileCompany (Nablus, Palestine) was used as a source of realcontaminants. The sample was light blue in colour and free ofsuspended solid particles. Once the sample reached our lab it wasfiltered using a Whatman filter paper to remove any traces ofsuspended solids, then the sample pH, total organic carbon (TOC),chemical oxygen demand (COD), and chromium (Cr3þ) concen-trations were determined (Table 1). The dye structure andchemistry in the real textile wastewater sample are unknown,and the disclosure of any identification or structural analysis wasstrictly prohibited by the supplier. However, as indicated by thesupplier, the dye present in the real textile wastewater sample is ofan ionic type. Hence, to understand the adsorption mechanism,two different model dyes, namely crystal violet (CV, C25N3H30Cl,MW¼ 407.98 g �mol�1, lmax¼ 590nm) and bromocresol green(BCG, C21H14Br4O5S, MW¼ 698.01 g �mol�1, lmax¼ 617nm),were obtained from Sigma-Aldrich and used as adsorbatesin preparing synthetic textile wastewater samples. These twosimple dyes have different configurations and contain some ofthe functional groups present in dyes that have been used in thetextile industry.[34] Therefore, themodel dyes provide insights intounderstanding the nature of real textile wastewater and adsorptivebehaviour by the adsorption batch experiment and computationalmodelling. The two dyes were used as received without any

Figure 1. X-ray diffraction pattern of the selected maghemite nanoparticles. Reference data g-Fe2O3 are from Materials Data XRD Pattern ProcessingIdentification & Quantification.

Table 1.Measured properties of the real wastewater sample consideredin this study

Type oftest pH

Temperature(C8)

COD(ppm)

TOC(ppm)

Cr3þ

(ppm)

Value 6.8 25 2582 971 0.0511

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further purification. Distilled water was used for preparing thesynthetic textile wastewater.

Dye Adsorption onto Nanoparticles

A batch adsorption method was employed by exposing about0.10 g of dry mass of g-Fe2O3 nanoparticles to a 10-mL aqueoussolution containing a certain concentration of a specified dye (CVand BCG). Then, the mixture was shaken vigorously by hand fora certain time at a pre-determined temperature and time. For thekinetic study, the aqueous solution containing a 100mg/Lconcentration of each dye and 2582mg/L COD for the case ofreal textile wastewater at 293K and a specified solution pH (CV:10.94, BCG: 2.39, RWW: 6.8) was shaken for a specified timeinterval. To determine the adsorption time required for equili-brium, samples were selected at predetermined time intervalsand analysed for dye and contaminant concentration. ForpH-dependent studies, adsorption pH experiments were con-ducted at 293K and 24 h. 1mol/L concentration of HNO3 or NaOHwas used to adjust the solution pH in a range of 2.5–11. For theisotherm studies, 0.1 g of g-Fe2O3 nanoparticles was added to10mL aqueous solution with model dye concentrations rangingfrom 0–400mg/L, at different temperatures between 293–353K,for 24 h. For the case of the real wastewater (RWW) sample, theisotherm studies were conducted by exposing different massesof nanoparticles ranging from 0.025–0.2 g to a solution of2582mg/L COD at the same temperature range and time intervalof the model dyes. For all experiments, after adsorption,nanoparticles containing the adsorbed dye and other co-existingions were separated by a simple magnet, and the supernatant wasdecanted and transferred for further analysis. The dye concen-tration in the synthetic wastewater was measured by UV-visspectrophotometry (UV-VIS-NIR-3101PC, Shimadzu). For thecase of RWW samples, the chemical oxygen demand (COD)measurements were performed instead, following the USEPAmethod (USEPA, 2013) and using a Digital Reactor Block DRB2000 (HACH, Germany). The COD sample was prepared byadding 1mL deionized water and 1mL supernatant (wastewatersample) to a standard solution from HACH containing 0.65 g/g ofH2SO4, HgSO4, and K2CrO7. Then the solution was transferred totheDRB instrument for2 hat150 8C forCODmonitoring.Deionizedwater was used as a blank in this test. The adsorbed amount of dyeor COD was determined by mass balance.[20,21] An atomicabsorption instrument iCE 3400 (Scientific Thermo, U.S) wasused for determining Crþ3 concentration (a common co-existingcontaminant in textile effluent) before and after adsorption in theRWW sample. A standard solution containing Crþ3 obtained fromRiedel de Hain (Germany) was used for AA calibration. It is worthnoting here that all experiments were performed in duplicate toconfirm reproducibility.

