Synthesis, characterization and adsorption studies of several heavy metal ions on amino-functionalized silica nano hollow sphere and silica gel

Synthesis, characterization and adsorption studies of several heavy metal ions on amino-functionalized silica nano hollow sphere and silica gel

Separation and Purification Technology 85 (2012) 193–205 Contents lists available at SciVerse ScienceDirect Separation and Purification Technology jou...

1MB Sizes 15 Downloads 96 Views

Separation and Purification Technology 85 (2012) 193–205

Contents lists available at SciVerse ScienceDirect

Separation and Purification Technology journal homepage: www.elsevier.com/locate/seppur

Synthesis, characterization and adsorption studies of several heavy metal ions on amino-functionalized silica nano hollow sphere and silica gel M. Najafi a, Y. Yousefi b, A.A. Rafati b,c,⇑ a

Department of Materials Engineering, Hamedan University of Technology, Hamedan 65174, Iran Department of Physical Chemistry, Faculty of Chemistry, Bu-Ali Sina University, P.O. Box 65174, Hamedan, Iran c Phytochemistry Center, Environmental Chemistry Department, Bu-Ali Sina University, Hamedan, Iran b

a r t i c l e

i n f o

Article history: Received 17 August 2011 Received in revised form 1 October 2011 Accepted 9 October 2011 Available online 14 October 2011 Keywords: Heavy metals Nano hollow sphere Adsorption Kinetic model Isotherm model

a b s t r a c t Amino functionalized silica gel (NH2–SG) and amino functionalized silica nano hollow sphere (NH2– SNHS) with rather monodispers shape and size were prepared and characterized by X-ray differaction, scanning electron microscopy (SEM), FT-IR, thermogravimetery, and N2 adsorption–desorption techniques. The synthesized nano particles were employed as a Cd2+, Ni2+, and Pb2+ adsorbent from aqueous solutions at room temperature. Adsorption performances of three different adsorbents prepared by functionalization of commercial silica gel (NH2–SG), silica nano hollow sphere (NH2–SNHS), and a non functionalized silica nano hollow sphere (SNHS) have been compared. Heavy metal adsorption process has been thoroughly studied from both kinetic and equilibrium points of view for all adsorbents. The adsorption isotherms were analyzed using the seven different isotherm models and correlation coefficients were determined for each isotherm. It was found that the Langmuir–Freundlich (Sips) isotherm showed better correlation with the experimental data than other isotherms. The adsorption kinetics was tested for the pseudo-first order, pseudo-second order and Elovich kinetic models at different experimental conditions. The kinetic data show that the process is very fast and the reactions follow pseudosecond-order kinetic models for amino functionalized adsorbents. Also, the maximum adsorption values for Cd2+, Ni2+, and Pb2+ under the experimental conditions were determined for all adsorbents. Ó 2011 Elsevier B.V. All rights reserved.

1. Introduction Toxic heavy metal ions, that are mostly toxic even at very low concentration, in groundwater and wastewater is a rising environmental problem worldwide. Removal of these pollutants from aqueous solution plays an important role in wastewater treatments. Therefore in recent years extensive studies have been undertaken to find more effective and cheaper methods for removal of heavy metal ions from aqueous effluents. A wide range of techniques have been developed for the removal of these metal ions from wastewater such as ion exchange [1–3], reverse osmosis [4,5], adsorption [6,7], precipitation [8], co-precipitation [9], filtration [10], and coagulation [11]. The adsorption technique is very popular and efficient due to simplicity and low cost. Several adsorption materials are capable capturing metal ions from aqueous solutions including zeolites [12], clays [13], activated carbon [14], fly ash [15], peat [16], microbial biomass [17], and agricultural residues [18]. Inherent disadvantages of these materials ⇑ Corresponding author at: Department of Physical Chemistry, Faculty of Chemistry, Bu-Ali Sina University, P.O. Box 65174, Hamedan, Iran. Tel.: +98 811 828 2807; fax: +98 811 825 7407. E-mail addresses: [email protected], [email protected] (A.A. Rafati). 1383-5866/$ - see front matter Ó 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.seppur.2011.10.011

are their low loading capacities, relatively small metal ion binding constants and small selectivity. To overcome these disadvantages, many researchers developed organically functionalized adsorbents such as organoclays [19], polymer nanocomposites [20], functionalized silica gel [21,22] and so on. Over the past two decades, organofunctionalized mesostructured silicas have received extensive attention as promising sorbents and have opened a wide field of applications. These functionalized silicas can effectively be used as adsorbents for the removal of specific toxic metal ions and other hazardous chemicals for environmental cleanup applications. One of the new mesostructured of silica is silica nano hollow sphere (SNHS). The SNHSs with hollow interior has attracted more and more attention because of many extraordinary properties of this structure, such as high specific surface area, narrow pore size distribution, large pore volumes, low density, good thermal and chemical stability, and low toxicity. These kind of materials are widely applied in controlled drug delivery, biomolecular separation, thermal insulators, structural low weight foams, catalysis, fillers, adsorption and removal of heavy metal ions and so on [23–26]. Two conventional methods based on template assisted, are usually applied for the fabrication of SNHS: hard templates such as polymer colloidal particles or carbon spheres [27]; and soft templates such as surfactant micelles and vesicles, gas bubbles

194

M. Najafi et al. / Separation and Purification Technology 85 (2012) 193–205

Table 1 Isotherm models and their linear forms. Isotherm

Linear form

Langmuir

qe ¼

Freundlich

qe ¼ qe ¼

Temkin Sips

qe ¼

Redlich–Peterson (R–P)

qe ¼

qm K L C e 1þK L C e K F C e1=n RT lnðK T C e Þ b

Ce qe

1=n

ln

qe =

Khan

qe ¼ qm ð1þbbK CCe ÞnK

qm C e n ðK To þC e T Þ1=nT K

þ

1 qm

Plot Ce qe

Ce

ln qe ¼ ln K F þ 1n ln C e qe ¼ RT ln K T þ RT ln C e b  b  ln qqm  1 ¼  ln K S  1n ln C e e

qm K S C e 1=n 1þK S C e K RP C e 1þaRP C be

Toth

¼

1 K L qm

ln

h

K RP C e q

 e qe qm



i  1 ¼ ln aRP þ b ln C e

¼ lnðC e Þ  n1T lnðK To þ C ne T Þ



qe vs. ln Ce   ln qqm  1 vs. ln Ce e h  i ln K RPq C e  1 vs. ln C e  e ln qqe v slnðC e Þ m



e

and emulsion droplets [28]. After the shell formation, the templates were removed by calcinations or solvent etching [29]. After synthesis the SNHSs, it is undergo functionalization by anchoring organic molecules to their surface. The present work studies the synthesis and functionalization of various types of silica based mesoporous materials via covalent attachment of organosilanes to improve their characteristics and introduces some alternatives for the removal heavy metals in wastewater from industrial effluents. The fabricated adsorbent materials were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), BET specific surface area, and Fourier transform infrared spectroscopy (FT-IR) analysis. Experimental data obtained from batch equilibrium tests have been analyzed different sorption isotherm models, namely Langmuir isotherm, Freundlich isotherm, Temkin isotherm, Dubinin– Radushkevich (D–R) isotherm, Sips isotherm, Redlich–Peterson isotherm, Toth isotherm, and Khan isotherm. Also kinetic investigations were carried out using three kinetic models, namely pseudo-first order model, pseudo-second order model and Elovich model. On the other hand, the effect of various parameters such as initial concentration of adsorbates and contact time on the adsorption process were studied and interpreted. 2. Materials and methods 2.1. Materials All chemicals were purchased from Merck and employed without further purification. Hexadecyltrimethylammonium bromide

