Investigation of [alpha]-iron oxide-coated polymeric nanocomposites capacity for efficient heavy metal removal from aqueous solution.


Nowadays, environmental pollution caused by heavy metals has been considered a major problem and has continuously been the focus of worldwide attention [1], Heavy metals with adverse health effects in human metabolism present obvious concerns due to their persistence in the environment and documented potential for serious health consequences [2], Heavy metals like arsenic (As), copper (Cu), cadmium (Cd), chromium (Cr), nickel (Ni), zinc (Zn), lead (Pb), mercury (Hg) and manganese (Mn) are often detected in industrial wastewaters [3], which originate from the metal plating, mining activities, smelting, battery manufacture, tanneries, petroleum refining, paint manufacture, preparation of nuclear fuels, pesticides, purification of metals, pigment manufacture, printing and photographic industries, etc. [4]. Among the variable heavy metals, copper, which has many applications in industries, is one of the most important toxic heavy metals. Copper is an essential trace element that is vital to the health of all organism (humans, plants, animals, and microorganisms). While these heavy metals are needed by living things at the micronutrient level, higher concentrations are known to produce a range of disorders such as stomach ailments, intestinal distress, liver and kidney damage and anemia [5]. Therefore, it is necessary to remove these heavy metals from the wastewaters before their discharge into the environment to meet increasingly stringent environmental quality standards. In recent years, the removal of toxic heavy-metal ions from sewage, industrial and mining waste effluents have been widely studied. Various techniques like adsorption, precipitation, ion exchange, reverse osmosis, electrochemical treatments, membrane filtration, evaporation, flotation, oxidation-reduction and solvent extraction are extensively used to remove heavy metal ions from aqueous solutions [6-8]. Among these methods; adsorption has increasingly received more attention due to simplicity, cost-effectiveness and high feasibility of industrial application without yielding harmful by-products. The most common adsorbent materials are rice husk ash [9], bio-char [10, 11], cellulose [3, 12], algal biomass [13], lignin [14, 15], carbon nanotube [16], activated carbon [17, 18], chitosan [19] polypyrrole [20] titanium oxide [21] and alginate [22]. However, these adsorbents described above suffer from low adsorption capacities and separation inconvenience. Therefore, efforts are still needed to exploit new promising adsorbents. Among the available adsorbents magnetic nanoparticles, hematite nanoparticles are classified as one of the promising agents for heavy metals removal from aqueous systems due to its large surface area, high activity, high capacity and selectivity [23, 24]. One challenge to overcome in application of these materials is that because of nanometric size, the bare magnetite nanoparticles are prone to agglomeration. Also, due to Brownian motion, these nanoparticles generally will not settle under normal conditions, and large magnetic forces should be utilize to overcome opposing forces in the separation process. Thus, providing a suitable support to coat magnetic nanoparticles is very important. In recent years, magnetic nanoparticles coated on different supports for the removal of Cu(II) from industrial wastewater have gained lots of attention. Several researches are available on the use of many different agents as a supporting material for the grafting of magnetic nanoparticles and their application for the removal of heavy metals from wastewater. Zhang and et al. [25] synthesized EDTAD-modified magnetic baker's yeast biomass and studied its ability to remove [Pb.sup.2+] and [Cd.sup.2+] from aqueous solution. Idris et al. [26] have evaluated the adsorption performance of the Pb(II) by using magnetic alginate beads; consisting of maghemite nanoparticles embedded in alginate.

In this work, magnetic hematite nanoparticles embedded on polystyrene cores are used as a sorbent to removal copper. Factors affecting the adsorption efficiency include initial concentration of [Cu.sup.2+] ion, pH, temperature and agitation time which have been investigated through batch sorption experiments. The experimental equilibrium adsorption datas were fitted using adsorption isotherm models (Langmuir, Freundlich, Sips and Redlich-Petersen), kinetics (pseudo-first-order, pseudo-second-order), thermodynamics ([DELTA]G[degrees], [DELTA]H[degrees] and [DELTA]S[degrees]), and interaction mechanism of PS@[alpha]-[Fe.sub.2][O.sub.3] nanoparticles and metal ions were also investigated.



Copper (II) sulfate (CuS[O.sub.4].5[H.sub.2]0), Ferric chloride ([Fecl.sub.3].6[H.sub.2]O), Sodium hydroxide (NaOH), the monomer, St (styrene), the initiator ammonium Peroxodisulfate [[(N[H.sub.4]).sub.2][S.sub.2][O.sub.8] (APS)] and the Stabilizer Poly vinyl pyrrolidone (PVP) were all purchased from Merck. All chemicals were of analytical grade and used without further purification.

