Improved adsorptive mineralization capacity of Fe–Ni sandwiched montmorillonite nanocomposites towards magenta dye

Chemical Engineering Journal 228 (2013) 308–317

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Improved adsorptive mineralization capacity of Fe–Ni sandwiched montmorillonite nanocomposites towards magenta dye Brijesh S. Kadu, Rajeev C. Chikate ⇑ Nanoscience Group, Department of Chemistry, Post-Graduate and Research Centre, MES Abasaheb Garware College, Karve Road, Pune 411 004, India

h i g h l i g h t s

g r a p h i c a l a b s t r a c t

 Fe–Ni bimetallic nanocomposites for

The adsorptive mineralization of magenta dye by Fe–Ni nanocomposites proceeds through pseudo-multilayer with thermodynamically favored exothermic chemisorption process.

magenta dye degradation.  Thermodynamically favored exothermic chemisorption process.  Pore diffusion controlled adsorption through micro and mesopores.  Surface properties of nanocomposites responsible for better longevity.

a r t i c l e

i n f o

Article history: Received 4 March 2013 Received in revised form 25 April 2013 Accepted 28 April 2013 Available online 7 May 2013 Keywords: Iron–nickel bimetallics Montmorillonite Nanocomposites Adsorption isotherms Diffusion controlled adsorption Recycling

a b s t r a c t To improve the adsorptive mineralization efficiency of Fe–Ni nanoparticles (Fe–Ni NP’s), we demonstrate a facile, rational and highly efficient approach by intercalating Fe–Ni NP’s onto montmorilonite (MMT). XRD analysis suggested formation of MMT-composites with Fe–Ni NP’s having spherical shape of 30–40 nm size. Kinetics of basic magenta (BM) demonstrated it to be of pseudo-second order with 25% in-situ and 10% loaded nanocomposites exhibiting better adsorption tendency. The adsorption properties of BM are analyzed with isotherms like Redlich–Peterson, Dubinin–Radushkevich, Temkin and Flory– Huggins besides Langmuir and Freundlich for understanding the adsorption dynamics. Pseudo-multilayer exothermic chemisorption is predominant with significant amount of free energy change (DG°) involved in adsorption on the nanocomposite surface. Employing Webber–Morris and Boyd intra-particle diffusion models, it is observed that diffusion is within micro- and meso-pores that subsequently favors pore-diffusion controlled process. These features have significantly contributed towards successful utilization of these composites for continuous removal capabilities. From the adsorption capacity, kinetics and diffusion controlled characteristics; it is observed that in-situ formed Fe–Ni nanocomposites possess enhanced adsorption capacity towards BM remediation. Present work clearly demonstrates that tailor-made nanocomposites may exhibit potential applications towards continuous removal of organic pollutants from aqueous streams with high efficiency. Ó 2013 Elsevier B.V. All rights reserved.

1. Introduction Contamination of aqueous streams due to synthetic dyes emanated by textile, leather and printing industries is a major environmental concern [1]. Different physicochemical and biological ⇑ Corresponding author. Tel.: +91 20 41038263; fax: +91 20 25438165. E-mail address: [email protected] (R.C. Chikate). 1385-8947/$ - see front matter Ó 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.cej.2013.04.103

approaches are employed for the removal of dyes from aqueous solution [2]. Amongst these, adsorption and biodegradation have been extensively utilized to address this issue at industrial scale. However, these methods are rather somewhat inefficient, expensive and generate lot of secondary waste that needs further disposal [3–5]. Commercial iron powder [6] has been employed for the abatement of dye stuff, although, it is less efficient and requires high

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dosage of adsorbent. Such shortcomings can be surmounted by size reduction process so as to generate reactive iron center with high surface area through formation of nano-sized zero valent iron (nZVI) species. In the recent past, there has been an upsurge of interest in the field of nZVI-based treatments of organic and inorganic pollutants from aqueous streams [7]. The process involves liberation of e from nanoparticles in water that subsequently induces oxidation and/or reduction of contaminants leading to generation less toxic metabolites [8]. It is significant to note that bare and supported nZVI has been successfully employed [9,10] for removal of majority of dyes at very low adsorbent loading with better removal capacity and faster removal rates. For example, iron nanoparticles are found to be extremely effectual in removing acid black 24 with high removal capacity at low adsorbent concentration [29]. However, major drawback of such a treatment centers around the fact that nZVI tend to agglomerate during contaminant degradation process and undergoes faster corrosion in water generating an inactive oxide layer on the particle surface that subsequently reduces its removal capacity [11]. To mitigate the agglomeration and retaining the surface reactivity of nZVI, some promising synthetic methods have been developed [12] to generate more dispersible and stable nZVI via immobilizing them onto micro-sized supports like carbon, zeolite or clay. Another approach is adopted wherein the incorporation of a second catalytic metal like Pd, Zn, Ni or Pt with nZVI has lead to improved performance with decreased corrosion rates of iron and facilitates easier reduction of pollutants by lowering down the hydrogen over-potential of the bimetallic system [13–15]. However, none of these catalysts possesses recycling capabilities with better removal capacity for continuous removal of contaminant from aqueous streams. Clay minerals; a class of inorganic layered compounds, can be tailored into various functional solid adsorbents by utilizing their inherent features such as composition, structure and beneficial adsorption capacity [16]. Thus, it is imperative to develop an ingenious approach by combing these features of clay with bimetallic nanoparticles that may result in engineering the ‘‘designer adsorbents’’ for their applications in green and sustainable technologies because of: (a) effective utilization of active species from the framework of clay (b) beneficial exploitation of the interlayer space for the formation of functional materials with nanoparticles (NPs) and (c) plausible enhancement in the adsorbing tendency of engineered nanocomposites. Montmorillonite (MMT), a 2:1 type of clay, has often been used to remove organic dyes and pigments because of its higher surface area and better cation exchange capacity [17]. Its removal capability can be further enhanced either through surface modification with surfactants or via intercalation with nanoparticles that lead to increased surface area and improved adsorption capacity [18]. It possesses two types of swelling properties namely, ‘‘intra-lamellar’’ and ‘‘extra-lamellar’’ in presence of aqueous mono-valent and divalent cations that are responsible for generating differences in the lamellar structures [19] and can eventually improve its sorption capability. For example, Fe-intercalated MMT [20] has been effectively used as an adsorbent for successful removal of dyes like rhodamne B and malachite green and it can be recycled for almost 14 times at 5 ppm dye concentration. Considering these features of MMT, two synthetic approaches are employed for the preparation of clay-based colloidal nanocomposites with Fe–Ni NP’s viz. in-situ generation of active Fe–Ni sites on the MMT structure and physical loading of preformed Fe–Ni NP’s onto the MMT surface. It is envisaged that such a strategy would result in enhanced adsorption behavior of Fe–Ni nanocomposites for aquatic pollutants and subsequently their removal capability. To investigate this hypothesis, systematic efforts are directed towards understanding the adsorption dynamics of MMTbased clay nanocomposites by employing variety of adsorption