Computational modelling of the interaction of CV and BCG withmaghemite surfaces

Understanding adsorption phenomena is of key importance, andthus we carried out computational modelling to derive insightsinto the interaction of CV and BCG molecules with differentmaghemite surfaces. The computational study was done usingForcite and Adsorption locator within Accelrys Materials Studiosoftware V7.0.[33,35–39] In order to investigate the adsorption ofCV and BCG on maghemite surfaces, the molecules werestructured and optimized with Forcite before adsorbing themon the selected maghemite surfaces. The quality of the GeometryOptimization in Forcite was set to Fine and the Forcefield toCOMPASS. The chemical structures drawn with ChemDraw

V14[40] and the 3-D molecules optimized with Forcite appear inFigure 2. As can be seen in Figures 2b and 2d, the two organicmolecules show a 3-D organization that resembles “fan blades”and differ from the flat configuration on the structural drawings(Figures 2a and 2c).

The structure of g-Fe2O3 (maghemite) is closely related to thestructure of magnetite (Fe3O4) which possesses the inverse spinelstructure but it differs from magnetite by the presence of ironvacancies.[35] Vacancy ordering gives rise to different crystalsymmetries, and several possible models for the distribution ofvacancies have been suggested. For this study, we selected themodel with ordered vacancies. Starting with the experimentalstructural data reported by Jørgensen, et al.[35] for the tetragonalmaghemite with ordered vacancies, we built the surfaces (001),(010), (100), and (113). Each surface was created with areas ofapproximately 9 nm2 (�3nm� 3nm) to ensure that the selectedorganic molecules, CV and BCG, do not interact with their imagesin adjacent cells. The depth of the surfaces was set toapproximately 26 A in order to ensure that it was greater thanthe non-bond cut-off used in the calculation. The vacuumthickness was set to 5 nm so that the non-bond calculation forthe CV and BCGmolecules did not interact with the periodic imageof the bottom layer of atoms in the surface. The Quality in theAdsorption Locator calculation was set to Fine, the forcefieldselected was COMPASS, the top layer atoms in each surface wereselected for the interaction with CV and BCG, and the maximumadsorption distance value was 1.5 nmwith a fixed energy windowof 418.68 kJ/mol for sampling configurations which differs fromthe lowest configuration by the maximum amount. Because of thelarge number of possible configurations generated for each surfacearrangement, only the lowest and highest configuration of the twoorganic molecules on each surface will be presented anddiscussed. To gain further insights into the interaction of CVand BCG with maghemite nanoparticles, a 10-nm sphericalnanoparticle of maghemite was built and CV and BCG moleculeswere allowed to interact with its surface. Two tests were carriedout, one with a single molecule and the second with 160molecules. Again, the Quality in the Adsorption Locator calcu-lation was set to Fine, the forcefield selected was COMPASS, thetop layer atoms in the spherical nanoparticle surface were selectedfor the interactionwith CV and BCG, and themaximumadsorptiondistance value was 1.5 nm with a fixed energy window of418.68 kJ/mol for sampling configurations.

RESULTS AND DISCUSSION

Effect of Contact Time (Kinetics Studies)

Figures 3a–3b show the dye adsorption experimental data togetherwith the kinetic model fitting for synthetic and real textilewastewater, respectively, as a function of contact time. As seen,in all cases, the dye adsorption was reasonably fast: adsorptionequilibrium was reached within 50min for the model dyes and< 125min for the real textile wastewater. This is not surprising, asthe consideredmaghemite nanoparticles are non-porous andhenceonly external adsorption occurs. In contrast, for porous adsorbents(like activated carbon), adsorption equilibrium time could takedays due to porous diffusion.[13] These findings are in very closeagreement with those reported by Nassar and coworkers onthe removal of different dyes andmetal ions fromwastewater usingdifferent metal oxide nanoparticles.[19–21,41] To further investigatethe kinetic mechanisms that control the adsorption process, theexperimental datawerefitted to theLagergrenpseudo-first-order[42]

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Figure 3. Effect of contact time on the adsorptive removal of dye from (a) synthetic wastewater and (b) real textile wastewater. Experimental conditions areT¼293K, nanoadsorbent dose, 10g/L; shaking rate, 200 rpm. The symbols are experimental data, the dashed lines are from the pseudo-first-order model(Equation (2)), and the solid lines are from the pseudo-second-order model (Equation (3)).