(CTAB), was used as structure directing agent. Tetraethoxysilane (TEOS) and 3-aminopropyltriethoxy-silane (APTES) were used as silica and propylamine precursors. Sources of metals for sorption experiments were [Cd(NO3)24H2O], [Ni(NO3)26H2O], and Pb(NO3)2 of synthesis grade that were supplied from Merck. All heavy metals solutions (Ni2+, Pb2+, and Cd2+) were prepared in stock solutions up to 1000 ppm (1 g dm3) of metal from the corresponding nitrate salts. No further pH adjustment of these solutions was made as their natural acidity due to hydrolysis of metals (i.e. to form MOH+ and H+) prevented the precipitation of the corresponding metal hydroxides. All solutions used in this study were diluted with double distilled water as required. Standard solutions (1.0 g dm3) of Ni2+, Cd2+, and Pb2+ were used for atomic absorption spectrometry experiments. Working standards were prepared from the dilution of stock solutions every day. All aqueous solutions were prepared by double distilled water at room temperature. 2.2. Preparation of hollow silica spheres Silica nano hollow sphere was prepared using sol–gel method according to Gao et al. [30]. In a typical synthesis, 0.1025 g of CTAB was added into 125 ml mixed solution of NH3 (2 ml) and double distilled water (123 ml) in a beaker with constant magnetic stirring. Then, TEOS (1 g) was added dropwise into the above homogeneous mixture giving white slurry and the reaction was kept at 30 °C for 1 h. After reaction was completed, the collected product was centrifuged, repeatedly washed with distilled water and ethanol (30% v/v) to remove surfactants and other impurities. The final

(1)

Micelle

vs. Ce

ln qe vs. ln Ce

Condensation of Silica

Formation of SNHS

(2)

Functionalization

Functionalized SNHS

Scheme 1. The general procedure to obtain the NH2–SNHS.

M. Najafi et al. / Separation and Purification Technology 85 (2012) 193–205

195

Fig. 2. SEM image of synthesized SNHS with high magnification.

Fig. 1. FT-IR spectrum of (a) SNHSs, (b) NH2–NSHS, and (c) NH2–SG.

Fig. 3. TEM image of synthesized SNHS with high magnifications. Table 2 Specific surface area of synthesized adsorbents. Adsorbent

SBET (m2/g)

SNHS NH2–SNHS NH2–SG

919 370 479

sample was dried at 80 °C for 8 h in oven for further characterization. After drying, the organic surfactant was removed by calcination at 550 °C for 3 h. The sonication was performed under ambient air conditions during the whole process.

2.3. Synthesis of amino-functionalized silica nano hallow sphere Amino-functionalized silica nano hollow sphere (NH2–SNHS) was prepared according to the method of Blitz et al. [31]. Calcined SNHS (0.5 g) were refluxed in 25 ml of toluene containing 2.5 mmol of 3-aminopropyltriethoxysilane (APTS) for 2 h. The solid products were filtered off and washed with toluene and ethanol respectively and dried in air oven at 150 °C for 2 h. Any residual organosilane was removed by Soxhlet extraction over ethanol for 24 h. The NH2–SNHS were resuspended in distilled water for 30 min, and then once again dried in vacuum at 150 °C to facilitate cross-linking.

196

M. Najafi et al. / Separation and Purification Technology 85 (2012) 193–205

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. Amount of organic groups grafted on surface silica measured by thermogravimetric analysis (TGA). TGA experiments were carried out between 30 and 900 °C at a heating rate of 10 °C/min using a Perkin–Elmer Pyris Diamond TG analyzer. The metal ion concentration of the solutions was determined by using an atomic absorption spectrometer (SpectrAA-220 Varian). 2.5. Heavy metal adsorption experiments Batch mode adsorption isotherm and kinetic studies were carried out at 25 °C. An amount of 0.015 g adsorbent (NH2–SG, SNHS or NH2–SNHS) was introduced into conical flasks with 5 ml of metal ion solution with different concentrations. The flasks were placed in a thermostatic shaker and agitated for 24 h at a fixed agitation speed of 160 rpm. Samples were taken periodically for measurement of aqueous phase of each metal ion concentrations. All the experiments were carried out at initial pH 4.5. Since, above pH 7 precipitations may occur [32], initial pH was adjusted by adding diluted HNO3. The equilibrium adsorption capacity of adsorbent was calculated by the following equation:

qe ¼

ðC 0  C e Þ V W

ð1Þ

where qe is the equilibrium adsorption capacity of adsorbent (mg of metal/g adsorbent), C0 is the initial concentration of the metal ions in mg/l, Ce is the equilibrium concentration of metal ions in mg/l at the time of equilibrium, V is the volume of metal ions solution in l, and W is the weight of the adsorbent in g. 2.5.1. Equilibrium adsorption experiments The equilibrium data were analyzed in accordance with the Langmuir, Frundlich, Temkin, Dubinin–Radushkevich (D–R), Redlich–Peterson (R–P), Sips, Toth, and Khan sorption isotherm models (see supporting information for more details). Since Sips, R–P, and D–R isotherm equations include three adjustable parameters and cannot be fitted to the experimental data by linear regression, thus nonlinear regression analysis was applied to evaluate the adsorption parameters for all isotherms. All of the models are listed in Table 1 and a detail was given in supporting material section.

Fig. 4. TGA curves of (a) SNHS, (b) amino functionalized SNHS with 2.5 mmol of APTS, and (c) amino functionalized SNHS with 5 mmol of APTS.

2.4. Characterization The FT-IR spectra were recorded by a Perkin–Elmer Spectrum GX FT-IR spectrometer. The spectrum was recorded from 550 to 4000 cm1 using KBr pellets. The crystallinity of the silica materials was characterized by X-ray diffraction (XRD; ITAL structures model APD2000) with applying Cu Ka radiation wavelength 0.15405 nm. A step size of 0.01 and a time per step of 0.2 s were used. Diffraction patterns were taken over the 2h range 0–60°. Average crystallite size of prepared particles was calculated by the Scherer’s equation. The sizes and morphologies of the synthesized silica nanoparticles were examined by a Philips SEM XL30 microscope operating at 30 kV. BET surface area measurements were conducted using a surface area analyzer (Nova 2000, Quantachrome Instruments, FL, USA)

2.5.2. Adsorption kinetics 2.5.2.1. Kinetic adsorption experiments. A kinetic study was carried out to examine the rate-controlling mechanism of the adsorption of some metal ions by different synthesized adsorbents. Kinetic experiments were conducted by a series of lead nitrate, cadmium nitrate and nickel nitrate solutions with the same initial concentrations of 100 mg/l which have been stirred in the presence of 15 mg adsorbents (SNHS, NH2–SNHS and NH2–SG) at 25 °C and for different selected times ranging from 5 to 180 min. The solutions were filtered to remove solids and analyzed by atomic absorption spectrophotometer. The adsorption capacities of adsorbents were calculated from the difference between the initial and the final concentration at any intermediate time, t. 2.5.2.2. Kinetic models. The kinetic parameters are useful in predicting the adsorption rate which can use as important information in designing and modeling of the adsorption process. On the other hand, it can be used for controls the residual time of the whole adsorption process. The sorption dynamics of the adsorption by functionalized and thiol-SNHS were tested with the Lagergren pseudo-first order [33] and the chemisorptions pseudo-second order [34] kinetic models.