309

isotherms that include conventional Langmuir, Freundlich as well as Redlich–Peterson, Dubinin–Radushkevich, Temkin and Flory– Huggins. These isotherms are preferred owing to their uniqueness in providing the specific sorption parameters that are supportive in evaluating the sorption mechanism as well as synergism in FeNiMMT nanocomposites towards removal capability for a model contaminant basic magenta dye (BM; Supplementary data Fig. S1). Furthermore, the adsorption capabilities are also assessed with intra-particle diffusion models so as to comprehend the diffusion mechanisms expected for nanocomposite-dye interactions and subsequent mineralization. It is worth mentioning here that these features indeed influence the mineralization capability as can be vouched from the successful utilization of these nanocomposites for continuous removal of organic pollutants. In the present work, we have clearly established that Fe–Ni composites retain their catalytic activity up to 12 cycles and can regain their activity after proper chemical treatment. Moreover, the investigated approaches augur well towards improved efficiency as well as reusability as compared to the existing nZVI-based adsorbents employed for remediation of organic pollutants. 2. Experimental 2.1. Materials and methods All chemicals were of analytical grade from Fluka A.G. USA and used as received: BM, Iron (II) Sulphate (FeSO47H2O), Nickel (II) chloride (NiCl26H2O), Sodium borohydride (NaBH4), and MMT. Deionized water is used for all the experiments. 2.2. Pretreatment of MMT 6.0 g of MMT was dispersed in 300 mL 1 M NaCl, stirred for 1 h at 6000 rpm on mechanical stirrer and the suspension was left to stand overnight at 250 rpm at room temperature. The slurry was centrifuged at 3000 rpm and the solid was dried in oven at 378 K for 4 h. The powder was ground to 200 mesh size and used for preparation of nanocomposites. 2.3. Synthesis of Fe–Ni nanoparticles Fe–Ni NP’s were synthesized in accordance with the procedure reported earlier [21]. 2.4. Synthesis of Fe–Ni nanocomposites 2.4.1. In-situ method To a suspension of 0.75 g of pretreated MMT in 50 mL of deionized water, aqueous solution of FeSO4.7H2O and NiSO4.6H2O (0.0025 M each dissolved in 20 mL of deionized water) was added with constant stirring under N2 atmosphere. The mixture was stirred for 30 min followed by drop wise addition of 0.08 M NaBH4 over a period of 1 h under nitrogen atmosphere. It was centrifuged at 3000 rpm, washed with acetone and dried under vacuum. This procedure yielded 25% in-situ nanocomposite (FeNi-in-situ-25%). Similar procedure is followed for the synthesis of other compositions and they are abbreviated as FeNi-in-situ-10%, and FeNi-insitu-50%, respectively. 2.4.2. Loading of Fe–Ni NP’s on MMT To a suspension of 0.75 g of pretreated MMT in 25 ml of acetone, 0.25 g of freshly prepared Fe–Ni NP’s was added in portions with constant stirring under N2 atmosphere. The mixture was stirred for 1 h and centrifuged at 3000 rpm and subsequently washed with acetone successively and dried under vacuum. This procedure

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yielded 25% loaded nanocomposite (FeNi-load-25%). Similar procedure is followed for the synthesis of other compositions and they are abbreviated as FeNi-load-10%, and FeNi-load-50%, respectively. 2.5. Characterization of nanocomposites X-ray powder diffraction (XRD) patterns are obtained using Phillips X’pert MPD X-ray diffractometer using Cu Ka radiation. Transmission electron microscope (TEM) images are obtained using a JEOL electron microscope (model 1200X). Brunnaer–Emmett–Teller (BET) surface area analysis of the synthesized nanoparticles is performed using nitrogen adsorption method with surface analyzer system (CHEMBET3000, Quantichrome Instruments, US). The amount of iron and nickel leached from the nanocomposites after their successive usage is analyzed with Optima 7000 DV ICP-OES Spectrometer (Perkin–Elmer).

