Preparation of silica mesoporous nanoparticles functionalized with β-cyclodextrin and its application for methylene blue removal

Preparation of silica mesoporous nanoparticles functionalized with β-cyclodextrin and its application for methylene blue removal

Journal of Molecular Liquids 209 (2015) 239–245 Contents lists available at ScienceDirect Journal of Molecular Liquids journal homepage: www.elsevie...

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Journal of Molecular Liquids 209 (2015) 239–245

Contents lists available at ScienceDirect

Journal of Molecular Liquids journal homepage: www.elsevier.com/locate/molliq

Preparation of silica mesoporous nanoparticles functionalized with β-cyclodextrin and its application for methylene blue removal Azra Ebadi, Amir Abbas Rafati ⁎ Department of Physical Chemistry, Faculty of Chemistry, Bu-Ali Sina University, P.O. Box 65174, Hamedan, Iran

a r t i c l e

i n f o

Article history: Received 18 April 2015 Received in revised form 31 May 2015 Accepted 2 June 2015 Available online xxxx Keywords: Methylene blue Silica nano hollow sphere Adsorption Functionalization Cyclodextrin

a b s t r a c t Silica nano hollow sphere was successfully modified to βCD-SNHS as a new adsorbent to remove methylene blue (MB) (as a model) from aqueous solution. Adsorption behaviors of dyes (MB) onto βCD-SNHS were studied from equilibrium and kinetic viewpoints. The equilibrium data could be well described by several isotherms. The βCDSNHS nanoparticles contributed to the enhancement of the adsorption capacities because of the strong abilities of the hydroxyl groups and the inner cores of the hydrophobic cavity in βCD to form complexes with organic pollutants. Thus, the synthesized βCD-SNHS particles can be a potential material for in situ remediation of contaminated surface and ground water. The prepared nanoparticle adsorbents were characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR) and N2 adsorption–desorption measurement (BET). The prepared nanoparticles have 40–100 nm diameters. Host–guest interactions between cyclodextrin and organic molecules had a great contribution to the adsorption of organic pollutants. These nanoparticles could be applied in the elimination, enrichment and detection of some environmental pollutants. The equilibrium data were modeled using seven isotherm models and fit well to the Toth model. The kinetic results were followed to modified pseudo-n-order (MPnO). The adsorption of MB onto βCD-SNHS was found to be dependent on pH. © 2015 Elsevier B.V. All rights reserved.

1. Introduction Effluent of chemical industries such as textiles, paper, color photography, printing, dye and food industries that consist of a large amount contaminants such as dyes and paints poses a threat to agriculture and the food chain and consequently to human health. Besides, over 10,000 different dyes and pigments have been applied in those industries. Synthetic dyes usually have complex aromatic molecular structures which make them more stable to biodegradation and oxidizing agents. Therefore, it is essential to treat dye wastewater before exposure to water resources of environment. Several methods to find a suitable technology for removal of dyes have been studied including adsorption, sedimentation, membrane processes, photocatalytic degradation and biological treatment [1–15]. Among the proposed methods, adsorption technique is one of the most suitable and low cost technique to remove dyes and effluent treatment. Various adsorbents have been studied to remove dyes from aqueous solutions, such as activated carbon [16], MCM41 and MCA [17], graphene oxide [18], mesoporous SiO2 [19], polymer-clay [20], alumina [2], agricultural wastes [21–25] and β-cyclodextrin-based polymers [26].

⁎ Corresponding author. E-mail addresses: [email protected], [email protected] (A.A. Rafati).

http://dx.doi.org/10.1016/j.molliq.2015.06.009 0167-7322/© 2015 Elsevier B.V. All rights reserved.

Several mesoporous silicas have been functionalized with different ligands and used for removal of some heavy metal ions from water. The modifications of SBA-15 and MCM-41 with 2-mercapto thiazoline, 2-mercaptopyridine, or 2-mercaptobenzothiazol and MCM-48 with benzoyl thiourea were recently reported [27–30]. But there are a few earlier reports on the functionalization of silica nanoparticles with βcyclodextrin for its application as adsorbent or carrier of organic materials. The objective of this work is synthesis and characterization of a new silica adsorbent, i.e., nano-hollow sphere silica, functionalized with βCD groups, aiming for future applications in water treatment. Cyclodextrins are a series of cyclic oligosaccharides which are produced by the action of amylase on starch. These compounds are able to form inclusion complexes in solution or in the crystalline state with various compounds such as amines, acids, aliphatic and aromatic hydrocarbons [27]. Besides, the application of mesoporous silica due to their high surface area, large pore volume and good performance as adsorbent, catalyst supports, and carriers for drug delivery has attracted great attention [28–30]. In this paper we have used β-CD derivative in preparation of adsorbent for the removal of methylene blue (MB) from aqueous solution. We have synthesized amino-functionalized silica nano hollow sphere by 3-aminopropyltrimethoxysilane (APTS) as a pore expander and then modified with tosyl-β-CD. These materials were characterized using scanning electron microscopy (SEM) and Fourier transform