M. Najafi et al. / Separation and Purification Technology 85 (2012) 193–205

197

Fig. 5. Equilibrium adsorption of (e) Ni2+, (d) Cd2+, and (D)Pb2+ on (a) SNHS, (b) NH2–SG, and (c) NH2–NSHS adsorbents at 25.0 °C.

A pseudo first-order equation (Lagergren) can be expressed in a nonlinear form as:

dqt ¼ k1 ðqe  qt Þ dt

ð2Þ

where qe and qt are the amounts of metal ions adsorbed on the adsorbent (mg g1) at equilibrium and at time t, respectively, and k1 is the rate constant of the first-order adsorption in min1. Equation integration and rearrangement yield the linear form:

lnðqe  qt Þ ¼ ln qe  k1 t

ð3Þ

The applicability of the first order kinetic model is suggested by the straight line plots of ln(qe  qt) versus t and from the slope and intercept of the plot, qe and k1 can be determined, respectively. Pseudo-second-order equation may be written in the form:

dqt ¼ k2 ðqe  qt Þ2 dt

2.5.3. Non-linear regression analysis In this study all the model parameters were evaluated by nonlinear regression. The optimization procedure required an error function to evaluate the fit of the equation to the experimental data. Not only the determination coefficient (R2) but also six additional error functions were used to measure the goodnessof-fit. The smaller the error function value, the better the curve fitting. The non-linear error functions employed in this study are as follows (in all error function equations, Qmeas is measured ion concentration and Qcalc is calculated ion concentration with models):

ð4Þ 1. The coefficient of determination (R2)

where k2 is the rate constant of second-order adsorption in (g mg1 min1). A linearized form of the pseudo-second order model can be described by integration of above differential equation [35]:

t 1 1 ¼ þ t qt k2 q2e qe

commonly used to check the validity of these models and to obtain the model parameters when the corresponding linear plot is adequate.

ð5Þ

The pseudo-second-order rate constants (k2) and qe were determined experimentally from the slope and intercept of the plot obtained by plotting t/q vs t. Linear arrangements, Eqs. (3) and (5), are

R2 ¼ Pn

i¼1 ðQ meas

ðQ meas  Q calc Þ2  Q calc Þ2 þ ðQ meas  Q calc Þ2

ð6Þ

where Q calc is the average of Qcalc. 2. Nonlinear chi-square test (v2)

v2 ¼

n X ðqe;calc  qe;meas Þ2 qe;meas i¼1

ð7Þ

198

M. Najafi et al. / Separation and Purification Technology 85 (2012) 193–205

100 90 80

qe (ppm)

70 60 50 40 30 20 10 0 0

50

100

150

200

250

Ce (ppm) 60 50

qe (mg/g)

40 30 20 10 0 0

20

40

60

80

100

120

140

160

Ce (ppm) 30 25

qe (mg/g)

20 15 10 5 0 0

20

40

60

80

100

120

140

Ce (ppm) Fig. 6. Typical fitting data with two parameters isotherm models () experimental, (  ) Langmuir , (- - -) Freundlich and (-  -  -) Temkin model for adsorption of Pb2+ on (a) NH2–SNHS, (b) NH2–SG, and (c) SNHS.

3. Residual root mean square error (RMSE)

vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u n u 1 X RMSE ¼ t ðQ  Q calc Þ2 n  2 i¼1 meas

5. Standard deviation of relative error

ð8Þ

where n is the number of observations in the experimental data. 4. Average relative error

ARE ¼

 n   100 X qe;meas  qe;calc   n i¼1  qe;meas

ð9Þ

SRE

sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Pn 2 i¼1 ½ðqe;meas  qe;calc Þ  ARE ¼ n1

ð10Þ

6. Marquardt’s percent standard deviation

vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi !2 u n u 1 X qe;meas  qe;calc t MPSD ¼ 100 n  p i¼1 qe;meas

ð11Þ

199

M. Najafi et al. / Separation and Purification Technology 85 (2012) 193–205 Table 3 Isotherm error deviation data related to the adsorption of Ni2+, Cd2+, and Pb2+ onto different adsorbents at 25.0 °C. Adsorbent

Metal

Error function model

SNHS

Ni+2

R2

v2

Cd+2

RMSE ERRSQ ARE SRE MPSD R2

v2

Pb+2

RMSE ERRSQ ARE SRE MPSD R2

v2 RMSE ERRSQ ARE SRE MPSD NH2–SG

Ni+2

R2

v2

Cd+2

RMSE ERRSQ ARE SRE MPSD R2

v2

Pb+2

RMSE ERRSQ ARE SRE MPSD R2

v2 RMSE ERRSQ ARE SRE MPSD NH2–SNHS

Ni+2

R2

v2

Cd+2

RMSE ERRSQ ARE SRE MPSD R2

v2

Pb+2

RMSE ERRSQ ARE SRE MPSD R2

v2 RMSE ERRSQ ARE SRE MPSD

Isotherm models Langmuir

Freundlich

Khan

Redilch–Peterson

0.9962 0.0484 0.1711 0.2343 2.7373 2.8772 3.9634 0.9982 0.0912 0.3060 0.8428 2.1921 2.2898 3.5473 0.9964 0.6496 0.6545 3.4273 6.1009 6.3242 15.094

0.9784 0.4244 0.4060 1.3198 7.8364 8.2880 15.1983 0.9727 2.4600 1.1851 12.6396 13.6017 14.3988 28.9434 0.9694 3.4217 1.7385 24.1804 15.0026 16.0272 33.0542

0.9981 0.0221 0.1181 0.1116 1.8495 1.9468 4.0775 0.9990 0.0753 0.2208 0.4389 2.1975 2.3232 4.6266 0.9984 0.0868 0.3882 1.2059 2.2222 2.3509 4.6515

0.9982 0.0193 0.1150 0.1058 1.6890 1.6938 2.5523 0.9991 0.0629 0.2061 0.3821 2.0543 2.1722 4.1153 0.9979 0.1632 0.4449 1.5839 3.0847 3.2432 7.3000

0.9982 0.0172 0.1180 0.1111 1.4142 1.4950 2.0633 0.9992 0.0497 0.2001 0.3602 1.8814 1.9884 3.3127 0.9971 0.3830 0.5564 2.4763 4.5116 4.7058 12.234

0.9982 0.0175 0.1170 0.1086 1.5068 1.5927 2.1863 0.9992 0.0537 0.2006 0.3624 1.9441 2.055 3.5932 0.9973 0.3182 0.5291 2.2397 4.1524 4.3382 10.9972

