application of response surface methodology to optimize the process variables for fluoride ion removal using maghemite nanoparticles

ORIGINAL ARTICLEApplication of response surface methodology to optimize the process variables for fluoride ion removal using maghemite nanoparticles Department of Chemistry, Shahre-Qods B

ORIGINAL ARTICLE

Application of response surface methodology to optimize the process variables for fluoride ion removal

using maghemite nanoparticles

Department of Chemistry, Shahre-Qods Branch, Islamic Azad University, Tehran, Iran

KEYWORDS

Adsorption;

Fluoride;

Box–Behnken design;

Maghemite (c-Fe 2 O 3 )

nano-particles;

Thermodynamics studies

Abstract Adsorption of fluoride ion was done from its aqueous solution by using maghemite (c-Fe2O3) nanoparticles Effects of the major independent variables (temperature, adsorbent dose and pH) and their interactions during fluoride ion adsorption were determined by response surface methodology (RSM) based on three-level three-factorial Box–Behnken design (BBD) Optimized values of temperature, maghemite nanoparticle dose and pH for fluoride sorption were found as

313 K, 0.5 g/L, and 4, respectively In order to investigate the mechanism of fluoride removal, var-ious adsorption isotherms such as Langmuir, Freundlich, Temkin and Florry–Huggins were fitted The experimental data revealed that the Langmuir isotherm gave a more satisfactory fit for fluoride removal The adsorption process was rapid and obeyed pseudo-second-order kinetics The values of thermodynamic parameters DG, DH and DS indicated that adsorption was spontaneous and endothermic in nature

ª 2013 King Saud University Production and hosting by Elsevier B.V All rights reserved.

1 Introduction

Fluoride is a health affecting substance The acceptable

fluo-ride concentration in drinking water is generally in the range

of 0.5–1.5 mg/L[38] The natural presence of fluoride generally

occurs through soil and rock formation in the form of

fluorap-atite, fluorspar and amphiboles, geochemical deposits, natural

water systems and earth’s crust [29,32] In addition to this

fluoride can also be found in various industrial activities, spe-cially semiconductor, electroplating, glass, steel, ceramic and fertilizer industries[31] Therefore higher fluoride concentra-tion causes severe harmful effects in aquatic life as well as in human bodies Excess intake of fluoride by human beings may lead to dental caries, bone fluorosis, and lesions of the thyroid, endocrine glands, and brain [32] Because of these reasons the pollution of water by fluoride has been a major concern The problems associated with fluoride ion pollution could be reduced or minimized by precipitation, ultra-filtra-tion, electrode-deposiultra-filtra-tion, reverse osmosis, etc., but these processes have high cost and poor removal efficiency Adsorp-tion has been found to be an effective and economic method with high potential for the removal, recovery and recycle of fluoride ions from wastewater[4], although desorption is an issue In the past decade, the synthesis of spinel magnetite

* Tel./fax: +98 (21)22873079.

E-mail address: ali.fakhri88@yahoo.com

Peer review under responsibility of King Saud University.

Production and hosting by Elsevier

King Saud University Journal of Saudi Chemical Society

www.ksu.edu.sa www.sciencedirect.com

1319-6103 ª 2013 King Saud University Production and hosting by Elsevier B.V All rights reserved.

and maghemite nanoparticles has been intensively developed

not only for its great fundamental scientific interest but also

for many technological applications in biology[39,9], medical

applications[23], bioseparation[8,16], separation and

precon-centration of various anions and cations[33]and pollutant

re-moval[34,36,37]due to their structural, electronic, magnetic

and catalytic properties Nano-iron oxides, such as magnetite

(Fe3O4) and maghemite (c-Fe2O3), and also different ferrite

compounds have unique magnetic and electronic properties

Due to their chemical stability, biocompatibility and heating

ability, ferrofluids of maghemite nanoparticles can be used

for ferrofluids hyperthermia in tumor treatment[15,30]