Figure 2. Chemical structures of (a) crystal violet and (c) bromocresol green; CPK representation of the optimized (b) crystal violet molecule (top and sideviews, respectively) and (d) bromocresol green (top and side views, respectively). Grey atoms represent carbon, blue atoms represent nitrogen,white atomsrepresent hydrogen, yellow atoms represent sulphur, green atoms represent bromine, and pale green atoms represents chlorine.

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andpseudo-second-order[43]models presented inEquations (1) and(2), respectively.

dQt

dt¼ K1ðQe � QtÞ ð1Þ

dQt

dt¼ K2ðQe � QtÞ2 ð2Þ

where Qe and Qt are the adsorbed amount of pollutant onto thenanoparticles (mmol/g) at equilibrium and at any time, t (min),respectively; the equilibrium rate constants K1 and K2 are offirst-order and second-order adsorption, respectively. The valuesof the obtained model parameters and their correspondingx-values obtained using the Polymath package are presented inTable 2.

As shown in Figures 3a–3b, and on the basis of the x-valuespresented in Table 2, both kinetic models fit closely to theexperimental data, with the pseudo-first-order model being thebest fit for the model dyes, and the pseudo-second-order modelbeing the best fit for the real textile wastewater sample. Thissuggests that the adsorption of themodel dye is faster than the realdye present in the textile wastewater. Generally, the adsorbatemolecule can be transferred from the bulk solution phase to theadsorbent surface in several steps; including external diffusion,pore diffusion, surface diffusion, and adsorption on the surface.[13]

Therefore, for the case of non-porous nanoparticles and owing toan effective degree ofmixing and extent dispensability, adsorptionseems to only be affected by electrostatic adsorption (as will bediscussed further in the ‘Effect of Solution pH’ section).[41] Sincethe real textile wastewater sample fits better to the pseudo-second-order model, it displays two adsorption kinetics: initial rapidadsorption (presumably due to electrostatic attraction) and slowadsorption at the later stagewhich represents a gradual adsorption

of pollutant at the nanoparticle surface by complexation.[32] It isworth noting here that the estimated theoretical values (by thekinetic model) of Qe were in very close agreement to the onesobtained experimentally.

Effect of Solution pH

The adsorption of wastewater pollutants by maghemite nano-particles depends significantly on the electrostatic interactionsbetween thenanoparticle surface and the functionalizedpollutants.These interactions are influenced largely by the pH of the solution,provided that it directly affects the surface charge of the nano-particles. In this set of experiments, different samples containing aspecified initial concentration (50mg/L formodel dyes in syntheticwastewater and2582mg/LCODofdye in real textilewastewater) atdifferent initial pH values from 2.5–11.0were performed to find theoptimumadsorption pH. Figures 4a–4b show the effect of pHon theamount of model dyes and real dye from textile wastewateradsorbed, respectively. Clearly, as seen in Figure 4a for the case ofBCG dye, the maximum amount adsorbed was at pH¼ 3. Thissuggests that adsorption is favoured in an acidic environment. Onthe other hand, for the case of CV dye, the maximum amountadsorbed was at pH¼ 10.5, which is favoured in a basic environ-ment. These results are not surprising, as the point of zero charge(pHpzc) of ironoxideparticles is around7.5,

[41,44] andhence ionizeddye adsorption on iron oxide surfaces is likely to be electrostaticattraction. Therefore, in a relatively basic solution pH> pHpzc, asignificantly high electrostatic attraction exists between thenegatively-charged surface of iron oxide and the positively-chargedCV dye. On the other hand, as the pH of the solution decreases, thenumber of positively-charged sites increases and the number ofnegatively-charged sites decreases. This led to a decrease in CVremoval due to charge repulsions. The adsorption process is thereverse for the BCG dye. It is worth noting here that otherinteractions between dye molecules and nanoparticle surfaces