0.9952 0.0235 0.1401 0.1571 1.5259 1.6138 2.3337 0.9969 0.1604 0.3240 0.9451 3.4373 3.6182 6.7060 0.9856 0.8092 0.9377 6.9895 7.3311 7.7778 14.0617

0.9972 0.2613 0.4668 2.1789 3.5332 3.6563 5.9992 0.9975 0.9622 0.6692 4.4779 6.6038 6.8056 16.1016 0.9957 3.3983 1.5034 27.1209 11.5288 11.5781 22.998

0.9748 3.1932 1.3829 19.1232 11.7778 12.4903 31.1789 0.9705 4.3567 1.9962 39.8496 15.8001 16.7896 29.9088 0.9759 8.5519 2.9918 107.4072 18.5519 19.8169 36.4546

0.9983 0.1620 0.3522 1.2403 2.0784 2.1998 6.0627 0.9991 0.1926 0.3438 1.1826 3.1346 3.2559 7.3399 0.9988 0.3464 0.6595 5.2191 3.4605 3.5903 6.9105

0.9982 0.1451 0.3593 1.2907 2.9621 3.1123 5.2204 0.9987 0.3344 0.4223 1.7831 4.1002 4.2467 9.9812 0.9982 0.7097 0.8230 8.1281 5.2212 5.3754 11.1919

0.9978 0.1564 0.4009 1.607 2.9404 3.0802 4.6184 0.9982 0.5967 0.5301 2.8095 5.4265 5.5883 13.5529 0.9969 1.6772 1.1227 15.1245 7.9750 8.1204 17.5027

0.9979 0.1489 0.3855 1.4859 2.9469 3.0907 4.7242 0.9983 0.5139 0.4991 2.4914 6.2514 6.4586 12.5548 0.9973 1.3178 1.0284 12.6922 7.1457 7.2982 15.5406

0.9928 0.5520 0.6195 3.8382 5.6677 5.9491 12.0096 0.9814 3.2628 1.3385 17.9149 12.8556 13.4877 28.7765 0.9634 3.8762 2.4986 74.9169 9.9583 11.1565 14.8465

0.9951 0.7382 0.7423 6.0609 6.4599 6.6129 11.1518 0.9929 2.5029 1.3351 19.6062 11.2018 11.3817 21.2823 0.9899 14.9439 3.7356 237.23 17.1803 141.1394 330.2671

0.9865 2.2572 1.1603 14.8105 11.0746 11.6976 24.9089 0.9789 3.7617 2.0384 45.7059 13.3902 14.2763 25.4813 0.9879 12.6042 3.4503 202.3741 16.2817 17.5126 38.7901

0.9984 0.1472 0.3905 1.6773 2.8460 3.0946 5.5680 0.9965 0.3812 0.8108 7.2310 3.8648 4.0564 6.4232 0.9968 1.4146 1.7177 50.1584 0.2257 1.6787 8.3284

0.9983 0.1228 0.4026 1.7828 2.3807 2.5048 4.2540 0.9958 0.5801 0.9021 8.9517 4.9441 5.1542 9.5301 0.9961 1.4898 1.9069 61.8228 4.0743 4.5019 6.6819

0.9976 0.1541 0.4704 2.4338 2.1907 2.30618 4.0291 0.9939 1.1264 1.1036 13.3987 7.2161 7.4520 14.6801 0.9937 2.5275 2.3906 97.1587 6.3606 6.7984 10.5719

0.9979 0.1333 0.4407 2.1371 2.2283 2.3455 3.8214 0.9945 0.9164 1.0361 11.8079 6.4397 6.6664 12.9693 0.9947 2.0866 2.2143 83.3570 5.5094 21.3383 8.8886

0.9812 2.4339 1.1657 14.9476 11.8243 12.3575 25.3604 0.9641 3.1078 1.9070 40.0052 11.6920 12.6920 20.1734 0.9377 22.1723 6.2612 666.4581 21.49063 23.445 33.4897

where p is the number of parameters of the model. 7. The sum of the squares of the errors (ERRSQ)

Sips

Toth

Temkin

3. Results and discussions 3.1. Characterization

ERRSQ ¼

n X

ðqe;cal  qe;isotherm Þ2i

i¼1

ð12Þ

Scheme 1 shows the overall procedure used to synthesize the amine functionalized-SNHS. The FT-IR spectra of the SNHS (a),

200

M. Najafi et al. / Separation and Purification Technology 85 (2012) 193–205

Table 4 Isotherm parameters for various two parameters adsorption isotherms for the adsorption of Ni2+, Cd2+, and Pb2+ onto different adsorbents at 25.0 °C. Adsorbent

SNHS

Isotherm models

Langmuir

Freundlich

Temkin

NH2–SG

Langmuir

Freundlich

Temkin

NH2–SNHS

Langmuir

Freundlich

Temkin

Parameters

Metals Ni+2

Cd+2

Pb+2

qm (mg/g) KL r2 KF 1/n r2 B (j/mol) K Te r2

8.375 0.059 0.9962 1.625 0.321 0.9785 1481.284 0.717 0.9952

20.815 0.059 0.9982 3.434 0.359 0.9727 596.7375 0.728 0.9969

26.858 0.104 0.9964 6.596 0.296 0.9694 540.4048 2.261 0.9856

qm (mg/g) KL r2 KF 1/n r2 B (j/mol) K Te r2

25.924 0.0440 0.9972 3.538 0.386 0.9748 483.1795 0.587 0.9928

31.894 0.086 0.9975 6.542 0.328 0.9704 445.7810 1.703 0.9814

54.351 0.069 0.9957 9.622 0.354 0.9759 281.4983 1.8917 0.9634

qm (mg/g) KL r2 KF 1/n r2 B (j/mol) K Te r2

31.291 0.029 0.9951 3.203 0.425 0.9865 418.7070 0.473 0.9812

40.727 0.053 0.9928 6.298 0.371 0.9789 360.0016 1.267 0.9641

96.786 0.032 0.9899 11.69 0.393 0.9879 175.7273 1.395 0.9377

APTES modified SNHS (b) and APTES modified SG, (c) are shown in Fig. 1. The broad IR absorption band covering from about 3500 to 3055 cm1 can be assigned to hydrogen bonded and partially hydrated silanols (Si–OH residue) [36]. Also, Fig. 1(a) displayed the characteristic features of Si–O–Si unit [37]: asymmetric stretching at 1101 cm1 and symmetric stretching at 819 cm1. Amine-functionalized silica nanospheres also show visible broad absorption bands at 1600 cm1 corresponding to the bending vibration of N–H group, while N–H stretching (3200–3500 cm1) and C–N stretching (1030–1230 cm1 overlapped with the broad absorption band of the silanol group and the Si–O–Si vibrations (Fig. 1b). These findings indicated that NH2 groups were introduced to the SiO2 surface. As evidenced by FT-IR, the surface chemical properties of NH2–SG (Fig. 1c) were much more like NH2–SNHS (Fig. 1b). These results revealed the success in synthesizing the NH2–SiO2 nanocomposites. Therefore, the synthesis of a weak base anion exchanger with a primary amine group is responsible for the chelating of Ni+2, Cd+2, and Pb+2 and the adsorption was assumed to be established by the complex formation reaction between Ni+2, Cd+2, and Pb+2 and the nitrogen atom in the functional groups [38]. The surface areas of samples were determined by the BET method and were listed in Table 2. It was found that the surface area of amino functionalized SNHS (370 m2/g) is lower than non-functionalized SNHS (919 m2/g). It is due to the introducing of organic functional groups into the pores which may reduce the pore size and increased the density of material. Figs. 2 and 3 show the scanning electron microscopy (SEM) and the transmission electron microscopy (TEM) of the as synthesized SNHS before and after functionalization. As shown in Figs. 2 and 3, the SEM and TEM images of the synthesized adsorbents show a spherical morphology and a narrow particle size distribution with a normal polydispersity. According to the high magnification SEM image, the size distribution of spherical particle of nano silica is mainly in the range less than 150 nm. The conceivable reason for the size distribution of the spheres is the instability and imbalance of vesicles and disequilibrium of ultrasound treatment.