Re-sponse surface modeling (RSM) is an empirical statistical

tech-nique that uses quantitative data obtained from appropriately

designed experiments to determine regression model and

oper-ating conditions[20,6,18,7,12,26,28,40] RSM is a technique to

design factorial experiments, in order to build mathematical

models which allow one to assess the effects of several factors

onto a desired response It is suitable for multi-factor

experi-ments and searches the common relationship between various

factors for the most favorable conditions of the processes This

paper is mainly concerned with the investigation of a combined

effect of various process parameters like adsorbent dose,

tem-perature and pH of the solution on removal of fluoride ion

from aqueous medium by maghemite nanoparticles using

Box–Behnken model experimental design in Response Surface

Methodology (RSM) by Design Expert Version 6.0.10 (Stat

Ease, USA)

2 Materials and methods

2.1 Raw materials

Iron(II) chloride (FeCl2), Iron(III) chloride (FeCl3) and

Sodium hydroxide were supplied by Sigma–Aldrich, Germany

Sodium fluoride salt (NaF) (molecular weight, 41.98871 g/mol)

andD-sorbitol were supplied by Merck, Germany (maximum

purity available) Doubly distilled deionized water (HPLC

grade 99.99% purity) was obtained from Sigma–Aldrich Co

(Germany)

2.2 Preparation of maghemite nanoparticles

There are various methods for the preparation of c-Fe2O3,

using different reagents for the synthesis In this paper the

nanoparticles were prepared by coprecipitation of ferrous

ion (Fe2+) and ferric ion (Fe3+) with NaOH solution.D

-sor-bitol was used to prevent the agglomeration between the

nanoparticles [33] The iron solutions were strongly stirred

in water, after adding NaOH solution The precipitates were

separated by magnetic decantation or slow filtration after

which it was washed several times with distilled water and

ethanol The magnetite nanoparticles were dried into an oven

at 60C In order to obtain maghemite (c-Fe2O3), the

magne-tite nanoparticle was heated at 200C, for 3 h and finally,

red–brown maghemite nanoparticles were collected

Trans-mission electron microscopy (TEM, JEM-2100F HR,

200 kV) and X-ray diffractometer (XRD) Philips X’Pert were

used to characterize the adsorbent for its morphological

information

2.3 Adsorption experiment

The adsorption of fluoride onto maghemite nanoparticles was investigated using batch experiments In these studies

1000 mg/L stock solution was prepared by dissolving 1 g of NaF in 1000 mL distilled water Different concentrations (25–75 mg/L) of fluoride solutions were prepared by this stock solution Solutions were evacuated to flasks of 100 mL Then adsorbent in the range of dosage 0.25–0.75 g/L was added and placed in the water bath shaker after pH adjustments made in the range of 4–12 The suspensions were shaken at

2000 rpm for 12 min at room temperature These experiments were conducted duplicate Samples from shaker were filtered with filter paper, and then remaining fluoride levels were mea-sured using a fluoride electrode (Orion, 9606BNWP) The equilibrium adsorption capacity was calculated from the relationship

qe¼ðCo CeÞV

where, qe(mg/g) is the equilibrium adsorption capacity, Ceis the fluoride concentration at equilibrium (mg/L), V is the vol-ume of solution (l) and W is the weight of adsorbent (g) 2.4 Response surface methodology

The three-level Box–Behnken experimental design with categorical factor was employed to optimize the adsorption capacity of the maghemite nanoparticles for fluoride (re-sponse) The design was composed of three levels (low, medium and high) and a total of 17 runs were carried out

to optimize the chosen variables, such as temperature, maghemite nanoparticle dosage and pH For the purpose of statistical computations, the three independent variables were denoted as x1, x2, and x3, respectively According to the preliminary experiments, the range and levels used in the experiments are selected and listed in Table 1 The main effects and interactions between factors were determined The experimental design matrix by the Box–Behnken design

is tabulated inTable 2 For RSM, the most commonly used second-order polynomial equation developed to fit the exper-imental data and determine the relevant model terms can be written as:

Y¼ b0þXk

i¼1

bixiþXk i¼1

biix2

i þXk 16i6j

bijxixjþ e ð2Þ

where Y represents the predicted response, i.e the adsorption capacity for fluoride by the maghemite nanoparticles (mg/g),

b0, the constant coefficient, bi, the ith linear coefficient of the input factor xi, bii, the ith quadratic coefficient of the input

Table 1 Factors and levels used in the factorial design

(1)

Medium level (0)

High level (+1)

Maghemite dosage (X 2 ) 0.25 g/L 0.50 g/L 0.75 g/L

factors xi, bij, the different interaction coefficients between

in-put factors xiand xj(i = 1–3, j = 1–3 and i/ = j), and e, the

error of the model[5] The equation expresses the relationship

between the predicted response and independent variables in

coded values according toTables 1 and 2

3 Results and discussion 3.1 Characterization of maghemite nanoparticles

Particle size distribution is calculated from TEM images by measuring the diameter of 100 particles randomly chosen FromFig 1A, it can be seen that the homemade maghemites have the most even particle.Fig 1B shows that the fluoride molecules possible into the adsorbent surface are covered The XRD pattern of maghemite nanoparticles is shown in

Fig 1C It shows that no other phases other than maghemite exist in the products The intensity change and peak broaden-ing of the XRD patterns of maghemites are due to a change in particle size of the nanoparticles which is in good agreement with the particle size: the smaller the particle the weaker is the intensity and broader are the peaks

3.2 Statistical analysis

The optimum conditions for adsorption of fluoride onto the surface of maghemite nanoparticles were determined by means

of the BBD under RSM The results are displayed inTable 3

In this way, the fluoride uptake by maghemite nanoparticles could be expressed using the following equation:

Y¼ 22:474 þ 2:476X1þ 1:241X2 2:445X3 2:650X1X2

þ0:147X1X3 2:472X2X3þ 9:095X2 0:879X2þ 6:873X2

ð3Þ

Table 2 BBD and results for the study of three experimental

variables in coded units

Figure 1 TEM images of maghemite nanoparticles (A), maghemite nanoparticles after adsorption (B) of fluoride ion and XRD pattern

of maghemite nanoparticles (C)

where, X1, X2and X3are temperature, maghemite dosage and

pH factors, respectively The quality of the fitted model was

expressed by the coefficient of determination, R2 The R2

coef-ficient gives the proportion of the total variation in the

re-sponse predicted by the model and a high R2value (close to

1) is desirable Eq (3) demonstrated that the model is well

fit-ted, considering the determination coefficient (R2

(adj) = 97.71%) and only 2.29% of total variation was not

ex-plained by the model

The estimated effects and coefficients for model are listed in

Table 3 Model terms were evaluated by the P-value

(probabil-ity) with 95% confidence level The P-values were used to

esti-mate whether F was large enough to indicate statistical

significance and used to check the significance of each

coeffi-cient The P-values lower than 0.05 indicated that the model

and model terms were statistically significant All the factors

and their square interactions (P < 0.05) except for interaction

of temperature–temperatureðX2

1Þ and pH–pH ðX2

3Þ were signif-icant at the 95% confidence level

Fig 2as can be seen the data points were well distributed

close to a straight line (R2= 0.9726), which suggested an

excellent relationship between the experimental and predicted

values of the response, and the underlying assumptions of the above analysis were appropriate The results also indicated that the selected quadratic model was adequate in assuming the response variables for the experimental data

The effect of pH in the range of 4.0–12.0 on the removal of fluoride was investigated using 0.01 mol/L HCl or NaOH solu-tions for pH adjustment The amount of adsorption decreased

by increasing pH At higher pHs, the high negatively charged adsorbent surface sites did not favor the adsorption of depro-tonated fluoride due to electrostatic repulsion

3.3 3D response surface plot The surface plots of the response functions are useful in under-standing both the main and interaction effects of the factors

[11,2] These plots can be obtained by computations using developed response models and adequate software The re-sponse surface plots are reported in Fig 3 This figure also shows the estimated Y parameter as a function of the normal-ized independent variables The 3D surface plots of the re-sponse (Y) indicated the same results as observed in the interaction plot (Fig 2)