Table 2. Estimated parameters for the pseudo-first-order and pseudo-second-order models

Pseudo-first-order Pseudo-second-order

Dye pH Qe (mmol/g) K1 (min�1) x2 Qe (mmol/g) K2 (g.mmol�1min�1) x2

CV 10.94 0.05 0.28 0.00012 0.052 0.35 0.0007BCG 2.39 0.03 0.18 0.00027 0.026 0.31 0.0008RWW 7.0 90.73 (mg/g) 0.03 7.55 98.55 (mg/g) 0.04 4.53

Figure 4. Effect of pH on adsorptive removal of dye from (a) synthetic wastewater at initial concentration of 50mg/L; (b) real textile wastewater at initialCOD of 2582.9mg/L. Experimental conditions are T¼293K, nanoadsorbent dose, 10 g/L; shaking rate, 200 rpm, time¼24h.

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should not be overlooked, as it will be further discussed in theComputational Modelling section. However, for the case of the realtextile wastewater sample this apparently was not the case, as theadsorptive dye removal was not significantly affected bysolution pH (Figure 4b). This suggests that the dye present in thereal textile wastewater sample might be multifunctional, andaccordingly it could be adsorbed in either basic or acidic environ-ments. The results are interesting for practical application as dyeremoval from real textile wastewater effluent could be removed bymagnetic nanoparticles at neutral conditionwithout the need of pHadjustment.

Effect of Temperature

In this set of experiments, the effect of temperature on adsorptivedye removal was studied at solution temperatures of 293, 328, and353K, and initial concentrations of dyes in synthetic wastewaterwere varied from 0–0.8mmol/L. For the case of real textilewastewater, the initial COD concentration was 2582.9mg/L andthe mass of nanoparticles varied from 0.02–0.25 g. Figures 5a–5bshow that CV and BCG adsorption at the preselected temperaturesincreased sharply at a low equilibrium concentration and startedto level off as equilibrium concentration increased. This suggeststhat g-Fe2O3 nanoparticles have good adsorption affinity towardCV and BCG at different temperatures. In addition, increasing thesolution temperature favoured adsorption. This could be attrib-uted to an increase in the mobility of dye molecules and asubsequent increase in the number of molecules that couldinteract with the active adsorption sites on the nanoparticlesurface.[20] Further, the increase of adsorption with temperatureindicates that the adsorption process is endothermic in nature.Similar observations, but at a slower rate, can be seen for dyeadsorption in real textile wastewater samples (Figure 6). Theslower kinetic rate for the case of real textile dyes agrees closelywith the results obtained in the kinetic study,where the real textiledye showed second-order kinetic behaviour. In addition, for all thedyes tested, the experimental adsorption isotherms were fitted tothe Langmuir and Freundlich models, represented by Equa-tions (3) and (4), respectively.

Qe ¼ Qmax KLCe

1þ KLCeð3Þ

Qe ¼ KFC1=ne ð4Þ

where Qe is the amount of dye adsorbed onto nanoparticles(mmol/g), Ce is the equilibrium concentration of dye in thesupernatant (mmol/L), KL is the equilibrium Langmuir adsorptionconstant related to the affinity of binding sites (L/mol), Qmax isthe maximum adsorption capacity for complete monolayer cover-age (mmol/g), and KF and 1/n are Freundlich constants which arerelated to the adsorbed amount and adsorption affinity, respec-tively. Both Langmuir and Freundlich model parameters wereestimated by minimizing the sum of squared differences betweenthe experimental and predicted values using the Solver feature inExcel. The non-linear x-square analysis, x2 ¼ S Qe�QeModelð Þ2

Qe Model, was

used toevaluate thecloseness offitting results,whereQe andQeModel

are the adsorbed amount of dye obtained experimentally and frommodelling, respectively. The close fitting to the experimental datawas indicated by the low x-values.Theestimatedvaluesofmodelparametersare listed inTables3–4.