Preparation of Hematite Nanoparticles via Sol-Gel Method

In a typical procedure, 50 mL of 5.4 M NaOH solution was dropped into 50 mL of 2.0 M [Fecl.sub.3] solution under vigorous magnetic stirring for 20 min. The resultant brown precipitate precursor [Fe[(OH).sub.3]] was transferred into oven at 100[degrees]C for 8 days. Afterward, the products were separated from the mother liquor by centrifugation. The precipitates were dried in an oven at 45[degrees]C for 24 h and then hematite nanoparticles were prepared after grinding [27],

Preparation of PS@[alpha]-[Fe.sub.2][O.sub.3] Nanocomposite Particles

The synthesis of PS@[alpha]-[Fe.sub.2][O.sub.3] nanoparticles were based on the microemulsion polymerization method. First, Accurately weighed (0.5 g) amount of [alpha]-[Fe.sub.2][O.sub.3] was dispersed in water via ultrasonica tion. Then the above suspension was added to 50 ml distilled water containing a definite ratio of PVP followed by the addition of 6 mL of styrene monomer. The mixture was heated to 70[degrees]C under vigorous stirring. Thereafter, the initiator APS was added drop-wise to the mixture. The resulting solution was kept refluxing at 70[degrees]C for 6 h. Then, the final products were separated and repeatedly washed with the centrifuge and then dried in the oven for 24 h.


The morphology and size distribution of the obtained products were investigated by a Zeiss EM10C transmission electron microscope (TEM) working at 80 KV. The chemical structures of the samples were analyzed by Fourier-transform infrared spectrophotometer. FTIR spectra was recorded by a vector 22 spectrometer, in the range of 400-4000 [cm.sup.-1] using KBr pellet method. Structural characterization of hematite was carried out by a INEL, EQuinox 3000 X-ray diffraction (XRD) using Cu K[alpha] ([lambda] = 1.54178[degrees]A) radiation. The initial and final copper concentrations remaining in the solutions were determined by a UV/Visible Spectrophotometer (UV-2800 Single Beam).

Adsorption Experiments

Copper stock solutions were prepared by dissolving a known quantity of copper(II) sulfate (Cu[So.sub.4]) in ultra-pure water.

The adsorption experiments were performed by adding 0.1 g of PS@[alpha]-[Fe.sub.2][O.sub.3] nanoparticles in 10 mL of [Cu.sup.2+] solution with specific initial concentration and pH. Then the solution was agitated with a constant speed of 200 rpm for an appropriate time in room temperature. The pH value was adjusted by adding 0.1 M NaOH or HCl.

The amounts of Cu(II) adsorbed were calculated by using the following equations:

[q.sub.e] = ([C.sub.0] - [C.sub.3])V / m (1)

where [C.sub.o] is the initial concentration (mg/L) and [C.sub.e] is the equilibrium concentration (mg/L) of copper. V is the volume of the aqueous phase (L), m is the amount of the adsorbent used (g), and [q.sub.e] is the equilibrium adsorption capacity (mg/g).

The removal ratio of Cu(II) adsorption from aqueous solution is calculated as follow:

Removal efficiency (%)= 100. ([C.sub.0] - [C.sub.3]/ [C.sub.0]) (2)

After adsorption, the solution was filtered and the residual concentration of the metal ions was determined by a UV/Visible Spectrophotometer.


Characterization of Magnetic Nanocomposites

Morphology. Figure 1 presents the transmission electron microscopy (TEM) images of the prepared Polystyrene and PS@[alpha]-[Fe.sub.2][O.sub.3] nanocomposite. Figure la shows that the Polystyrene has spherical shape and a very smooth surface, and its particles size is less than 80 nm. Figure lb shows the TEM micrograph of the PS@[alpha]-[Fe.sub.2][O.sub.3] magnetic microsphere. As can be seen, after polymerization there exists a thin layer of hematite on the surface of PS microspheres. High magnification shows that the nanocomposites structure can be clearly distinguished: gray area for the polymeric core, and dark black area for the magnetic coating. This indicates that hematite nanoparticles were well deposited on the surface of Polystyrene core.

X-ray Fluorescence Spectrometry Analysis. Figure 2 illustrates the main diffraction peaks in XRD diffractogram which confirms the successful synthesis of hematite nanoparticles. Diffraction peaks at 27.1[degrees], 32.2[degrees], 35.5[degrees], 39.5[degrees], 45.7[degrees], 56.1[degrees], 61.7[degrees], 64.3[degrees], and 67.5[degrees] are assigned to (012), (104), (110), (113), (024), (116), (018), (214), and (300) crystal planes of [alpha]-[Fe.sub.2][O.sub.3] (PDF No. 33-0664). The narrow sharp peaks of the XRD pattern indicate that the [alpha]-[Fe.sub.2][O.sub.3] product was well crystallized.

FUR Analysis. FTIR spectra of hematite nanoparticles and PS@[alpha]-[Fe.sub.2][O.sub.3] magnetic microsphere are presented in Figure 3. The FT-1R spectra of the prepared hematite is shown in Fig. 3a. The absorption peaks at 477 [cm.sup.-1] and 675 [cm.sup.-1] are the characteristic stretching vibrations of Fe-0 bond in hematite particles. The absorption peaks at 3420[cm.sup.-1] is attributed to the hydroxyl group (-OH). The presence of the absorption peak at 2360 [cm.sup.-1] reveals the presence of atmospheric C[O.sub.2]. The absorption band at 1627 [cm.sup.-1] refers to the vibration of remaining [H.sub.2]O on the sample. Furthermore, in Fig. 3b we can observe the typical bands such as C-H stretching at 752 [cm.sup.-1], C-C stretching vibration at 1446 [cm.sup.-1] and 1490 [cm.sup.-1], C=C stretching vibration at 1647 [cm.sup.-1] and C-H stretching vibration of the benzene ring at 2923-3026 [cm.sup.-1], which were attributed to the polystyrene core. Besides, we can observe, the nanocomposite is having characteristic peaks at 400 and 539 [cm.sup.-1] which were corresponded to hematite nanoparticles. This indicates the presence of hematite nanoparticles in the nanocomposite after coating.