3.4 Adsorption isotherms

The ability of maghemite nanoparticles to adsorb fluoride from aqueous solutions is evaluated from the shape of the adsorption isotherm plot In the present study, isotherm data were applied to four adsorption models and the results of their linear regressions were used to find the model with the best fit Values of resulting parameters and regression coefficients (R2) are listed inTables 4 and 5

The correlation coefficient for the Langmuir isotherm was 0.9995, which is higher than the values obtained from the other isotherm models The experimental data fit very well to this isotherm model, and indicate that fluoride adsorption occurs

on monolayer surfaces, which is similar to the conclusion reached for maghemite nanoparticles[1]

3.5 Adsorption kinetics

According to the kinetic data obtained from the experiments, various models have been used to throw light on the

Table 3 Analysis of variance for the response of the adsorption capacity for fluoride ion

Figure 2 Plot of the experimental and predicted responses

mechanisms of adsorption and potential rate controlling steps.

Effects of contact time on adsorption are investigated, as

shown inFig 4 The adsorption process was quite rapid and

reached equilibrium in 30 min (Fig 4) In this experiment,

the pseudo-first-order, pseudo-second-order, and intra-particle

diffusion models were used to test the mechanism of fluoride

adsorption on maghemite nanoparticles

The pseudo-first-order rate equation is given as[22,41,42]

logðqe qtÞ ¼ logðqeÞ  k1

2:303

where qeand qt are the amounts of fluoride adsorbed (mg/g)

at equilibrium and at time t (min), respectively, and k1(L/

min) is the adsorption rate constant of first-order

adsorp-tion qe and k1were determined from the intercept and slope

of the plot which are shown in Table 6 From the data, qe

(calculated) and qe (experimental) values are not in

agree-ment with each other Therefore, that indicates the

adsorp-tion of fluoride on maghemite nanoparticles was not a

first-order reaction In addition, the experimental data were

also applied to the pseudo-second-order kinetic model

equa-tion [17,41,42]:

t

qt¼ 1

k2q2þ t

where k2 is the rate constant of pseudo-second-order chemi-sorptions (g/(mg min)) The plot t/qtversus t giving a straight line is shown inFig 5and the constant calculated from the slop and intercept of the plots is given inTable 6.Fig 5shows that R2values are higher than those obtained from the first-or-der kinetics In addition, theoretical and experimental qevalues are in agreement Therefore, it is possible to prove that the adsorption process using maghemite nanoparticles followed the second-order kinetic model (Table 7)

Figure 3 Response surface plots of adsorption capacity versus the effect of three variables

Table 4 Summary of equilibrium isotherms (KL, KF, B1, KT: Langmuir, Freundlich and Temkin constants; n: heterogeneity coefficient; qm: maximum adsorption capacity; qe: uptake at equilibrium; Ce: equilibrium concentration; B: activity coeffi-cient related to mean sorption energy; KFH: equilibrium constant; nFH: number of adsorbates occupying adsorption sites)

q e ¼ 1

K L q m þ C e

q m

C e ¼ log K FH þ n FH logð1  hÞ

The intra-particle diffusion equation can be described as:

where C is the intercept and kiis the intra-particle diffusion

rate constant (mg/g min0.5), which can be evaluated from the

slope of the linear plot of qtversus t1/2(Fig 6) The first

shar-per portion is due to the diffusion of adsorbate through the

solution to the external surface of the adsorbent and the

sec-ond portion represents the gradual adsorption procedure, that

is, the diffusion of adsorbate molecules inside the adsorbent

It is easy to find that kiof the first region was higher than ki

of the second region This indicates that the adsorption rate of

fluoride is higher in the beginning owing to the large surface

area of the adsorbent available for the adsorption The

adsor-bate formed a thick layer in the exterior gradually due to the

inter attraction and molecular association This blocked the

further adsorption and the uptake rate was limited by the rate

at which the adsorbate was transported from the exterior to

the interior sites of the adsorbent particles

3.6 Thermodynamic studies

Thermodynamic parameters related to the adsorption process, i.e., Gibbs free energy change (DG, kJ mol1), enthalpy change (DH, kJ mol1), and entropy change (DS,