Clearly, for all thedyes, theLangmuirmodel presented a closerfit tothe experimental data. This suggests that the selected nanoparticlesportray a homogeneous surface where monolayer adsorptionwould occur. Clearly, in all cases, the KL and Qmax values increasedwith the temperature,which confirms that the adsorption process isendothermic and favoured with temperature increases.

Figure 5. Effect of temperature on dye adsorptive removal by g-Fe2O3 nanoparticles. (a) CV dye, (b) BCG dye. Experimental conditions are nanoadsorbentdose, 10 g/L; shaking rate, 200 rpm, contact time¼24h. The symbols are experimental data, and the solid lines are from the Langmuir model(Equation (4)).

Figure 6. Effect of temperature on dye adsorptive removal by g-Fe2O3

nanoparticles from real textile wastewater. Experimental conditions areinitial COD concentration¼2582.9mg/L; shaking rate, 200 rpm, contacttime¼24h. The symbols are experimental data, and the solid lines arefrom the Langmuir model (Equation (4)).

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Thermodynamic Studies

To better understand the effect of temperature on adsorptive dyeremoval, thermodynamic studies were employed by estimatingthe changes in standard Gibbs free energy (DG8), enthalpy (DH8),and entropy (DS8) of adsorption. The values ofDG8were estimatedusing Equation (5).

DGo ¼ �RT lnK ð5Þ

where R is the universal ideal gas constant (R¼ 8.314 J/mol �K), Tis the temperature (K), and K is the adsorption equilibriumconstant. K is expressed as KL�Cs, where KL is the Langmuirequilibrium constant (L/mmol) and Cs is the solvent molarconcentration (mmol/L), which is estimated from the density andmolecular mass of water.[45]

The values of DH8 and DS8were estimated using the Van ’t Hoffequation[46] (Equation (6)), by plotting ln(K) against 1/T(Figure 7). DH8 and DS8 could be measured from the slope andintercept of the best-fit line, respectively. The calculatedthermodynamic parameters for the model dyes and real dye intextile wastewater are presented in Table 5.

lnðKÞ ¼ �DHo

RTþ DSo

Rð6Þ

As seen in Table 5, for all dyes, the values of DG8 at alltemperatures are negative, which indicates that dye adsorptiononto nanoparticle surfaces is spontaneous and thus thermody-namically favourable. Further, the DH8 value is positive for alldyes, which implies that dye adsorption is endothermic in nature.The positive value of DS8 may be attributed to the increase inrandomness at the nanoparticle surface–liquid interface.[20,21]

Effect of Coexisting Pollutants

As effluent wastewater contains more than one pollutant, thepresence of other pollutantsmay interfere in the removal efficiency

of an individual one. As a result, the effect of coexisting pollutantsshould be addressedwhen conducting an adsorption study. For thecase of real textile wastewater it appears that in addition toremoving colour from textile wastewater, the nanoparticlesuccessfully removed other contaminates, such as Cr3þ, at a rateofmore than 98%, as confirmed by the atomic absorption analysis.

Computational Modelling

Figures 8–9 show some configurations that the CV and BCG dyemolecules may obtain after adsorption on different maghemitesurfaces. In Figure 8, it is possible to see that the original “fanblades” configuration of CV (Figure 2b) is modified uponadsorption to the different surfaces of maghemite, where aflattening of themolecule is clearly observed to occur as it interactswith the different selected surfaces ofmaghemite. According to the

Table 3. Estimated Langmuir parameters at different temperatures. KL (L/mmol), Qmax (mmol/g) formodel dyes and KL (L/mg) andQmax (mg/g) for dyein real textile wastewater

Temperature (K)

293 328 353

Dyes pH KL Qmax x2 KL Qmax x2 KL Qmax x2

CV 10.94 20.99 0.49 0.050 20.04 0.55 0.04 21.26 0.61 0.04BCG 2.39 9.32 0.19 0.005 10.63 0.20 0.01 12.03 0.21 0.01RWW 6.8 0.00002 363.6 1.43 0.00015 413.2 1.71 0.0002 425.2 2.46

Table 4. Estimated Freundlich parameters at different temperatures. 1/n (unit less), KF [(mmol/g)(L/mmol)1/n] for model dyes and KF [(mg/g)(L/mg)1/n] for dye in real textile wastewater

Temperature (K)

293 K 328 K 353 K

Dyes pH KF 1/n x2 KF 1/n x2 KF 1/n x2

CV 10.94 0.9 0.5 0.2 0.89 0.49 0.17 0.87 0.49 0.16BCG 2.39 0.77 0.84 0.19 0.84 0.84 0.22 0.84 0.81 0.20RWW 6.8 0.17 0.98 1.43 0.52 0.89 1.71 0.35 0.85 2.46

Figure 7. van't Hoff plot for the endothermic adsorption of CV, BCG andRWW.