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several times to remove unreacted materials. Final product was dried at ambient temperature. To remove surfactant template, the white precipitate was placed in furnace for 3 h and 550 °C.

2.3. Amino-functionalized silica nanoparticles Scheme 1. The structure of methylene blue.

infrared spectroscopy (FT-IR) analysis. The adsorption ability of βCDSNHS was studied in the removal of MB from both equilibrium and kinetics point of view. Also for choose the best model of isotherm and kinetic adsorption, error analysis was investigated.

0.5 g of nanoparticles and 0.6 mL APTS were mixed with 25 mL of toluene and were refluxed for 2 h. The obtained product was filtrated and washed with toluene. After that it was placed in an oven in 120 °C. Then to remove unreacted APTS the obtained precipitate was mixed with 50 mL water and stirred for 30 min and dried at 100 °C [32]. 2.4. Preparation of mono-tosyl-β-cyclodextrin (Ts-β-CD)

2. Exprimental 2.1. Materials Cetyltrimethylammonium bromide (CTAB), tetraethyl orthosilicate (TEOS, ≥ 98%, Merck) as a silylation agent and 3-aminopropyl triethoxysilane (APTS), MB (the structure of MB was shown in Scheme 1.), β-CD, pyridine, dimethylformamide (DMF), diethyl ether, tosyl chloride, ammonia solution (25%, Scharlau), ethanol (≥ 99.9%, Merck), and toluene (≥99%, Merck) were of analytical grade and used without further treatment.

A solution of β-CD (8 mmol) and 50 mL dry pyridine was prepared and stirred at room temperature by a magnetic stirrer. Then ptoluenesulfonyl chloride (6 mmol) was added to this solution. The temperature of solution was adjusted at 2–4 °C for 8 h. After that, the solution was stirred for 48 h at room temperature. A white precipitate was obtained by adding the final solution to diethyl ether. A pure precipitate was obtained by washing with water and acetone repeatedly. The procedure is summarized in Scheme 2. 2.5. Modification of silica nano hollow sphere containing CD molecules

2.2. Synthesis of mesoporous silica nanoparticles Silica nanoparticles were prepared by sol–gel method. A certain amount of CTAB was solved by stirring into 100 mL de-ionized water and sonication by prob sonicator for 2 min [31]. Then 2 mL NH3 solution and 1 mL TEOS were added dropwise to the solution. After 10 min, colloidal product was centrifuged and washed with water and ethanol

For the preparation of βCD-SNHS, initially 1 g of amino functionalized silica nanoparticle was dispersed in 25 mL DMF at room temperature. Then the solution of 0.125 g of Ts-β-CD and 10 mL DMF was added to it and was refluxed under nitrogen atmosphere at 60 °C. The obtained product was centrifuged and washed with DMF and acetone repeatedly. Then the final product was dried at room temperature.

NH / TEOS

Calcination

3

Self-assemble

APTS

Toluen

CTAB

NH2 Si

O O

CH OTs

CH OH

2

2

O

P-TsCl Pyridine, 2-4 °C

DMF

60 °C

H N O

Si O O

Scheme 2. Schematic representation of the preparation steps of βCD-SNHS.

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241

(b)

(a)

1µm

200nm

Fig. 1. Low (a) and high (b) magnification SEM images of prepared silica hollow sphere.