be of spherical shape (20–40 nm diameters) that are connected in chains of beads probably due to the electronic and magnetic interactions between the metals [21]. Surface area for MMT, Fe–Ni NP’s is found to be 61.4 and 13.9 m2 g1 (Supplementary data Table T1). Upon composite formation, there is significant increase in the surface area (158–252 m2 g1) that can be attributed to the insertion of Fe–Ni NP’s into the structure of MMT. Because of dissimilar synthetic approaches adopted for the synthesis of these nanocomposites, in-situ formed nanocomposites exhibit higher surface area as compared to loaded nanocomposites. In the former case, metal ions are adsorbed and subsequently reduced while in the later ones the pre-formed nanoparticles are loaded onto MMT. This would certainly lead to difference in the pillaring of MMT that may account for lowering in the surface area for loaded nanocomposites. 3.2. Efficiency of nanocomposites towards BM removal

3.1. Characterization of Fe–Ni nanoparticles

3.2.1. With Fe–Ni NP’s In order to obtain optimized conditions for better removal of BM and the influence of the amount of adsorbent, different amounts of adsorbent are added to the BM solution under specific conditions keeping other variables being fixed such as BM concentration (100 mg L1), pH  7 and temperature 298 K. The results obtained by varying the amount of adsorbent between 0.5 and 1.5 g L1 are shown in Fig. 3a which suggest that 1 g L1 of adsorbent is appropriate for highest removal of BM under simulated conditions. Although it is expected that this dose gives higher conversion than 0.5 g L1, it is rather surprising that higher doses of nanocomposite exhibit lower BM removal. A possible explanation comes from the fact that the volume of the solution is same (10 mL) in both the cases, but the amount of the solid adsorbent markedly changes and reaches saturation levels after certain amount. Moreover, increase in the turbidity of adsorbent suspension with higher loading also hinders favorable adsorption, there by affecting the rate of BM removal capacity. Thus, a dose of 1.0 g L1 nanocomposite is selected for further investigation of the effect of other factors. The efficiency of Fe–Ni NP’s is also evaluated with varying the initial BM concentration so as to find out its removal capacity under identical conditions (amount of adsorbent 1 g L1, pH  7 and temperature 298 K). Time profile (Fig. 3b) of such an aspect in the range of 50–150 mg L1 of BM reveals that better removal rates are observed at 100 mg L1, although similar observations are found at lower BM concentrations. The main objective of this study is to identify the effectiveness of Fe–Ni NP’s that can have better removal capacity without compromising the rate of decolourization. However at higher concentrations, it is plausible that adsorption equilibrium reaches to its saturation point that inhibits the removal efficiency of Fe–Ni NP’s. Thus, 100 mg L1 is chosen as the initial concentration of BM in subsequent experiments.

Fig. 1 represents XRD patterns of MMT and its Fe–Ni nanocomposites. MMT shows peaks at 20.9° and 26.9° due to (0 2 1 1) and (0 0 5) plane [22]. Upon interaction with Fe–Ni NP’s, it is observed that these planes are shifted to the lower angle region suggesting the insertion of Fe–Ni NP’s in the MMT structure and formation of intercalative nanocomposite with 1:1 ordered heterostructure [23]. It also suggests the attainment of crystallinity as well as proper dispersion of nanoparticles in the clay matrix. Fe–Ni NP’s and their nanocomposites exhibit characteristic peaks corresponding to Fe–Ni in the range of 40–65° that are assigned to (1 1 1) and (2 0 0) crystal planes of fcc (JCPDS 47-1417) and bcc (JCPDS 37-0474) structures of Fe–Ni NP’s [24]. The gradual increase in their intensities with increasing metal content (Fig. 1) reveals high degree of crystallinity for both types of nanocomposites. The morphology of Fe–Ni nanocomposites (Fig. 2) is found to

3.2.2. With in-situ and loaded nanocomposite Having established the efficiency of Fe–Ni NP’s towards BM removal, it is quite logical to extend similar approach for nanocomposites to evaluate the role of clay in the removal process. Fig. 4 depicts the time profile of BM decolourisation capacity for both Fe–Ni in-situ and loaded nanocomposites with different amounts of Fe–Ni nanoparticles onto MMT matrix. It can be seen from this figure that the degradation of BM is almost complete within 10 min with increasing in the Fe–Ni content possessing better rate constants. Amongst the in-situ formed nanocomposites, FeNi-in-situ-25% (Fig. 4a) possesses higher removal capacity while FeNi-load-10% (Fig. 4b) is found to be better within the family of loaded nanocomposites. Such dissimilarity in the removal capacities for Fe–Ni NPs, in-situ formed and loaded Fe–Ni nanocomposites can be judged

2.6. Batch adsorption experiments Stock solution of BM (100 mg L1) was prepared in deionized water and adsorption experiments were performed in an open batch system at room temperature, 298 K. The solution contained fixed amount of Fe–Ni nanocomposite (1 g L1). Dye solution was stirred with an agitator to keep the nanocomposite powder suspended. Samples were withdrawn at fixed interval for few minutes and centrifuged for 5 min at 3000 rpm. The supernatant was taken out at regular time intervals and the change in decolourisation was monitored by measuring the absorbance of the solution from 200 to 600 nm with UV–VIS spectrophotometer (Perkin Elmer, lambda 25). 2.7. Recycling of composites The recycling experiments with nanocomposites were carried out on [BM]ini = 100 mg L1 with 1 g L1 nanocomposite. After the completion of cycle, the residue is centrifuged at 3000 rpm, followed by washing with 5 mL of 0.001 M HCl followed by deionised water and acetone, dried in vacuum and used for subsequent cycles. 2.8. Leaching experiments The amount of iron and nickel leached out from the surface of nanocomposites was estimated by ICP-OES using the supernatant obtained after last cycle of reusability studies. 3. Results and discussion

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Fig. 1. X-ray diffraction patterns of (a) in-situ and (b) loaded Fe–Ni nanocomposite.