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adsorption calculations, CV has a strong interaction with themaghemite surfaces through nitrogen atoms and aromatic rings,forcing the flat configuration of CV on the surface. The adsorptionenergy of CV on the (010) surface is the lowest of the four studiedsurfaces, and that on the surface (113) is the highest: a differenceof 1105.31 kJ /mol was obtained between the lowest configu-rations on surface (010) and on surface (113) indicating thatsurface (113) is the least favourable for CV adsorption. Table 6shows the differences in adsorption energy with respect to thelowest surface adsorption on surface (010). Differences between

the values of adsorption energy of CV for surfaces (010), (100),and (001) are smaller, predicting that the adsorption of CV onthese maghemite surfaces should follow the Langmuir adsorptionmodel, which indeed was observed experimentally, and that thesurface (113) must grow to be exposed in larger areas in order tomodify the adsorption model from Langmuir to Freundlich.Figure 9 illustrates the configuration of the BCGmolecule as it is

adsorbed on the different studied maghemite surfaces. For thiscase, it is observed that the BCG molecule interacts with thesurface through aromatic rings and hydroxyl groups, and thesulfur double-bonded with oxygen atom points upward inthe lowest and highest configurations. The configurations arealmost flat compared with the original configuration (Figure 2d).As happened with the CV molecule, the lowest adsorption energyis found on surface (010) and the highest on surface (113). Adifference of 418.68 kJ/mol is observed between the lowestadsorption energies on surface (010) and surface (113), as shownin Table 6. Again, the differences in adsorption energies betweensurfaces (010), (100), and (001) are small, indicating that BCG andCV do not sense substantial differences in the adsorption sites onthese surfaces. Thus, a Langmuir adsorption model is predictedaccording to these results. This was observed experimentallywhen CV and BCG were adsorbed on maghemite nanoparticles.Table 7 shows a summary of the configurations that CV and BCGcan obtain on the studied maghemite surfaces.

Table 6. Adsorption energy differences for the adsorption of CV andBCG in the studied surfaces of maghemite with respect to the surface(010)

CV Adsorption Energydifference with respect to(010) surface [kcal/mol]

BCG Adsorption Energydifference with respect to(010) surface [kcal/mol]

Surface Lowest Highest Lowest Highest

(010) 0 92.97 0 99.83(001) 22.98 76.96 7.99 107.91(100) 3.52 99.96 3.90 103.79(113) 264.13 332.72 100.72 200.01

Table 5. Values ofDG8,DH8 andDS8 for adsorptive removal of CV, BCG and dye in real wastewater samples at different temperatures.DG8:(kJ/mol),DS8:(J/mol.K), DH8:(kJ/mol), K:(unitless)

Temperature (K)

293 353 353

Dye 4G8 4S8 4H8 K x10�3 4G8 K x10�3 DG8 Kx10�3

CV �34.03 116.14 0.05 1164.52 �35.64 1106.68 �38.09 1163.55BCG �32.05 128.2 5.5 517.32 �34.01 587.27 �36.54 658.84RWW �6.95 144.17 35 0.17 �13.13 0.12 �15.32 0.19

Figure 8. CPK images of the adsorption of crystal violet on the surfaces of maghemite (side and top views, respectively). (a) Lowest and highestconfiguration on surface (001); (b) lowest and highest configuration on surface (010), and (c) lowest and highest configuration on surface (100); and (d)lowest and highest configuration on surface (113). Bright blue atoms represent nitrogen, gray atoms represent carbon, white atoms represent hydrogen,pale green atoms represent chlorine, red atoms represent oxygen and light blue atoms represent iron.