J mol1K1) are determined by the following equations:

where Kc is the equilibrium constant, which can be obtained from Langmuir isotherm, R is the universal gas constant, 8.314 J mol1K1, and T is absolute temperature (K) DH and DS were obtained from the slope and intercept of the plot

of Gibbs free energy change, DG vs temperature, T (Fig 7) The negative values of DG (6.546, 7.853 and

9.370 kJ mol1for 283, 297 and 313 K, respectively) confirm the feasibility of the process and the spontaneous nature of

Table 5 Langmuir, Freundlich, Temkin and Florry–Huggins isotherm constants for adsorption of fluoride ion

0

10

20

30

40

50

60

70

80

q e

t (min)

25mg/L

50mg/L

75mg/L

Figure 4 Influence of contact time on fluoride removal (initial

pH: 4.0; adsorbent dose: 0.5 g/L)

Table 6 Kinetic parameters and experimental adsorption capacities for fluoride onto maghemite nanoparticles

q e,experimental (mg/g) 23.90 46.32 67.23 Pseudo-first-order model

Pseudo-second-order model

Figure 5 Second-order kinetic modeling of fluoride adsorption

on maghemite nanoparticles

adsorption with a high preference for fluoride onto maghemite

nanoparticles The standard enthalpy and entropy changes of

adsorption were determined from Fig 7 The value of DH

(20.102 kJ mol1) is positive, indicating that the adsorption

reaction is endothermic The positive value of DS

(94.100 J mol1K1) reflects an increase in the randomness at

the solid/solution interface during the adsorption process[27]

3.7 Regeneration studies

Desorption studies help to enucleate the nature of adsorption

and recycling of the spent adsorbent and the fluoride ion pH

of the experimental solution impressed fluoride ion adsorption inversely Desorption process was accomplished on loaded nanoparticles by mixing 0.02 g fluoride ion loaded maghemite nanoparticle with 10 mL of EtOH, DMF and 0.005 mol/L NaOH, solutions and the desorption turnover for them was calculated as 10%, 19%, and 88%, respectively Thus, the fluo-ride could be desorbed from the loaded nanoparticles by changing the pH of the solution to alkaline medium and NaOH solution has higher desorption turnover compared to the other eluents

5 Conclusions The ANOVA of the quadratic model demonstrates that the model was highly significant Maghemite nanoparticle dose was the most significant factor affecting fluoride removal Therefore, it is apparent that the response surface methodology not only gives valuable information on interactions between the factors but also helps to the recognition of possible optimum values of the studied factors Batch adsorption experiments indicate that the adsorption equilibrium can be achieved within

30 min The kinetics studies of fluoride on maghemite nanopar-ticles indicated that the adsorption kinetics of fluoride on maghemite nanoparticles followed the pseudo-second order at different initial concentrations The results of equilibrium data showed that the adsorption of fluoride on maghemite nanopar-ticles followed Langmuir isotherm Thermodynamic studies indicated that the fluoride adsorption onto maghemite nano-particles was spontaneous and endothermic

Acknowledgment The authors gratefully acknowledge supporting of this re-search by the Islamic Azad University Shahre-Qods Branch References

[1] A Afkhami, R Moosavi, Adsorptive removal of Congo red, a carcinogenic textile dye, from aqueous solutions by maghemite nanoparticles, J Hazard Meter 174 (2010) 398–403

[2] I.P Arbizu, C.J Luis Pe´rez, Surface roughness prediction by factorial design of experiments in turning processes, J Mater Process Technol 143 (2003) 390–396

[3] S Ayoob, A.K Gupta, Insights into isotherm making in the sorptive removal of fluoride from drinking water, J Hazard Mater 152 (2008) 976–985

Table 7 Comparison of fluoride ion adsorption with different adsorbents

Figure 6 Intra-particle diffusion model for adsorption of

fluo-ride on maghemite nanoparticles

Figure 7 Plot of Gibbs free energy change vs temperature for

fluoride ion adsorption onto maghemite nanoparticles

[4] S.E Bailey, T.J Olin, R.M Bricka, D.D Adrian, A review of

potentially low-cost sorbents for heavy metals, Water Res 33

(1999) 2469–2479

[5] K.Y Benyounis, A.G Olabi, M.S.J Hashmi, Effect of laser

welding parameters on the heat input and weld-bead profile, J.