(a)

(b)

20 nm

(c)

20nm Fig. 2. TEM images of (a) Fe–Ni NP’s (b) FeNi-in-situ-25% and (c) FeNi-load-10%.

Fig. 3. Time profiles of BM decolourisation by Fe–Ni NP’s; (a) at different adsorbent amount and (b) at different initial concentrations of BM.

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Fig. 4. Time profile of BM decolourisation by (a) in-situ and (b) loaded Fe–Ni nanocomposites: {[BM]ini = 100 mg L1; [nanocomposite] = 1 g L1}.

from the fact that besides adsorption tendency of Fe–Ni NP’s, the clay matrix also contributes towards enhancing the effective sorption capacity of composites there by functioning in the synergistic manner. These results can also be attributed to the pillaring of clay [25] that changes the basal spacing and enhances the accessibility of BM in presence of H2O [26]. Based on the these observation, Fe–Ni NP’s, FeNi-in-situ-25% and FeNi-load-10% are utilized for comparative account of adsorption behavior with 1.0 g L1 adsorbent and varying the initial BM concentration.

3.3. Effect of BM concentration Fig. 5 depicts removal capacity of Fe–Ni NP’s, FeNi-in-situ-25% and FeNi-load-10% at various BM concentrations with time. The kinetic behavior of Fe–Ni NP’s is sensibly different than nanocomposites due to differences in their adsorption tendencies as evident from a sharp decrease of residual dye concentration after 10 min. Thus, kinetic data of BM revealed that the ‘‘slowest’’ adsorption behavior is observed for FeNi-load-10%. Effect of initial dye concentration is also clearly reflected in the removal capacity of three nanocomposites wherein the faster rates are observed at lower concentrations (50–100 mg L1) while at higher concentration the rate of decolourisation for BM is considerably reduced. These features can be attributed to the fact that at higher concentrations, the available number of adsorption sites reduces and

subsequently the adsorption depends on the initial concentration of BM [27]. 3.3.1. Kinetics of BM removal In order to evaluate the rate-controlling factors and mass transfer mechanism, kinetic data is correlated to linear forms of the pseudo first-order Eq. (1) and pseudo second order Eq. (2).

ln ðqe  qe Þ ¼ ln qe  k1 t

ð1Þ

t 1 t ¼ þ qt k2 q2e qe

ð2Þ

where qe and qt are the adsorption capacities of dye (mg g1) at equilibrium and at time t, while k1 (min1) and k2 (g mg1 min1) are the first-order and the second-order rate constants respectively. According to Eq. (1), the plot of ln(qe  qt) vs. t gives a straight line with a slope of – k1 and an intercept of ln qe while the plot of t/qt vs. t from Eq. (2) results   in a straight line with a slope of 1/qe and an intercept of 1= k2 q2e . The compliance between experimental data and the values obtained from kinetic models are evaluated from the correlation coefficients (R2). The effect of the initial BM concentration provides an important driving force to overcome the mass transfer resistance of the dye between aqueous and solid phases. It is observed that the rate constants are higher (Supplementary data Table T2) due to large number of available reactive sites causing an increased concentration

Fig. 5. Kinetic data for (a) Fe–Ni NP’s (b) FeNi-in-situ-25% and (c) FeNi-load-10% at 298 K fitted to proposed kinetic model for BM molecule.

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gradient between the sorbate in the solution and that at the sorbent surface. With passage of time, this gradient is decreased owing to the adsorption of the dye onto the vacant sites and subsequently leads to decreased adsorption at the later stages [28]. By correlating the kinetic data with the pseudo first-order and the pseudo second-order kinetic equations (Supplementary data Table T2), it is found that the correlation coefficient (R2) is higher for second-order adsorption kinetics as compared to firstorder kinetics. In addition, equilibrium adsorption capacity qe, calculated from the pseudo second-order kinetics model, is in agreement with experimental data suggesting that the adsorption process predominantly follows pseudo second-order rate model, and the overall process appeared to be controlled by chemisorption on the surface [29]. This can be attributed to the fact that the ratedetermining step primarily involves valency forces formed by sharing of electrons between dye anions and adsorbent [30]. Furthermore, increased adsorption capacity of nanocomposites (qe) with the increase in dye concentration can be ascribed to adsorption of BM mainly on the outer surface of the nanocomposite. The increased value of qe for in-situ and loaded Fe–Ni nanocomposites is due to increased surface area which considerably favors effective adsorption and subsequently better adsorption tendency for these nanocomposites.

Table 1 Isotherm parameters for Fe–Ni NP’s, FeNi-in-situ-25% and FeNi-load10%.

3.4. Sorption dynamics 3.4.1. Langmuir isotherm The Langmuir adsorption assumes that the adsorbed layer is of one molecule in thickness. The sorption data is analyzed according to linear form of Langmuir equation as:

Ce Ce 1 ¼ þ qe qm qm K L

ð3Þ

A linear plot of Ce/qe vs. Ce (Supplementary data Fig. S2) suggests that the single layer adsorption phenomenon is predominant over the entire range of concentrations. The co-relation coefficients (>0.99), isotherm constants and equilibrium monolayer capacities (Table 1) indicate the accurate description of the experimental data [31] where maximum amount of BM adsorbed on composite is found to be 123.45, 126.58 and 140.84 mg g1 for Fe–Ni NP’s, FeNi-in-situ-25% and FeNi-load-10% respectively. Such a feature strongly supports for higher adsorption tendency of BM molecule on the nanocomposite surfaces due to MMT support. It also suggests that a single surface reaction with constant activation energy is predominant sorption step and probably the predominant rate controlling step with high degree of irreversibility. 3.4.2. Freundlich isotherm The Freundlich equation describes that the dye concentration on the adsorbent surface increases linearly with initial dye concentration. However, the experimental data in the present study indicate that there is a limiting value of solid-phase concentration. The linearized form of Freundlich can be described as;

ln qe ¼ bF ln C e þ ln K F

ð4Þ

The logarithmic plot for Freundlich equation deviates from linearity (Supplementary data Fig. S3) indicating that the adsorption characteristics do not follow multilayer sorption. However, if the nonlinear plots are divided into two regions viz. Region 1 (corresponding to lower concentration) and Region 2 (applicable to higher concentration range), an accurate description of sorption characteristics can be evaluated [32]. From sorption isotherm constants and corelation coefficients (Supplementary data Table T3), it can be argued that both these regions independently follow the Langmuir type linearity while together they can be described as pseudo-multilayer

Adsorbent

Fe–Ni NP’s

FeNi-in-situ-25%

FeNi-load-10%

Langmuir qm (mg g1) KL (L mg1) R2

123.45 0.26 0.999

126.58 0.37 0.999

140.84 0.37 0.995

Freundlich KF (mg g1) bF R2

40.12 0.305 0.916

46.89 0.288 0.931

49.24 0.324 0.818

Redlich–Peterson b KR (L g1) aR (L mg1) R2

0.699 1487.88 36.45 0.983

0.715 2379.11 50.00 0.988

0.680 2157.60 43.03 0.951

Dubinin–Radushkevich E (kJ mol1) 23.35 K (J2 mol2) 9.17  104 QDR (mg g1) 1115.43 R2 0.989

30.23 5.47  104 442.34 0.943

27.52 6.60  104 681.20 0.878

Temkin bTe (kJ mol1) KT (L g1) DG° (kJ mol1) R2

0.105 3.68 3.23 0.964

0.108 6.17 4.51 0.967

0.089 4.82 3.90 0.906

Flory–Huggins n KFH (L g1) DG° (kJ mol1) R2

1.245 3.16  103 19.97 0.962

1.497 1.31  104 23.50 0.971

1.248 5.24  103 21.22 0.760

adsorption (Table 1). Such a behavior can be ascribed to irregular energy distributions due to different surface groups possessing different levels of activation energies for the adsorption process [33]. In the present study, besides hydroxyl groups present on the MMT surface, the intercalated Fe–Ni NP’s significantly contribute towards deviation from the Freundlich adsorption. 3.4.3. Redlich–Peterson (R–P) isotherm Combination of Langmuir and Freundlich equations is summarized in three parameter R–P adsorption isotherm model that clearly signifies the distinction between monolayer and multilayer adsorption phenomena. This isotherm can be described by

qe ¼

K R Ce 1 þ aR C be

ð5Þ

where qe is the solid-phase sorbate concentration at equilibrium (mg g1), Ce is the liquid-phase sorbate concentration at equilibrium (mg L1), KR is the R–P isotherm constant (L g1), aR is the R–P isotherm constant (L/mg11/b), and b is the exponent, which lies between 1 and 0. Under these conditions if b = 1, the adsorption favors Langmuir equation

qe ¼

K R Ce 1 þ aR C e

ð6Þ

However, when b = 0, the Henry’s law (7) predominates at lower range of concentration of adsorbate.

qe ¼

KR Ce 1 þ aR

ð7Þ

By rearranging Eq. (5), the R–P equation can be converted to a linear form as:

ln

  Ce K R  1 ¼ ln aR þ b ln C e qe

ð8Þ

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The linearized form of the R–P plots (Fig. 6a) for three adsorbing media viz. Fe–Ni NP’s, FeNi-in-situ-25% and FeNi-load-10% and the evaluated parameters (Table 1) suggest that the sorption dynamics of BM neither reflects Langmuir nor Freundlich behavior, rather a pseudo-multilayer surface reactions are predominant as evident from exponent b values. Such a behavior can be attributed to the fact that layered structure of MMT facilitates interlayer adsorption along with the sandwiched Fe–Ni active sites present within these layers of nanocomposites. 3.4.4. Dubinin–Radushkevich (D–R) isotherm D–R model is often employed for estimating the characteristic porosity and the apparent free energy of adsorption of pollutant on the adsorbent and can be described by the following equation as:

ln qe ¼ ln Q DR  K 2e

ð9Þ

where Ce is the equilibrium concentration of the dye; qe is the adsorption capacity of the dye, QDR is D–R maximum adsorption capacities of the dye, K is D–R constants and e is the Polanyi potential given as equation

  1 e ¼ RT ln 1 þ Ce

ð10Þ

D–R constant (K) gives the mean energy of adsorption as:

E ¼ ð2KÞ1=2

ð11Þ

where E is the mean adsorption energy. The linear regression of the D–R isotherm plot for the sorption of BM is depicted in Fig. 6b, and corresponding parameters are shown in Table 1. The sorption affinity for Fe–Ni NP’s is found to be highest amongst these adsorbents plausibly due to stronger electrostatic adsorption of BM on the electronically charged surface of nanoparticles. It also suggests that zero-valent bimetallic system promotes preferential adsorption and subsequent degradation of BM molecule on its surface; a feature well established for degradation of organic pollutants on zero-valent iron surfaces [34]. On the other hand, this affinity is considerably reduced for nanocomposite due to presence of intercalated nanoparticles on the MMT structure. However, it enhances the dispersion of nanoparticles as well as generation of reactive sites that are favorable for adsorption and later decomposition process in a synergistic

manner. Mean adsorption energy (E) from D–R model necessarily involves transfer of the free energy of one mole of solute from infinity (in solution) to the adsorbent’s surface. This value clearly reflects dominance of chemisorption on the adsorbent surface and can eventually lead to degradation process of BM molecule. Moreover, the negative values of E establish that this adsorption is primarily exothermic in nature that leads to rapid mineralization through reductive process for BM molecule. 3.4.5. Temkin isotherm Temkin isotherm model predicts a uniform distribution of binding energies over the population of surface adsorption sites of adsorbates. The range and distribution of the binding energies strongly depends on the density and distribution of functional groups present on both dye and nanocomposite surfaces and determines the adsorption potentials of the adsorbent. It is suggested that due to sorbate/sorbent interactions, the heat of absorption of all molecules within the layer would decrease linearly with coverage. Temkin isotherm has generally been applied within the following form:

qe ¼

RT ln K T C e bTe

ð12Þ

where bTe is the Temkin constant related to heat of adsorption (J/mol); KT Temkin isotherm constant (L/g), R the gas constant and T the absolute temperature (K). Linearized form of Temkin equation is given as:

qe ¼

RT RT ln K T þ ln C e bTe bTe

ð13Þ

KT and DG° are related as follows

DG ¼ RT ln K T

ð14Þ

From the plot of qe vs. ln Ce (Fig. 7a), values of both constants KT and bTe are calculated (Table 1). Lower values of bTe (0.089–0.105 kJ/mol) obtained in this study indicate that there exists a weak ionic interaction between BM molecules and nanocomposites. It is interesting to note that rate constant KT is significantly higher for in-situ nanocomposites; a similar observation already has been noted for kinetics of decolourisation of BM molecule with different adsorbents in the previous section. The negative DG° values support for exothermicity of the adsorption process, although it also describe the weaker ionic interactions of BM molecule on the surface of

Fig. 6. (a) Redlich–Peterson and (b) Dubinin–Radushkevich adsorption isotherms for (i) Fe–Ni NP’s (ii) FeNi-in-situ-25% and (iii) FeNi-load-10%. {[Nanocomposite] = 1 g L1; at 298 K}.

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Fig. 7. (a) Temkin and (b) Flory–Huggins adsorption isotherms for (i) Fe–Ni NP’s (ii) FeNi-in-situ-25% and (iii) FeNi-load-10%. {[Nanocomposite] = 1 g L1; at 298 K}.

nanocomposites supporting an ion-exchange type of mechanism for nanocomposites. 3.4.6. Flory–Huggins Isotherm Flory–Huggins model deals with the degree of surface coverage characteristics of adsorbate onto adsorbent and can explain the feasibility and spontaneous nature of an adsorption (Eq. 15)

h ¼ K FH ð1  hÞn C0

ð15Þ

In this respect, h is the degree of surface coverage, KFH represents equilibrium constant and n signifies number of adsorbates present on the adsorbent surface. h is also calculated using following equation:

h¼1

Ce C0

ð16Þ

Its equilibrium constant KFH is used to calculate the spontaneity of Gibbs free energy (DG°) as

DG ¼ RT ln K FH

ð17Þ

The linearized Flory–Huggins equation is as follows:

ln

h ¼ ln K FH þ n ln ð1  hÞ C0

ð18Þ

The isotherm showed a linear plot (Fig. 7b) of ln(h/C0) vs. ln(1  h) and values of KFH and n were calculated from the slope and intercept of the plot (Table 1). It is interesting to note that the n is maximum for in-situ composite while it remains almost constant for remaining two nanocomposites. Such a difference can be attributed to two factors: (a) uniform dispersing of Fe–Ni NP’s in clay matrix for in-situ that are responsible for efficient adsorption and (b) increased surface area for this nanocomposite. Concomitantly, this observation is further corroborated with KFH values that signify the amount of adsorbed BM molecule per g of adsorbents. Furthermore, negative values of DG° also confirm the thermodynamically favored process and the spontaneity for BM adsorption on clay composites [35].

second order reaction models. Thus, Weber and Morris intra-particle diffusion model is utilized which is expressed by the equation:

qt ¼ K ID t 1=2

ð19Þ 1

1/2

where KID represents the rate constant (mg g min ). Ideally, a straight line is expected for the plot of qt against t1/2 where intraparticle diffusion is the rate determining step while multi-linearity represents different mechanisms involved in the sorption process. Plots of qt vs. t1/2 for Fe–Ni NP’s, FeNi-in-situ-25% and FeNi-load10% (Supplementary data Fig. S4) can be segmented into two portions: (a) initial curved portion (slope KID1) that can be attributed to mass transfer effects taking place with boundary layer diffusion through larger pores and (b) upper linear portion (slope KID2) ascribed to intra-particle diffusion via micro- and mesopores of adsorbents. The values of KID1 and KID2 (Table 2) indicate that the intraparticle diffusional resistance for micro and mesopores is higher than larger pores [36]. It also infers that intra-particle diffusion is not only the rate controlling step but also facilitates subsequent degradative processes on the adsorbent surface. These processes are necessarily confined to nanoparticles sites of nanocomposites that induce oxidative-reductive cleavages of BM molecule. 3.5.2. Boyd plot Boyd film-diffusion model is employed for evaluating the contribution of film resistance for BM sorption that assumes the main resistance to diffusion is within the boundary layer surrounding the adsorbent particle and is expressed by the equation

FðtÞ ¼

qt qe

ð20Þ

where F(t) is the fractional attainment of equilibrium, at different times t, Bt is a function of F(t), qt and qe are the dye uptake (mg/g) at time t and at equilibrium, respectively.