Thermogravimetric analyses of the extracted NH2–SNHS organosilicas were performed to test the thermal stability of the samples (Fig. 4). The amount of organic groups grafted on SNHS was measured by thermogravimetric analysis (TGA) which has been carried out between 30 °C and 900 °C at a heating rate of 10 °C/min using a Perkin–Elmer Pyris Diamond TG analyzer. The weight loss for two NH2–SNHS samples were about 2% at temperature below 150 °C is due to a loss of residual water. For the two functionalized samples of SNHS with different amounts of APTS i.e. 2.5 mmol (Fig. 4b) and 5 mmol (Fig. 4c), loss in samples weight are correspond to 1.54% and 13.53% functionalization of the surface, respectively. 3.2. Adsorption isotherms The adsorption behavior of heavy metal ions onto the three different adsorbents (SNHS, NH2–SG, and NH2–SNHS) at different initial heavy metal ions concentration was investigated. Fig. 5 shows the equilibrium adsorption uptake of the adsorbents at different initial heavy metal ions concentration. All the three metals’ adsorption onto adsorbents was found to be concentration dependent. As can be observed, increasing initial heavy metal ions concentration increases significantly the equilibrium adsorption uptake of the adsorbents. It can be due to the fact that adsorption onto the adsorbents is a diffusion based process. At higher initial concentration, the mass transfer driving force is larger, and hence, this results in more adsorption of heavy metal ions [39]. It is shown in Fig. 5 that the adsorption capacities of Pb2+, Cd2+, and Ni2+ tend to a constant value. It means that the whole active sites in adsorbents were fully attached by Pb2+, Cd2+, and Ni2+. The equilibrium adsorption uptake (adsorption capacity) is an important factor because it determines how much adsorbent is required quantitatively for enrichment of an analyte from a given solution. As can be observed in Fig. 5, the adsorption capacity decreases in the order Pb2+ > Cd2+ > Ni2+ for all of the adsorbents.

201

M. Najafi et al. / Separation and Purification Technology 85 (2012) 193–205 Table 5 Isotherm parameters for various three parameters adsorption isotherms for the adsorption of Ni2+, Cd2+, and Pb2+ onto different adsorbents at 25.0 °C. Adsorbent

Isotherm models

Parameters

Metals Ni+2

SNHS

Sips

Redilch–Peterson

qm(mg/g) 1/n Ks r2 KR

aR Toth

Khan

b r2 qm(mg/g) K T0 n r2 qm(mg/g) bK

aK r2 NH2–SG

Sips

Redilch–Peterson

qm(mg/g) 1/n Ks r2 KR

aR Toth

Khan

b r2 qm(mg/g) K T0 n r2 qm(mg/g) bK

aK r2 NH2–SNHS

Sips

Redilch–Peterson

qm(mg/g) 1/n Ks r2 KR

aR Toth

Khan

b r2 qm(mg/g) K T0 n r2 qm(mg/g) bK

aK r2

In order to describe the uptake of ions by adsorbents, the isotherms data were analyzed using seven models (all of the models are listed in Table 1). The two and three parameter models, namely Langmuir, Freundlich, Sips, R–P, Khan, Temkin, and Toth equations have been applied to evaluate the fit by isotherm for the adsorption of Pb2+, Ni2+, and Cd2+ (Fig. 6 and Fig. S1 in Supporting material were plotted for Pb2+, typically). In order to verify the model for the adsorption system, it is necessary to analyze the data using error analysis. The seven error functions employed in this study are included: the coefficient of determination (R2), nonlinear chi-square test (v2), residual root mean square error (RMSE), average relative error (ARE), standard deviation of relative error (SRE), Marquardt’s percent standard deviation (MPSD), and the sum of the squares of the errors (ERRSQ). The smaller the error function value, the better the curve fitting. The values of different errors from nonlinear method are listed in

Cd+2

Pb+2

9.215 0.823 0.046 0.9981 0.628 0.118 0.909 0.9982 9.579 6.145 0.713 0.9982 5.979 0.0986 0.885 0.9982

22.097 0.891 0.050 0.9990 1.436 0.0982 0.928 0.9992 22.806 8.479 0.797 0.9991 15.899 0.0869 0.9018 0.9992

29.353 0.797 0.084 0.9984 3.663 0.196 0.923 0.9973 30.465 3.462 0.681 0.9979 20.420 0.1657 0.9112 0.9971

28.098 0.872 0.035 0.9983 1.366 0.079 0.919 0.9979 29.219 9.607 0.766 0.9982 19.571 0.0663 0.894 0.9978

34.860 0.819 0.068 0.9991 3.459 0.159 0.919 0.9989 36.159 4.498 0.707 0.9987 23.972 0.1347 0.9047 0.9982

63.817 0.753 0.044 0.9988 5.587 0.1968 0.8665 0.9973 70.21 3.490 0.5773 0.9982 33.229 0.1484 0.8441 0.9969

38.982 0.767 0.017 0.9984 1.433 0.123 0.813 0.9979 45.739 5.923 0.555 0.9983 15.013 0.0848 0.7596 0.9977

49.526 0.737 0.031 0.9960 3.477 0.184 0.841 0.9945 56.119 3.679 0.543 0.9957 22.153 0.1378 0.8105 0.9939

143.295 0.635 0.011 0.9968 9.510 0.431 0.725 0.9947 227.404 2.206 0.337 0.9961 24.950 0.3089 0.6845 0.9939

Table 3. The best model for each ion and adsorbents was indicated in table. After the equilibrium adsorption data were fitted with different isotherm models with nonlinear or linear regression, the fitting parameter values are summarized in Tables 4 and 5, and the graphical representations of these models are presented in Figs. 6 and S1, typically for Pb2+. The higher correlation factors and lower error functions of Sips model for all elements and all adsorbents indicates that the Sips model gives a better fit to the experimental data and so the nature of adsorption of three metal ions on the adsorbents is more compatible with Sips assumptions. The isotherms represent the sorption behavior of metals on three different adsorbents, i.e. SNHS, NH2–SG, and NH2–SNHS as a function of increasing aqueous metal ion concentration after equilibrium. All adsorbents show effective in sorbing all the three