2.6. Characterization of the modified silica nanoparticles FT-IR spectroscopy was performed by a Perkin-Elmer Spectrum GX FT-IR spectrometer and spectra were recorded between 550 and 4000 cm−1 using KBr pellets. Structure of nanoparticles was identified by SEM images. BET surface area measurements were conducted using surface area analyzer (Nova 2000, Quantachrome Instruments, FL, USA) using nitrogen (99.99% purity) as the adsorption gas. The sample was slowly heated to 300 °C for 3 h under a nitrogen atmosphere. To obtain the BET specific surface area measurements, the different precursors were evacuated at −196 °C for 66 min. 2.7. Adsorption study 2.7.1. Equilibrium studies The equilibrium experiments were performed by adding 0.01 g of new adsorbent into 7 mL of the solutions with different concentration

(5–140 ppm) of MB. All of the solutions were placed in shaking thermostat (N-BIOTEK, NB-300) for 24 h at 27 °C and shaking speed of 160 rpm to attain equilibrium conditions. Then the residual dye solution was analyzed using UV–vis spectrophotometer at 665 nm. The equilibrium adsorption capacity per unit mass, qe, was calculated with the following equation (mg/g) qe ¼

C 0 −C e V m

ð1Þ

where C0 (mg/g) is the initial concentration, Ce (mg/L) is the concentration of dye after equilibrium time, V (L) is the solution volume, and m (g) is the mass of the adsorbent. 2.7.2. Kinetic studies (contact time effect) The effect of contact time and kinetic experiments were performed at two different initial concentrations of MB (50 and 80 mg/L). For this study an amount of 0.01 g adsorbent was added into 5 mL MB solutions each with a certain concentration and was placed in the shaking

Fig. 2. FT-IR spectrum of prepared adsorbents.

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70

Table 2 The values of error function for isotherm models of MB adsorption onto βCD-SNHS.

60

Isotherm model

Error function

Error value

Langmuir

χ2 RMSE ERRSQ R2 χ2 RMSE ERRSQ R2 χ2 RMSE ERRSQ R2 χ2 RMSE ERRSQ R2 χ2 RMSE ERRSQ R2 χ2 RMSE ERRSQ R2 χ2 RMSE ERRSQ R2

6063 1.7108 26.3415 0.9944 11.5731 3.3134 98.8099 0.9803 1.7529 1.7261 26.8156 0.9945 1.7590 1.8708 31.5008 0.9945 22.8292 4.0793 149.7713 0.9683 1.2513 1.8258 30.0020 0.9942 1.6474 1.7759 28.3851 0.9944

qe(mg/g )

50 Freundlich

40 30

Toth

20 Redlich–Peterson

10 Tempkin

0 0

20

40

60

80 Sips

Ce (mg/L) Fig. 3. Adsorption isotherm for MB on βCD-SNHS.

Extended-Langmuir

thermostat with the agitation speed 160 rpm at 27 °C. Then at different time intervals the samples were centrifuged at 11,000 rpm for 2 min. The clarified solutions were analyzed using UV–vis spectrophotometer. The adsorption capacity qt (mg/g) of βCD-SNHS was calculated by the following equation:

qt ¼

C t −C e V m

ð2Þ

calculated by the following equation:

%Re ¼

C 0 −C e  100: C0

ð3Þ

2.9. Error analysis To evaluate the best isotherm model and mechanism for the adsorption, it is essential to use error analysis. We calculated three error functions such as (a) non-linear chi-square test (χ2), (b) the sum of the squares of errors (ERRSQ) and (c) residual root mean square error (RMSE) [33].

where Ct is the concentration of dye at time t. 2.8. The effect of pH The pH value of dye solution has a considerable role in all of adsorption process and especially in adsorption capacity. In this work, the effect of initial pH on adsorption capacity was investigated in the range of 3–11 at concentration of 10 mg/L of dye. The initial pH was adjusted using sodium phosphate buffer. 0.01 g of adsorbent was added to 8 mL solution of dye and was left in the shaking thermostat with 160 rpm speed at 27 °C for 12 h. The supernatant was analyzed by UV–vis spectrophotometer. Adsorption percent of MB onto adsorbent was

3. Results and discussion 3.1. Characterization of adsorbent The structure of the synthesized nanoparticles was investigated by SEM. Fig. 1 shows the low and high magnification SEM images of the obtained nanoparticles which show regular sphere nanoparticles with radius less than 100 nm.

Table 1 Isotherm parameters for adsorption of methylene blue onto βCD-SNHS.  

KF

KR

1 n

αR

bT

β

a

AT

Ref.