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The previous CV and BCG adsorption calculations were carriedout on perfectly flat maghemite surfaces. Thus, to get a glimpse ofwhat may actually be happening with a real nanoparticle,calculations of the adsorption of CV and BCG were carried out

on a 10 nm spherical maghemite nanoparticle (closest to theactual size obtained experimentally for the real maghemitesample used). Figures 10–11 illustrate the adsorption ofone molecule of CV or BCG and the adsorption of 160 moleculesof CV or BCG on the 10 nm spherical maghemite nanoparticle,respectively. In Figure 11a (expanded insets) it is possible to seethat in the rounded surface of the 10 nm spherical maghemitenanoparticle, the lowest configuration of CV is no longer the flatone observed in the perfectly flat surfaces of maghemite, but atilted one (more vertical) anchored by the interaction of twonitrogen atoms that are not positively charged (this configurationwas observed in the flat surfaces but the adsorption energy washigh, and thus not discussed in the previous section). Thepositively-charged nitrogen is pointing upwards togetherwith thechloride atom, in the absence ofwater. In Figure 10b it is observedthat as more CVmolecules are added (in this case 160), the tilting

Figure 9. CPK images of the adsorption of bromocresol green on the surfaces of maghemite (side and top views, respectively). (a) Lowest and highestconfiguration on surface (001); (b) lowest and highest configuration on surface (010), and (c) lowest and highest configuration on surface (100); and (d)lowest and highest configuration on surface (113). Bright green atoms represent bromine, yellow atoms represent sulfur, gray atoms represent carbon,white atoms represent hydrogen, red atoms represent oxygen and light blue atoms represent iron.

Table 7. Summary of the different configurations of CV and BCG in thedifferent maghemite surfaces

CV (Configuration) BCG (Configuration)

Surface Lowest Highest Lowest Highest

(010) Flat Flat-slightly tilted Almost flat Almost flat(001) Flat Flat-slightly tilted Almost flat Almost flat(100) Flat Flat-slightly tilted Almost flat Almost flat(113) Flat Flat Almost flat Almost flat

Figure 10. CPK images of the adsorption of crystal violet on the surfaces of a 10 nmmaghemite nanoparticle. (a) side and top views of the adsorption of onemolecule of CV on the 10nmmaghemite nanoparticle; and (b) adsorption of 160 CV molecules on the 10nmmaghemite nanoparticle. Bright blue atomsrepresent nitrogen, gray atoms represent carbon, white atoms represent hydrogen, pale green atoms represent chlorine, red atoms represent oxygen andlight blue atoms represent iron.

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of the CV molecules is more pronounced (more vertical) thanwhen one lonemolecule of CV is on the nanoparticle surface. Thisarrangement indicates that more CV molecules can be adsorbedon the surface thanwould be estimated by the flat configuration ofthe molecule observed for the flat surfaces studied, pointing outthe importance of surface morphology for CV adsorption.

Figure 11 shows the lowest configuration of BCG adsorption onthe 10nmmaghemite nanoparticle. For this case, the configurationof BCG on the rounded nanoparticle surface (Figure 11a) is similarto that observed for the flat surfaces in which aromatic rings andhydroxyl groups are the anchoring sites toward the surface. WhenmoreBCGmolecules are added (160 in this case), it is possible to seethat some of the BCGmolecules can tilt slightly on the surface of thespherical nanoparticle (Figure 11b), but not all of them are tilted asin the case of CVmolecules. This indicates that the configuration ofBCG molecules on the surface remains similar to when only one ispresent, which should predict a difference in adsorption capacitywith respect to CV. This supports the experimental findings onkinetic and isotherm studies (Figures 3 and 5). Both figures showthat CV uptake is greater than BCGuptake,whichmay be related tothe insights gained in the adsorption calculations carried out for thespherical maghemite nanoparticles.