Mater Process Technol 164 (2005) 978–980

[6] D Bingol, N Tekin, M Alkan, Brilliant Yellow dye adsorption

onto sepiolite using a full factorial design, Appl Clay Sci 50

(2010) 315–321

[7] D Bingo¨l, Removal of cadmium (II) from aqueous solutions

using a central composite design, Fresenius Environ Bull 10

(2011) 2704–2709

[8] S Bucak, D.A Jones, P.E Laibinis, T.A Hatton, Protein

separations using colloidal magnetic nanoparticles, Biotechnol.

Prog 19 (2003) 477–484

[9] J.W.M Bulte, Intracellular endosomal magnetic labeling of

cells, Methods Mol Med 124 (2006) 419–439

[10] L Chen, H.X Wu, T.J Wang, Y Jin, Y Zhang, X.M Dou,

Granulation of Fe–Al–Ce nano-adsorbent for fluoride removal

from drinking water by spray coating on sand in a fluidized bed,

Powder Technol 193 (2009) 59–64

[11] C Cojocaru, G.Z Trznadel, Response surface modeling and

optimization of copper removal from aqua solutions using

polymer assisted ultrafiltration, J Membr Sci 298 (2007) 56–70

[12] D Das, N Das, Response surface approach for the bisorption

of Ag(I) by Macrofungus Pleurotus platypus, CLEAN – soil,

air, Water 2 (2011) 157–161

[13] A.A.M Daifullah, S.M Yakout, S.A Elreefy, Adsorption of

fluoride in aqueous solutions using KMnO4-modified activated

carbon derived from steam pyrolysis of rice straw, J Hazard.

Mater 147 (2007) 633–643

[14] S Gao, J Cui, Z Wei, Study on the fluoride adsorption of

various apatite materials in aqueous solution, J Fluorine Chem.

130 (2009) 1035–1041

[15] G.N Glavee, K.J Klabunde, C.M Sorensen, G.C.

Hadjipanayis, Chemistry of borohydride reduction of iron(II)

and iron(III)ions in aqueous and nonaqueous media Formation

of nanoscale Fe, FeB, and Fe2B powders, Inorg Chem 34

(1995) 28–35

[16] V.K Gupta, I Ali, V.K Saini, Defluoridation of wastewaters

using waste carbon slurry, Water Res 41 (2007) 3307–3316

[17] Y.S Ho, G Mckay, Pseudo-second order model for sorption

process, Process Biochem 34 (1999) 451–465

[18] S.A Jabasingh, G Pavithra, Response surface approach for the

biosorption of Cr6+ions by mucor racemosus, CLEAN – soil,

air, Water 38 (2010) 492–499

[19] S Jagtap, M.K.N Yenkie, N Labhsetwar, S Rayalu,

Defluoridation of drinking water using chitosan based

mesoporous alumina, Micropor Mesopor Mater 142 (2011)

454–463

[20] P Kaushik, A Malik, Process optimization for efficient dye

removal by Aspergillus lentulus FJ172995, J Hazard Mater 185

(2011) 837–843

[21] E Kumar, A Bhatnagar, U Kumar, M Sillanpaa,

Defluoridation from aqueous solutions by nano-alumina:

characterization and sorption studies, J Hazard Mater 186

(2011) 1042–1049

[22] S Lagergren, K Svenska, About the theory of so called

adsorption of soluble substances, K Sven Vetenskapsad.