0.02

















[38]

4.84 –

– –

0.60 –

– –

– 156.98







– –

– 0.49

[39] [40]

Redlich–Peterson (R–P) Toth

– 99.22

– –

– –

2.5 –

– 0.90

0.03 –

– 0.02

0.97 –

– –

– –

[41] [42]

Extended-Langmuir

96.85

0.02













0.1

Sips

86.58

0.02





1.05









Equation

Isotherm models

qm

qm K L C e qe ¼ 1þK L Ce

Langmuir

91.88

qe = KFC1/n  e qe ¼ RT ; ln AT C e bT

Freundlich Tempkin

qe = KRCe/(1 + αRCβe ) h i1=nT nT qe ¼ qm bT C e = 1 þ ðbT C e Þ  pffiffiffiffiffiffiffiffiffiffiffi qe ¼ q m K L C e = 1 þ K L C e þ a K L C e   1 1 qe ¼ qm KC ne = 1 þ KC ne

KL

l mg

[43] –

[44]

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70

the bonding vibration of N–H group as well as the wide peak at 3440 cm−1 for N–H stretching. Then with consideration to above results we prepared amino functionalized silica nanoparticles. The spectrum of βCD-SNHS displays two peaks at 1391 and 1664 cm−1 that related to existence the cross-linked structure of β-cyclodextrin onto silica nanoparticles [34]. Thus, all the above results indicate that β-CD has been grafted successfully on silica nanoparticle hollow sphere. The BET measurement was performed for SNHS and βCD-SNHS and specific surface areas were calculated. It is noted that the sample exhibits a BET surface area of 919 and 754 m2 g− 1 before and after functionalization, which is much higher than the values for mesoporous silica particles reported in the literatures [35–37].

60 50

qe(mg/g)

243

40 30 20

10 0

3.2. Adsorption isotherm models

-10

0

10

20

30

40

50

60

70

Adsorption isotherms are the essential aspect for the design of adsorption systems and data analysis. The relationship between the adsorption capacity (qe) and concentration of solution after adsorption at a certain temperature is called as the adsorption isotherm. Fig. 3 illustrates the effect of initial concentration of MB solution on adsorption capacity. It could be seen that the initial concentration has a significant role to enhance mass transfer of the MB as a driving force for adsorption. The equilibrium data was fitted with Langmuir (L) [38], Freundlich (F) [39], Tempkin [40], Redlich–Peterson (R–P) [41], Toth [42], Extended Langmuir (E-L) [43] and Langmuir–Freundlich (Sips) [44] models. Tables 1 and 2 tabulate the model parameters and their results of error analysis functions. According to the obtained parameters, the best fitted model is Toth. Fig. 4 shows the nonlinear fitted curves with different isotherm models for adsorption of MB on βCD-SNHS. Table 3 lists a comparison of maximum adsorption capacities of the samples obtained in this study with some various adsorbents previously used for the removal of MB [45–51]. It can be seen the βCD-SNHS has higher adsorption ability than that of most adsorbents reported in other literatures.

80

Ce(mg/L) Fig. 4. The nonlinear fitted curves with different isotherm models for adsorption of MB onto βCD-SNHS: Experimental data point (●), Langmuir (×), Freundlich (−−−−), Toth (\ \\ \\ \), R–P (□), L–F (△), Tempkin (−), E-L (+).

Fig. 2 illustrates FT-IR spectra of nanoparticles (a), aminefunctionalized nanoparticles (b) and β-CD functionalized nanoparticles (c). The wide peak at the IR absorption band from 3000 to 3500 cm−1 is related to O–H and N–H bond stretching vibration. Two asymmetric and symmetric peaks at 1091 cm−1 and 817 cm−1 were assigned to Si–O–Si vibration. Fig. 2(b) shows a clear peak at 1632 cm−1 that is related to

Table 3 Maximum adsorption capacities for the adsorption of MB onto various adsorbents. Adsorbent

Adsorption capacity (mg/g)

Ref.