SCALING-UP AND COST-EFFECTIVENESS OF NANOPARTICLE

TECHNOLOGY

Our study on the application of nanoparticles falls under the field ofin situ remediation rather than packed bed processes. Asmentioned, due to high medium mobility with high dispersionability, nanoparticles lead to effective transport for in situapplications. Therefore, the nanoparticles can be employed insitu, within the contaminated zone. Nevertheless, integratingnanoparticle technology with conventional wastewater treatmentprocesses is possible.[30] Nanoparticle technology can be integratedwith the sedimentation process, were it can work as both acoagulant and an adsorbent. Further, nanoparticle technology canbe integratedwithbedfiltration technology,where thefiltrationbedwill trap suspended contaminants and thenanoparticleswill adsorbsoluble ones.[30] The ratioof nanoparticles tobedmediawill depend

on the initial concentration of soluble contaminants. The presenceofnanoparticles in thebedshall not impact thebedpermeabilitynorflux, as the nanoparticles will be integrated with the sand grains orothermedia to support and hold the nanoparticles, andwill be usedin small quantities (less than 0.1 g of nanoparticles per gram of bedmaterial).[30] Another advantage of this packed bed process is thatafter adsorption, the nanoparticles can be employed as catalysts,whereby the adsorbed organic contaminants can be gasified intosynthetic gas with the aid of steam (catalytic steam gasificationprocess).[47] This will also help in the regeneration of nanoparticlesfor another cycle or dumping them safely without any negativeimpact on the environment, as sand- and iron-based nanoparticlesare naturally occurring and environmentally-friendly. We believethat incorporating nanoparticle technology in conventional waste-water treatment is an important step forward in making conven-tional wastewater treatment plants more accessible to differenttypes of industrial effluents andnot justmunicipalwastewater, as isthe case in Palestine. By incorporating nanoparticle technologywith conventionalwastewater treatment processes, this technologybecomes overwhelmingly cost-effective and appealing to theaverage wastewater producer.

CONCLUSIONS

Iron oxide nanoparticles have shown potential for environmentalapplications because of their unique properties, such as specificfunctionality and large specific surface area per unit mass. Theresults from the present study indicate that g-Fe2O3 nanoparticlescould be employed successfully for decolourization of textilewastewater effluent. Dye adsorptionwas fast and equilibriumwasachieved in less than 125min for dye in real textile wastewater.Further, for dye and contaminants in real textile wastewater,adsorption was favoured at higher temperatures and was notsignificantly affected by solution pH, indicating dye multi-functionality. It was found that the equilibrium data closely fitthe Langmuir model, suggesting monolayer adsorption, whichwas backed up by the adsorption calculations. The adsorptionresults of the thermodynamics studies showed the endothermicnature of the adsorption process, the spontaneity, and the

Figure 11. CPK images of the adsorption of bromocresol green on the surfaces of a 10nmmaghemite nanoparticle. (a) side and top views of the adsorptionof one molecule of BCG on the 10nm maghemite nanoparticle; and (b) adsorption of 160 BCG molecules on the 10nm maghemite nanoparticle. Brightgreen atoms represent bromine, yellow atoms represent sulfur, gray atoms represent carbon, white atoms represent hydrogen, red atoms represent oxygenand light blue atoms represent iron.

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physisorption of the process. As a conclusion, this study confirmedthat g-Fe2O3 nanoparticles could be employed as an efficientadsorbents for industrial wastewater treatment where classicaladsorbents could be ineffective or costly.

ACKNOWLEDGEMENTS

The authors thank Dr. A. Abu Obaid from the Department ofChemistry for providing the model dyes, Mr. N. Dwikat for hisassistance in the UV-vis and AA analyses and the Departmentof Chemical Engineering for providing the COD kits, andMrs. Hamees Tbaileh and Mr. Yusef Ratrout for their help inCOD measurements. Special thanks to Al-Aqad Textile Companyin Nablus, Palestine for providing the textile wastewater sample.The authors would like to thank the Engineer Zuhair HijjawiAward 2014.Dr. Nassar thanks the PalestinianAmericanResearchCenter for the 2014/2015 fellowship. The authors are also gratefulto the Natural Sciences and Engineering Research Council ofCanada (NSERC), Nexen-CNOOC Ltd, and Alberta Innovates-Energy and Environment Solutions (AIEES) for the for thefinancial support provided through the NSERC/NEXEN/AIEESIndustrial Research Chair in Catalysis for Bitumen Upgrading.

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Manuscript received November 18, 2014; revised manuscriptreceived January 19, 2015; accepted for publication February 23,2015.

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