Condition I : For FðtÞ > 0:85; Bt ¼ 0:4977  ln ð1  FðtÞÞ

ð21Þ

Condition II : For FðtÞ < 0:85; sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi  2 !2 p FðtÞ p p 3

pffiffiffiffi

3.5. Intra-particle diffusion

Bt ¼

3.5.1. Weber–Morris model The adsorption mechanism involves several steps including the slowest one that determines the effectiveness of adsorption kinetics. Generally, porosity of adsorbent and intra-particle diffusion are key factors for rate limiting conditions under batch reactor system which cannot be evaluated by the pseudo-first and/or pseudo-

It is worth mentioning that film diffusion is observed when external transport of the ingoing molecules is greater than internal transport while particle diffusion governs the rate when external transport is less than internal transport. Since fairly linear plots for Bt vs. time are obtained for nanocomposites (Supplementary data Fig. S5) at 50, 100 and 150 ppm BM concentrations, it can be argued that the

ð22Þ

316

B.S. Kadu, R.C. Chikate / Chemical Engineering Journal 228 (2013) 308–317

Table 2 Intra-particle diffusion parameters from Weber–Morris and Boyd plots for BM removal. BM conc.

50 (mg L1)

Adsorbent

KID1a

100 (mg L1) R

Weber–Morris Fe–Ni NP’s FeNi-in-situ-25% FeNi-load-10%

9.814 8.456 16.87

0.958 0.987 0.912

2

KID2

a

7.951 8.259 0.274

R

KID1a

0.922 0.913 0.961

7.098 42.63 15.38

2

150 (mg L1)

R

KID2a

R

0.998 0.968 0.995

4.300 6.253 1.098

0.962 0.946 0.949

2

2

100 (mg L1)

KID1a

R2

KID2a

R2

46.94 46.75 44.95

0.999 0.999 0.999

10.03 16.67 6.289

0.944 0.926 0.912

BM conc.

50 (mg L1)

150 (mg L1)

Adsorbent

Slope

Int

R2

Slope

Int

R2

Slope

Int

R2

Boyd plot Fe–Ni NP’s FeNi-in-situ-25% FeNi-load-10%

0.549 0.112 0.405

0.839 0.931 1.865

0.999 0.969 0.915

0.413 0.527 0.543

0.550 0.560 0.218

0.916 0.957 0.941

0.220 0.343 0.116

0.405 1.059 0.154

0.924 0.941 0.904

redox degradation of BM necessarily proceeds through porediffusion with external transport of the ingoing ions greater than internal transport [37]. However, it seems that pore diffusion becomes more prominent at higher BM concentrations, as the intercept approaches lower values with increasing initial concentration (Table 2). Slight non-linearity can also be ascribed to competitiveness for pore-diffusion as well as film-diffusion dependent mechanisms probably due to simultaneous diffusion-degradation of BM molecules on the adsorbents.

3.6. Longevity of Fe–Ni NP’s and nanocomposites The life span of Fe–Ni NP’s is evaluated for investigating the economy of the remediation process which is a measure of the number of times a material can be employed for successive cycles without sacrificing its efficiency. Therefore, it is prerogative to desorb dye molecules from the adsorbent surface so as to achieve the regeneration of adsorption capacity of adsorbent. However, very few reports are available in literature on Fe-based nanocomposites addressing this issue. For example, iron powder exhibits [6] recycling capability up to 10 cycles, however, the removal capacity is found to be very low (<0.02) due to high loading of adsorbent (Table 1). On the other hand, Fe–Mo–Si–B amorphous alloy [14] preserves its activity up to five cycles when used for removal of direct blue 2B. In the present work, recycling experiments are carried out on Fe–Ni NP’s, FeNi-in-situ-25% and FeNi-load-10% for comparing their efficiencies towards continuous usage. The dye reduction capacity is found to be highest for FeNi-in-situ-25% with >70% removal is observed during first six cycles with subsequent lowering up to 10% for twelfth cycle (Fig. 8). On the other hand, FeNi-load-10% exhibited similar efficiency for the first three cycles which gradually decreases to 15% for seventh cycle. However, Fe–Ni NP’s showed lowest recycling capability amongst the materials evaluated for recycling experiments. These results suggest that nanocomposites are better candidates for removal of BM due to better adsorption capacity due to increased reaction sites. Such behavior may be attributed to the proper dispersion of Fe–Ni NP’s in the clay matrix with enhanced permeability. It augurs well for BM removal and degradation capacity through synergism of clay and nanoparticles functioning as a bifunctional adsobent. Moreover, favored pseudo-multilayer adsorption significantly contributes towards their effectiveness in subsequent usages. These results can be further substantiated from the fact that oxidation of Fe0 is controlled by adjacent Ni0 nanoparticles thereby promoting efficient flow of electrons that leads to enhanced reduction rates. The removal capacities for Fe–Ni NP’s, FeNi-in-situ-25% and FeNi-load-10% after 5th, 12th and 7th cycle respectively restored via chemical treatment establishes the fact that these adsorbents may be successfully employed for continuos removal and/or degradation process. Thus, it can be concluded that

Fig. 8. Reusability of Fe–Ni NP’s, FeNi-in-situ-25% and FeNi-load-10% in BM degradation. {[BM]ini = 100 mg L1, [adsorbent] = 1 g L1}.