MG Clay CNTs Magnetic rectorite Magnetic chitosan MCNT Halloysite Garlic peel β-CD-SNHS

24.88 6.3 46.2 31.18 60.4 43.86 84.3 82.6 99.22

[45] [46] [47] [48] [49] [45] [50] [51] This work

3.3. Kinetics models In order to study the mechanisms of MB adsorption on the βCDSNHS kinetic, data of the adsorption for two solution with different initial concentrations (50 and 80 mg/L) were fitted to seven kinetic models: the pseudo-first-order (PFO) [52], pseudo-second-order (PSO) [53], Elovich [54], mixed 1,2-order (MOE) [55], modified pseudo-n-order (MPnO) [56], fractal-like pseudo-first order (FL-PFO)

Table 4 The calculated parameters according to kinetic models for adsorption of MB onto βCD-SNHS at 27.0 °C. Kinetic model

Equation

PFO PSO MOE

qt = qe(1 − Exp(−k1t)) qt = k2q2e t/(1 + k2qet)   1−Expð−k1 t Þ qt ¼ qe 1− F 2 Expð−k1 t Þ 1 qt ¼ b ; ln ð1 þ abt Þ  1=n n−1 qt ¼ qe 1−e−nkqe t

Elovich MPnO

qe

FL-PSO FL-PFO

qt = kq2e tα/(1 + kqetα)  α qt ¼ qe 1−e−kt

PFO PSO MOE

qt = qe(1 − Exp(−k1t)) qt = k2q2e t/(1 + k2qet)   1−Expð−k1 t Þ qt ¼ qe 1− F 2 Expð−k1 t Þ 1 qt ¼ b ; ln ð1 þ abt Þ  1=n n−1 qt ¼ qe 1−e−nkqe t

Elovich MPnO FL-PSO FL-PFO

kq2e tα/(1

α

qt = + kqet )  α qt ¼ qe 1−e−kt



mg g



k1

l s

k2



g mgs



F2

a

b

n

α

– – –

– – –

– – –

c0 = 50 mg/l 19.11 – 24.39 – 19.11 –

0.004 – 0.0041

– 10–4 –

– – 3 × 10−4

– – –











0.11

0.143

18.14

0.0686











19.71 18.06

10−5 4 × 10−4

0.005 – 0.0049

– 10–4 –

– – 0.01

– – –











29.17

0.0042









– –

– –

−5

3 × 10 0.0031

– 1.62 1.45

c0 = 80 mg/l 29.11 – 36.26 – 29.35 –

31.03 28.78

0.5

– – –

– – –

– – –

0.22

0.102









1.05



– –

– –

– –

1.4 1.1

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Table 5 The values of error function for kinetic models of MB adsorption onto βCD-SNHS. Kinetic model

Error function

C0 = 50 (mg/L)

C0 = 80 (mg/L)

Pseudo-first order

χ2 RMSE ERRSQ R2 χ2 RMSE ERRSQ R2 χ2 RMSE ERRSQ R2 χ2 RMSE ERRSQ R2 χ2 RMSE ERRSQ R2 χ2 RMSE ERRSQ R2 χ2 RMSE ERRSQ R2

9.8519 1.4035 17.7295 0.9724 13.1550 1.8826 31.8991 0.9506 18.3158 2.3740 50.7235 0.9211 10.0644 1.4087 17.8606 0.9724 0.4644 0.5252 2.4829 0.9968 1.0769 0.5556 2.7783 0.9956 0.0519 0.7467 5.0190 0.9922

3.7470 0.9273 7.7389 0.9964 6.7702 1.6794 25.3835 0.9887 14.1792 2.6501 63.2106 0.9707 3.1238 1.0557 10.0317 0.9963 2.4394 0.8033 5.8084 0.9968 1.5430 0.7718 5.3611 0.9975 0.4066 0.6577 3.8935 0.9982

Pseudo-second order

Elovich

MOE

MPNO

FL-PFO

FL-PSO

Fig. 6. The non-linear fitted curves with seven kinetic models for the adsorption of MB onto βCD-SNHS at initial concentration of 80 mg/L: Experimental data point (●), MPnO (□), FL-PFO (\ \), FL-PSO (\ \\ \\ \), PSO (+), PFO (×), MOE(Δ), Elovich (.....).

with studied seven kinetic models for MB solutions with concentration of 50 and 80 mg/g, respectively.