Handl 24 (1898) 1–39

[23] S Laurent, D Forge, M Port, A Roch, C Robic, L Vander

Elst, R.N Muller, Magnetic iron oxide nanoparticles: synthesis,

stabilization, vectorization physicochemical characterizations, and biological applications, Chem Rev 108 (2008) 2064–2110 [24] Y.H Li, S Wang, A Cao, D Zhao, X Zhang, C Xu, Z Luan,

D Ruan, J Liang, D Wu, B Wei, Adsorption of fluoride from water by amorphous alumina supported on carbon nanotubes, Chem Phys Lett 350 (2001) 412–416

[25] Y.H Li, S Wang, X Zhang, J Wei, C Xu, Z Luan, D Wu, Adsorption of fluoride from water by aligned carbon nanotubes, Mater Res Bull 38 (2003) 469–476

[26] T Mathialagan, T Viraraghavan, Biosorption of pentachlorophenol by fungal biomass from aqueous solutions:

a factorial design analysis, Environ Technol 6 (2005) 571–579 [27] W.S.W Ngah, S Fatinathan, Adsorption of Cu(II) ions in aqueous solution using chitosan beads, chitosan–GLA beads and chitosan–alginate beads, Chem Eng J 143 (2008) 62–72 [28] V Ponnusami, V Krithika, R Madhuram, S.N Srivastava, Biosorption of reactive dye using acid-treated rice husk: factorial design analysis, J Hazard Mater 142 (2007) 397–403 [29] K Shailaja, Mary Esther Cynthia Johnson: fluorides in groundwater and its impact on health, J Environ Biol 28 (2007) 331–332

[30] C Sun, J.S.H Lee, M Zhang, Magnetic nanoparticles in MR imaging and drug delivery, Adv Drug Deliver Rev 60 (2008) 1252–1265

[31] A Toyoda, A Taira, IEEE trans, semiconductor, Manufacture

13 (2000) 305–309 [32] S.S Tripathy, J.-L Bersillon, K Gopal, Removal of fluoride from drinking water by adsorption onto alum-impregnated activated alumina, Sep Purif Technol 50 (2006) 310–317 [33] T Tuutijarvi, J Lu, M Sillanp, G Chen, As(V) adsorption on maghemite nanoparticles, J Hazard Mater 166 (2009) 1415–

1420 [34] T Tuutijarvi, J Lu, M Sillanpaa, G Chen, Adsorption mechanism of arsenate on crystal gamma-Fe 2 O 3 nanoparticles,

J Environ Engineer Asce 136 (2010) 897–905 [35] N Viswanathan, S Meenakshi, Enriched fluoride sorption using alumina/chitosan composite, J Hazard Mater 178 (2010) 226–

232 [36] C.B Wang, W Zhang, Synthesizing nanoscale iron particles for rapidandcomplete dechlorination of TCE and PCBs, Environ Sci Technol 31 (1997) 2154–2156

[37] P Wang, I.M.C Lo, Synthesis of magnetic mesoporous a-Fe 2 O 3

and its application to chromate removal from contaminated water, Water Res 43 (2009) 3727–3734

[38] WHO, Guidelines for Drinking Water Quality, World Health Organization, Geneva, 2008

[39] X Xie, X Zhang, B Yu, H Gao, H Zhang, W Fei, Rapidextraction of genomic DNA from saliva for HLA typing

on microarray based on magnetic nanobeads, J Magn Magn Mater 280 (2004) 164–168

[40] J Zolgharnein, A Shahmoradi, M.R Sangi, Optimization of Pb(II) biosorption by Robinia tree leaves using statistical design

of experiments, Talanta 76 (2008) 528–532 [41] A Fakhri, Adsorption characteristics of graphene oxide as a solid adsorbent for aniline removal from aqueous solutions: Kinetics, thermodynamics and mechanism studies, J Saud Chem Soc., 2013, http://dx.doi.org/10.1016/j.jscs.2013.10.002.

[42] A Fakhri, S Adami, Adsorption and thermodynamic study of Cephalosporins antibiotics from aqueous solution onto MgO nanoparticles J Taiwan Inst Chem Eng, 2013, http://dx.doi.org/ 10.1016/j.jtice.2013.09.028.