to obtain better longevity for nanoparticles towards sustainable efficiency, these nanoparticles need to be dispersed on a solid support that may have pronounced effects on the removal capacity and this strategy may be regarded as an effective tool for remediation of organic pollutants. 3.7. Leaching experiments For the effective usage of these adsorbents towards continuous removal of a pollutant, it is highly essential to determine the metal ion content in the treated aqueous solution. Therefore, the amount of iron leached from nanocomposites is monitored from the supernatant obtained after the last cycle of successive treatment using ICP-OES. These values are found 193 ppb for Fe–Ni NP’s after 5th cycle, 248 ppb for FeNi-in-situ-25% after 12th cycle and 214 ppb for FeNi-load-10% after 7th cycle. However, leaching of nickel is found to be <50 ppb implying that nickel is not corroded under the conditions employed for BM removal. It also indicates that Ni acts as an electron shuttle between BM and ZVI center of nanocomposites. Such a feature has already been noted for ZVI based bimetallic nanoparticles that are explored for degradation of variety of organic and inorganic pollutants. These findings also supports for stronger interaction between iron and nickel nanoparticles with MMT matrix and contributes very little or nothing to the metallic lixiviation. 4. Conclusions To summarize, the present investigations clearly demonstrate that the surface adsorption capacity of Fe–Ni nanoparticles is indeed enhanced through composite formation with MMT clay. This phenomenon is primarily responsible for efficient removal of BM molecule on nanocomposite surface plausibly due to synergic effects of Fe–Ni nanoparticles and MMT thereby generating effective reaction sites for adsorption and subsequent degradation of dye.

B.S. Kadu, R.C. Chikate / Chemical Engineering Journal 228 (2013) 308–317

Employing different adsorption models, the process of mineralization of BM is found to be strongly dependent on the mono- and/or multilayer association with the surface leading to thermodynamically favored exothermic chemisorption process. The mobility of BM molecule is found to be through pore diffusivity generating concentration gradient that facilitates the adsorption dynamics on the nanocomposite surface. These findings clearly demonstrate that the enhanced adsorption capacity of MMT is due to incorporation of nanoparticles which not only induces stronger adsorption but also favors degradation of adsorbed species. Furthermore, the overall BM removal capability (222–750 mg L1) per g of nanocomposites can be ascribed to appreciable free energy change in the adsorption process along with pore-diffusion phenomenon observed during successive recycles and therefore, they may be considered as potential adsorbents for continuous removal process. The striking feature of the present work is that these adsorbents are more superior towards mitigation of dyes and pigments than already existing nZVI-based treatment processes. Thus, the sustainable efficiency of nanocomposites towards environmental remediation of aquatic pollutants may be regarded as ‘‘Modified ZVI Technology’’. Acknowledgements Authors are thankful Dr. A.D. Natu Head, Dept. of Chemistry and Principal, A.G. College, for constant encouragement and support. DST, New Delhi is acknowledged for providing FIST grant. Appendix A. Supplementary material Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.cej.2013.04.103. References [1] Y. He, J. Gao, F. Feng, C. Liu, Y. Peng, S. Wang, The comparative study on the rapid decolorization of azo, anthraquinone and triphenylmethane dyes by zero-valent iron, Chem. Eng. J. 179 (2012) 8–18. [2] M.R. Hoffmann, S.T. Martin, W. Choi, D.W. Bahamann, Environmental applications of semiconductor photocatalysis, Chem. Rev. 95 (1995) 69–96. [3] Y.H. Ni, L.N. Jin, L. Zhang, J.M. Hong, Honeycomb-like Ni@C composite nanostructures: synthesis, properties and applications in the detection of glucose and the removal of heavy-metal ions, J. Mater. Chem. 20 (2010) 6430– 6436. [4] C. Wang, S.Y. Tao, W. Wei, C.G. Meng, F.Y. Liua, M. Han, Multifunctional mesoporous material for detection, adsorption and removal of Hg2+ in aqueous solution, J. Mater. Chem. 20 (2010) 4635–4641. [5] X.B. Wang, W.P. Cai, Y.X. Lin, G.Z. Wang, C.H. Liang, Mass production of micro/ nanostructured porous ZnO plates and their strong structurally enhanced and selective adsorption performance for environmental remediation, J. Mater. Chem. 20 (2010) 8582–8590. [6] K. Wang, C. Lin, M. Wei, H. Liang, H. Li, C. Chang, Y. Fang, S. Chang, Effects of dissolved oxygen on dye removal by zero-valent iron, J. Hazard. Mater. 182 (2010) 886–895. [7] W. Zhang, X. Quan, J. Wang, Z. Zhang, S. Chen, Rapid and complete dechlorination of PCP using Ni–Fe nanoparticles under assistance of ultrasound, Chemosphere 65 (2006) 58–64. [8] X. Li, D.W. Elliott, W. Zhang, Zero-valent iron nanoparticles for abatement of environmental pollutants: materials and engineering aspects, Cri. Rev. Solid State Mater. Sci. 31 (2006) 111–122. [9] Y. Lin, C. Weng, F. Chen, Effective removal of AB24 dye by nano/micro-size zero-valent iron, Sep. Purif. Technol. 64 (2008) 26–30. [10] F.S. Freyria, B. Bonelli, R. Sethi, M. Armandi, E. Belluso, E. Garrone, Reactions of acid orange 7 with iron nanoparticles in aqueous solutions, J. Phys. Chem. C. 115 (2011) 24143–24152. [11] H.L. Lien, W.X. Zhang, Nanoscale Pd/Fe bimetallic particles: catalytic effects of palladium on hydrodechlorination, Appl. Catal. B: Environ. 77 (2007) 110–116.

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