202

M. Najafi et al. / Separation and Purification Technology 85 (2012) 193–205

Table 6 Comparison of the heavy metal ion adsorption by some functionalized adsorbents from the literature with three different adsorbents synthesized in this work. Surface area (m2/g)

Adsorbent Mesopore

Function

SBA-15 MCM-41 SBA-15 MDA–SBA-15 EDSG DTSG

–RNH2 –CH2–(CH2)2–NH2 3-Aminopropytriethoxysilane Melamine-based NH2 dendrimer EDTA Diethylenetriaminepentaacetic acid (DTPA)

NH2–MCM–41

–RNH2

S S–S N–S NN–S NNN–S

Non H3C–(CH2)3–SH H3C–(CH2)3–NH2 H3C–(CH2)3–NH–(CH2)2–NH2 H3C–(CH2)3–NH–(CH2)2–NH–(CH2)2–NH2

687–712 875–888 62–65 120–220 245–314

NH2–MCM–41

–NH2

1387

SiCl–PAAH

4-Phenylacetophynone 4-aminobenzoylhydrazone (PAAH)

480–540

SNHS NH2–SG NH2–SNHS

Non 3-Aminopropyltriethoxy-silane (APTES) 3-Aminopropyltriethoxy-silane (APTES)

919 479 370

775 1387 486 293 386 367

Adsorption capacity (mg/g)

Ref.

Pb(II)

Cd(II)

Ni(II)

1.10 – – – – –

1.10 57.70 23.70 94.80 – –

– 18.20 14.10 71.10 19.62 16.97

[40] [38] [41] [41] [42] [42]



79.8

40.50

[43]

– – – – –

5.90 11.74 – 0.59 –

0.88 0.29 0.06 8.80 8.80

[44] [44] [44] [44] [44]

18.25

12.36

[38]

5.51

[45]

57.74 – 26.86 54.35 96.79

– 20.82 31.89 40.73

8.38 25.92 31.29

This work This work This work

Fig. 7. Kinetic adsorption of (e) Ni2+, (d) Cd2+ and (D) Pb2+ on (a) SNHS (b) NH2–SG, and (c) NH2–SNHS adsorbents at 25 °C.

metal ions. The trend of metals sorption on adsorbents was NH2– SNHS > NH2–SG > SNHS. On the other hand, the trend of metal sorption on whole three adsorbents was Pb2+ > Cd2+ > Ni2+.

The adsorption results were compared with those of mesoporous based adsorbents, reported by other authors (Table 6); this revealed that the adsorption efficiency of the adsorbent amine

203

M. Najafi et al. / Separation and Purification Technology 85 (2012) 193–205

18

(a)

16

qt (mg/g)

14 12 10 8 6 4 2 0

0

20

40

60

80

100

120

140

160

180

200

t (min) 20

(b)

18 16

qt (mg/g)

14 12 10 8 6 4 2 0 0

50

100

150

200

t (min) 12

(c)

10

qt (mg/g)

8 6 4 2 0 0

20

40

60

80

100

120

140

160

180

200

t (min) Fig. 8. Typical fitting data with the pseudo-first-order (  ), pseudo-second-order (- - -), and Elovich (-  -  -) kinetic model and experimental data () for adsorption of Pb2+ ion on (a) NH2–SG, (b) NH2–SNHS, and (c) SNHS adsorbents at 25 °C.

functionalized SNHS prepared in our work was generally higher than the previously reported values. 3.3. Adsorption kinetics Several adsorption kinetic models have been established to understand the adsorption kinetics and rate-limiting step. The pseudo-first and pseudo-second order rate models are the most well liked model to study the adsorption kinetics of heavy metals and quantify the extent of uptake in adsorption kinetics. In the present work, adsorption rate has been analyzed by using two common semi-empirical kinetic models which are based on adsorption equilibrium capacity: the pseudo-first-order and pseudo-second-order equations, proposed by Lagergren [33] and Ho and McKay [34], respectively.

Fig. 7 represents the variation of Pb2+, Ni2+, and Cd2+ adsorption on NH2–SNHS, NH2–SG, and SNHS with shaking time (0–180 min) at initial Pb2+, Ni2+, and Cd2+ solution concentrations. This figure indicates that while the adsorption of ions is quite rapid initially, the rate of adsorption becomes slower with the passage of time and reaches a constant value (around 100 min for Pb2+, Ni2+, and Cd2+) (equilibrium time). The initial faster rate may be due to the availability of the uncovered surface area of the adsorbents, since the adsorption kinetics depends on the surface area of the adsorbent. The kinetic adsorption data can be processed to understand the dynamics of the adsorption reaction in terms of the order of the rate constant. Fig. 8 show a typically comparison between experimental points and fitted points for Pb2+. Among three different kinetic models, pseudo-first order kinetic model had very high value of

204

M. Najafi et al. / Separation and Purification Technology 85 (2012) 193–205

Table 7 The values of seven different error analysis of adsorption kinetic models for adsorption of Ni2+, Cd2+, and Pb2+ onto different adsorbents at 25.0 °C. Adsorbent

SNHS

Metal

Ni

+2

Error function model 2

R

v2

Cd+2

RMSE ERRSQ ARE SRE MPSD R2

v2

Pb+2

RMSE ERRSQ ARE SRE MPSD R2

v2 RMSE ERRSQ ARE SRE MPSD NH2–SG

Ni+2

R2

v2

Cd+2

RMSE ERRSQ ARE SRE MPSD R2

v2

Pb

+2

RMSE ERRSQ ARE SRE MPSD R2

v2 RMSE ERRSQ ARE SRE MPSD NH2– SNHS

Pseudosecond-order

Elovich

0.9907 0.8860 0.1304 0.1700 44.4851 46.5044 104.1409 0.9966 0.1486 0.2331 0.4892 6.1685 6.5224 9.2382 0.9981 0.1356 0.1781 0.3171 5.5835 5.8679 10.4649

0.9859 1.0318 0.1521 0.2314 48.3302 50.5208 111.2735 0.9906 0.3536 0.3750 1.2656 9.6751 10.2154 14.4469 0.9955 0.3553 0.2839 0.8058 8.8807 9.3402 16.5425

0.9796 1.1669 0.1749 0.3062 51.5663 53.8979 117.5675 0.9816 0.6241 0.5110 2.3503 12.7355 13.4270 19.7057 0.9872 0.7221 0.4525 2.0473 12.8729 13.5158 22.7308

0.9911 0.4773 0.2798 0.7048 11.7130 12.2987 23.9396 0.9885 0.5783 0.4118 1.6907 7.4092 7.7438 13.912 0.9701 1.0482 0.8653 8.9845 7.0925 7.3118 11.5783

0.9935 0.3501 0.2485 0.5558 13.2828 13.9699 30.8733 0.9929 0.3929 0.3342 1.1166 7.9842 8.3874 20.4959 0.9936 0.2375 0.3847 1.7761 3.4843 3.6166 5.6708

0.9916 0.7254 0.2854 0.7329 16.497 17.3499 38.57 0.9788 1.3223 0.5667 3.2119 12.8931 13.5218 29.6680 0.9752 0.8058 0.5748 6.8369 12.1971 12.6882 9.9966 0.9972

0.9979

0.9995

v2

Cd+2

RMSE ERRSQ ARE SRE MPSD R2

0.1628 0.2296 0.5270 5.7249 5.9259 11.1177 0.9859 2.5655 0.9753 10.4633 14.8046 14.7655 25.1898 0.9886 0.6224 0.6185 4.5909 4.6982 4.8269 2.5549

0.0524 0.1042 0.1086 3.4615 3.6130 7.1339 0.9974 0.07929 0.2576 0.7299 2.5149 2.6212 3.3819 0.9958 0.1848 0.3498 1.4685 2.7707 2.8923 1.2811

Pb+2

v2 RMSE ERRSQ ARE SRE MPSD

Kinetics models

Parameters

Metals Ni+2

Pseudo-firstorder

R2

RMSE ERRSQ ARE SRE MPSD R2

Adsorbent

Kinetic models

Ni+2

v2

Table 8 The values of parameters obtained by different kinetic models.