[56] and fractal-like pseudo-second order (FL-PSO) [56] models. The equations of these models are listed in Table 4. The calculated parameters using these kinetic models and their error functions are presented in Tables 4 and 5. For choosing the best mechanism for adsorption of MB onto βCD-SNHS it is essential to match values of error functions. According to the reported values in Tables 4 and 5 it is clear that the modified pseudo-n-order (MPnO) was the best-fitted kinetic model to describe the adsorption of MB onto βCD-SNHS. Figs. 5 and 6 show the effect of contact time on adsorption and the non-linear fitted curve

25

3.4. Effect of initial pH Fig. 7 illustrates the effect of solution pH on MB adsorption onto βCD-SNHS. It is clear that, as the pH value increased from 3 to 11 the removal percentage of MB was increased from 46.5 to 95.6%. This is related to the pH of the solution that affects on the surface charge of the adsorbent. The basic dye causes positive charge in solution when dissolved in water. At higher pH the surface of adsorbent may gain negative charged. Therefore the increase of adsorption at higher pH or in other words at alkaline medium could be described using the electrostatic attraction between positively charge of MB and the negatively charged active adsorption sites of βCD-SNHS surface due to the presence of more hydroxyl ions. At acidic pH the competitive effects between H+ ions and positive charges on functional groups of MB, and

120 100

15

% Re

qt (mg/g)

20

10

5

80 60 40

20 0

0 0

200

400

600

800

1000

1200

1400

t (min) Fig. 5. The non-linear fitted curves with seven kinetic models for the adsorption of MB onto βCD-SNHS at initial concentration of 50 mg/L: Experimental data point (●), MPnO (□), FL-PFO (\ \), FL-PSO (\ \\ \\ \), PSO (+), PFO (×), MOE (Δ), Elovich (.....).

0

2

4

6

8

pH Fig. 7. The effect of pH on adsorption process.

10

12

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also electrostatic repulsion of positively charged sites on the surface and dye molecules are factors that prevents the adsorption process. 4. Conclusion In this work, β-CD functionalized silica nanoparticles were fabricated by sol–gel method and its adsorption capacity for removal of MB was investigated. The results confirm that βCD-SNHS is a suitable adsorbent for the removal of MB from aqueous solution. The adsorption isotherm data in attention to the highest correlation coefficient and error functions is well described by Toth model with a maximum adsorption capacity of 60.55 mg g−1. Toth isotherm model is designed for investigation of heterogeneous adsorption systems. The best pH value for adsorption of MB is 10.5 with maximum removal efficiency of 95.5%. Result of kinetic study shows that MPnO model is the best kinetic model for describing of MB adsorption onto βCD-SNHS system. Acknowledgments The authors greatly acknowledge Bu-Ali Sina University for the financial support due to Grant No. 32-1194. References [1] M. Zarezadeh-Mehrizi, A. Badiei, A. Rashidi Mehrabadi, J. Mol. Liq. 180 (2013) 95. [2] A. Mittal, D. Kaur, A. Malviya, J. Mittal, V.K. Gupta, J. Colloid Interface Sci. 337 (2009) 345. [3] A. Mittal, J. Mittal, A. Malviya, D. Kaur, V.K. Gupta, J. Colloid Interface Sci. 342 (2010) 518. [4] X. Yan, Li Chai, Q. Li, Sep. Sci. Technol. 48 (2013) 1442. [5] V.P. Kasperchik, A.L. Yaskevich, A.V. Bil'dyukevich, Pet. Chem. 52 (2012) 545. [6] V.K. Gupta, R. Jain, A. Mittal, T.A. Saleh, A. Nayak, S. Agarwal, S. Sikarwar, Mater. Sci. Eng. C 32 (2012) 12. [7] O. Monge-Amaya, J.L. Valenzuela-García, E. Acedo Félix, M.T. Certucha-Barragán, A.L. Leal-Cruz, F.J. Almendariz-Tapia, Miner. Process. Extr. Metall. Rev. 34 (2013) 422. [8] T.A. Saleh, V.K. Gupta, Environ. Sci. Pollut. Res. 19 (2012) 1224. [9] V.K. Gupta, S.K. Srivastava, D. Mohan, S. Sharma, Waste Manag. 17 (1998) 517. [10] V.K. Gupta, I. Ali, T.A. Saleh, A. Nayak, S. Agarwal, RSC Adv. 2 (2012) 6380. [11] V.K. Gupta, R. Jain, A. Nayak, S. Agarwal, M. Shrivastava, Mater. Sci. Eng. C 31 (2011) 1062. [12] T.A. Saleh, V.K. Gupta, J. Colloid Interface Sci. 371 (2012) 101. [13] H. Khani, M.K. Rofouei, P. Arab, V.K. Gupta, Z. Vafaei, J. Hazard. Mater. 183 (2010) 402. [14] S. Karthikeyan, V.K. Gupta, R. Boopathy, A. Titus, G. Sekaran, J. Mol. Liq. 173 (2012) 153.

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