0.1639 0.2469 0.6094 3.7336 3.9341 9.4140 0.9941 0.3884 0.4176 1.9183 5.9139 6.0906 9.7013 0.9581 1.4485 1.1107 14.8031 8.5158 8.9152 3.3140

SNHS

Pseudo-firstorder Pseudo-secondorder Elovich

NH2–SG

Pseudo-firstorder Pseudo-secondorder Elovich

NH2– SNHS

Pseudo-firstorder Pseudo-secondorder Elovich

Cd+2

Pb+2

k1 q e1 r2 k2 q e2 r2 b (g/mg) a (mg/ (g min)) r2

0.0132 3.205 0.9907 0.002 4.705 0.9856 0.5985 0.2868

0.0180 9.797 0.9977 0.0011 13.297 0.9906 0.2413 0.5619

0.0207 10.378 0.9981 0.0013 13.729 0.9955 0.2427 0.7169

0.9759

0.9816

0.9872

k1 q e1 r2 k2 q e2 r2 b (g/mg) a (mg/ (g min)) r2

0.0169 8.108 0.9911 0.0013 10.980 0.9935 0.2921 0.5374

0.038 9.988 0.9885 0.0033 12.006 0.9929 0.3413 0.2434

0.110 14.039 0.9700 0.0099 15.362 0.9936 0.3985 0.3359

0.9916

0.9788

0.9752

k1 q e1 r2 k2 q e2 r2 b(g/mg) a (mg/ (g min)) r2

0.0203 12.058 0.9979 0.0011 15.702 0.9995 0.2206 0.8103

0.0255 14.043 0.9859 0.0015 17.476 0.9974 0.2182 0.1414

0.109 15.378 0.9886 0.0089 17.285 0.9958 0.3573 0.3514

0.9971

0.9941

0.9581

confirm this kinetic behavior (see Table 7). All the parameters obtained by pseudo-first order, pseudo-second order and Elovich kinetic models are presented in Table 8.

4. Conclusion In the present study, we used nano silica hollow sphere as effective adsorbent to remove metal ions from aqueous solutions. Prepared adsorbent with particles size distribution of less than 100 nano-meters to improve the adsorption capacity were modified with amine groups. Adsorption experiments were carried out for Ni2+, Cd2+, and Pb2+ ions onto SNHS, NH2–SG, and NH2–SNHS. Experimental data were fit with seven different isotherms. Results shows that the Experimental data was better fit with Sips isotherms. The maximum adsorption capacity values of Ni2+, Cd2+, and Pb2+ ions onto NH2–SNHS (from Sips isotherm) were 38.982, 49.526, and 143.295 mg/g, respectively. The kinetic data justified that the adsorption of Ni2+, Cd2+, and Pb2+ ions onto NS followed the pseudo-first-order kinetic model. Whereas, adsorption of Ni2+, Cd2+, and Pb2+ ions onto AS and NAS followed the pseudo-second-order kinetic model. The kinetic studies indicated that the contact time was suitable for the technological applications. Consequently, fundamentally the outlook is promising that the amine functionalized nano silica hollow sphere has the potential of removing significant amounts of metal ions from aqueous solutions. Appendix A. Supplementary data

R2 for SNHS whereas the pseudo-second order model explains the adsorption in a better way for NH2–SNHS, and NH2–SG. The values of error functions, i.e. R2, v2, RMSE, ARE, S RE, MPSD, and ERRSQ

Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.seppur.2011.10.011.

M. Najafi et al. / Separation and Purification Technology 85 (2012) 193–205

References [1] R.K. Misra, S.K. Jain, P.K. Khatri, Iminodiacetic acid functionalized cation exchange resin for adsorptive removal of Cr(VI), Cd(II), Ni(II) and Pb(II) from their aqueous solutions, J. Hazard. Mater. 185 (2011) 1508–1512. [2] F. Fernane, M.O. Mecherri, P. Sharrock, M. Hadioui, H. Lounici, M. Fedoroff, Sorption of cadmium and copper ions on natural and synthetic hydroxylapatite particles, Mater. Charact. 59 (2008) 554–559. [3] A. Da˛browski, Z. Hubicki, P. Podkos´cielny, E. Robens, Selective removal of the heavy metal ions from waters and industrial wastewaters by ion-exchange method, Chemosphere 56 (2004) 91–106. [4] M. Mohsen-Nia, P. Montazeri, H. Modarress, Removal of Cu2+ and Ni2+ from wastewater with a chelating agent and reverse osmosis processes, Desalination 217 (2007) 276–281. [5] B.K.C. Chan, A.W.L. Dudeney, Reverse osmosis removal of arsenic residues from bioleaching of refractory gold concentrates, Miner. Eng. 21 (2008) 272–278. [6] W.S. Wan Ngah, L.C. Teong, M.A.K.M. Hanafiah, Adsorption of dyes and heavy metal ions by chitosan composites: A review, Carbohyd. Polym. 83 (2011) 1446–1456. [7] A. Afkhami, M. Saber-Tehrani, H. Bagheri, Simultaneous removal of heavymetal ions in wastewater samples using nano-alumina modified with 2, 4dinitrophenylhydrazine, J. Hazard. Mater. 181 (2010) 836–844. [8] H. Sakai, S. Matsuoka, A.A. Zinchenko, S. Murata, Removal of heavy metal ions from aqueous solutions by complexation with DNA and precipitation with cationic surfactant, Colloid Surf. A 347 (2009) 210–214. [9] R. Silva, L. Cadorin, J. Rubio, Sulphate ions removal from an aqueous solution: I. Co-precipitation with hydrolysed aluminum-bearing salts, Miner. Eng. 23 (2010) 1220–1226. [10] S.K. Nataraj, K.M. Hosamani, T.M. Aminabhavi, Nanofiltration and reverse osmosis thin film composite membrane module for the removal of dye and salts from the simulated mixtures, Desalination 249 (2009) 12–17. [11] Z. Wu, M. He, X. Guo, R. Zhou, Removal of antimony (III) and antimony (V) from drinking water by ferric chloride coagulation: Competing ion effect and the mechanism analysis, Sep. Purif. Technol. 76 (2010) 184–190. [12] V. Kumar Jha, M. Nagae, M. Matsuda, M. Miyake, Zeolite formation from coal fly ash and heavy metal ion removal characteristics of thus-obtained Zeolite X in multi-metal systems, J. Environ. Manage. 90 (2009) 2507–2514. [13] S.I. Abu-Eishah, Removal of Zn, Cd, and Pb Ions from water by Sarooj clay, Appl. Clay Sci. 42 (2008) 201–205. [14] C.K. Ahn, D. Park, S.H. Woo, J.M. Park, Removal of cationic heavy metal from aqueous solution by activated carbon impregnated with anionic surfactants, J. Hazard. Mater. 164 (2009) 1130–1136. [15] S. Mohan, R. Gandhimathi, Removal of heavy metal ions from municipal solid waste leachate using coal fly ash as an adsorbent, J. Hazard. Mater. 169 (2009) 351–359. [16] P.A. Brown, S.A. Gill, S.J. Allen, Metal removal from wastewater using peat, Water Res. 34 (2000) 3907–3916. [17] S.S. Ahluwalia, D. Goyal, Microbial and plant derived biomass for removal of heavy metals from wastewater, Bioresour. Technol. 98 (2007) 2243–2257. [18] D. Sud, G. Mahajan, M.P. Kaur, Agricultural waste material as potential adsorbent for sequestering heavy metal ions from aqueous solutions – A review, Bioresour. Technol. 99 (2008) 6017–6027. [19] P. Stathi, K. Litina, D. Gournis, T.S. Giannopoulos, Y. Deligiannakis, Physicochemical study of novel organoclays as heavy metal ion adsorbents for environmental remediation, J. Colloid Interf. Sci. 316 (2007) 298–309. [20] R. Say, E. Birlik, A. Denizli, A. Ersöz, Removal of heavy metal ions by dithiocarbamate-anchored polymer/organosmectite composites, Appl. Clay Sci. 31 (2006) 298–305. [21] M. Najafi, R. Rostamian, A.A. Rafati, Chemically modified silica gel with thiol group as an adsorbent for retention of some toxic soft metal ions from water and industrial effluent, Chem. Eng. J. 168 (2011) 426–432. [22] R. Rostamian, M. Najafi, A.A. Rafati, Synthesis and characterization of thiolfunctionalized silica nano hollow sphere as a novel adsorbent for removal of poisonous heavy metal ions from water: Kinetics, isotherms and error analysis, Chem. Eng. J. 171 (2011) 1004–1011.

205

[23] Z.Z. Li, L.X. Wen, L. Shao, J.F. Chen, Fabrication of porous hollow silica nanoparticles and their applications in drug release control, J. Control. Release 98 (2004) 245–254. [24] L. He, A.F. Dexter, A.P.J. Middelberg, Biomolecular engineering at interfaces, Chem. Eng. Sci. 61 (2006) 989–1003. [25] M.E. Davis, Ordered porous materials for emerging applications, Nature 417 (2002) 813–821. [26] A. Stein, Advances in microporous and mesoporous solids – highlights of recent progress, Adv. Mater. 15 (2003) 763–775. [27] M. Chen, L.M. Wu, S.X. Zhou, B. You, A method for the fabrication of monodisperse hollow silica spheres, Adv. Mater. 18 (2006) 801–806. [28] Q. Sun, P.J. Kooyman, J.G. Grossmann, P.H.H. Bomans, P.M. Frederik, P.C.M.M. Magusin, T.P.M. Beelen, R.A. Van Santen, N.A.J.M. Sommerdijk, The formation of well-defined hollow silica spheres with multilamellar shell structure, Adv. Mater. 15 (2003) 1097–1100. [29] X. Wang, X.R. Miao, Z.M. Li, W.L. Deng, Fabrication of microporous hollow silica spheres templated by NP-10 micelles without calcinations, Appl. Surf. Sci. 257 (2011) 2481–2488. [30] W. Fan, L. Gao, Synthesis of silica hollow spheres assisted by ultrasound, J. Colloid Interf. Sci. 297 (2006) 157–160. [31] I.P. Blitz, J.P. Blitz, V.M. Gun’ko, D.J. Sheeran, Functionalized silicas: Structural characteristics and adsorption of Cu(II) and Pb(II), Colloid Surf. A 307 (2007) 83–92. [32] D. Kovacevic, A. Pohlmeier, G. Özbas, H.D. Narres, M.J.N. Kallay, The adsorption of lead species on goethite, Colloid Surf. A 166 (2000) 225–233. [33] S. Lagergren, About the theory of so-called adsorption of soluble substances, Kungliga Svenska Vetenskap-Sakademiens, Handlingar 24 (1898) 1–39. [34] Y.S. Ho, G. McKay, Pseudo-second order model for sorption processes, Process Biochem. 34 (1999) 451–465. [35] Y.S. Ho, C.C. Chiang, Y.C. Hsu, Sorption kinetics for dye removal from aqueous solution using activated clay, Sep. Sci. Technol. 36 (2001) 2473–2488. [36] K. Nakamoto, Infrared and Raman Spectra of Inorganic and Coordination Compounds, Wiley Inter Science, New York, 1977. [37] C.T. Kirk, Quantitative analysis of the effect of disorder-induced mode coupling on infrared absorption in silica, Phys. Rev. B 8 (2) (1988) 1255–1273. [38] A. Heidari, H. Younesi, Z. Mehraban, Removal of Ni(II), Cd(II), and Pb(II) from a ternary aqueous solution by amino functionalized mesoporous and nano mesoporous silica, Chem. Eng. J. 153 (2009) 70–79. [39] M.A. Tofighy, T. Mohammadi, Adsorption of divalent heavy metal ions from water using carbon nanotube sheets, J. Hazard. Mater. 185 (2011) 140– 147. [40] L. Zhang, C. Yu, W. Zhao, Z. Hua, H. Chen, L. Li, J. Shi, Preparation of multiaminegrafted mesoporous silicas and their application to heavy metal ions adsorption, J. Non-Cryst. Solids 353 (2007) 4055–4061. [41] A. Shahbazi, H. Younesi, A. Badiei, Functionalized SBA-15 mesoporous silica by melamine-based dendrimer amines for adsorptive characteristics of Pb(II), Cu(II), and Cd(II) heavy metal ions in batch and fixed bed column, Chem. Eng. J. 168 (2011) 505–518. [42] E. Repo, T.A. Kurniawan, J.K. Warchol, M.E.T. Sillanp, Removal of Co(II) and Ni(II) ions from contaminated water using silica gel functionalized with EDTA and/or DTPA as chelating agents, J. Hazard. Mater. 171 (2009) 1071– 1080. [43] K.F. Lam, K.L. Yeung, G. McKay, Efficient approach for Cd2+ and Ni2+ removal and recovery using mesoporous adsorbent with tunable selectivity, Environ. Sci. Technol. 41 (2007) 3329–3334. [44] L. Bois, A. Bonhomme, A. Ribes, B. Pais, G. Raffin, F. Tessier, Functionalized silica for heavy metal ions adsorption, Colloids Surf. Physicochem. Eng. Aspects 221 (2003) 221–230. [45] I. Hatay, R. Gup, M. Ersöz, Silica gel functionalized with 4-phenylacetophynone 4-aminobenzoylhydrazone: Synthesis of a new chelating matrix and its application as metal ion collector, J. Hazard. Mater. 150 (2008) 546–553.