Removal Study of Copper from an Ac/ueous Medium by Batch Method

Effect of pH on Adsorption of Cu(II) Ions. It is known that the pH of the solution is an important parameter affecting the removal of metal ions by adsorption [28]. The effect of pH on the adsorption capacity of PS/[alpha]-[Fe.sub.2][O.sub.3] was investigated using 10 mL of Cu(II) solution containing 0.1g adsorbent with the pH value of 2.0, 3.0, 4.0, and 5.0 at room temperature. As shown in Fig. 4, the adsorption capacity of copper ions onto the PS/[alpha][Fe.sub.2][O.sub.3] was increased with the increase in pH from 2.0 to 5.0. Further experiments using pH > 5 was not attempted because the precipitation tooke place to some degree in the aqueous solution at pH = 6. The highest adsorption capacity was achieved at pH values up to 5. The reduction in the adsorption of copper at low pH was due to the electrostatic repulsions between the positive surface charge of PS/[alpha]-[Fe.sub.2][O.sub.3] and the positively charged Cu(II) species in solution. Therefore, the adsorption capacity of PS/[alpha]-[Fe.sub.2][O.sub.3] increased as the solution pH increases due to electrostatic attractions between positively charged metal ions and negatively charged surface sites of PS/[alpha][Fe.sub.2][O.sub.3] [29].

Effect of Copper Initial Concentration. The effect of initial [Cu.sup.2+] concentration on the removal efficiency was performed by varying the initial Cu(Il) concentrations from 100 to 500 mg/L. Results indicated that the adsorption of metal ions by any adsorbent is highly dependent on the initial concentration of metal ions. It is evident in Fig. 5 that the equilibrium load of copper per unit area of PS@[alpha]-[Fe.sub.2][O.sub.3] decreased almost linearly by increasing the initial concentration of copper ions in solution. This can be explained that the adsorption of [Cu.sup.2+] initially occurs at higher energy sites on PS@[alpha]-[Fe.sub.2][O.sub.3] surface, and as initial concentration of metal ion increases the higher energy sites are first saturated and thereafter, adsorption to the lower energy (the less energetically favorable) sites begins resulting in a decrease in the adsorption efficiency and percentage metal ions adsorbed. Thus all the adsorbents has a limited number of active sites, which become saturated at a certain concentration.

Contact Time Study. Contact time experiments were performed to determine the time required to attain the equilibrium state. For the equilibrium study, 0.1 g of sample was added into each bottle containing 10 mL CuS[O.sub.4] solution with a [Cu.sup.2+] concentration of 100 mg/L at pH value of 5 by varying the contact time from 0.5 to 24 h. As shown in Fig. 6, the removal process took place in two phases. In the first-phase removal percentage of copper ions increased rapidly during the first 5.0 h of contact. This may be due to the fact that initially all adsorbent sites were vacant and the solute concentration gradient was high. In the second phase after 19 h, no remarkable improvement was observed in the adsorption of Cu(II). This is due to the decrease in number of adsorption sites as well as copper concentration. The adsorption equilibrium was reached after approximately 24 h. On the basis of these results, a shaking time of 6.0 h was assumed to be suitable for the sorption experiments.

Effect of the Temperature. To investigate the effect of temperature on copper adsorption, several flasks containing 0.1 g of adsorbent and 10 mL of 100 mg/l aqueous solutions were agitated on a shaker at 200 rpm for 24 h while keeping the temperature at 25, 35, 45, and 55[degrees]C. It can clearly be found from Fig. 7 that the adsorption capacity of metal ions decreased with increasing temperature. The decrease in adsorption density with increasing temperature is likely due to the weakening of attractive forces between adsorbate and the adsorbent. This enhances the tendency of the adsorbate ions to escape from each adsorbent surface to the solution phase, hence desorption may start to occur above this temperature. Also, at high temperature, the thickness of the boundary layer decreases, due to the increased tendency of the metal ion to escape from the biomass surface to the solution phase, which results in a decrease in adsorption as temperature increases. The magnitude of the heat of adsorption can provide useful information concerning the nature of the surface and the adsorbed phase. As we know, the adsorption capacity increases with temperature with the endothermic reactions and decreases with temperature while the reaction must be exothermic. Hence, the Cu(II) adsorption on PS@[alpha]-[Fe.sub.2][O.sub.3] is an exothermic process.

Adsorption Isotherm

The aim of the adsorption isotherms is to relate the adsorbate concentration in the bulk to the adsorbed amount at the interface. So, the study of adsorption isotherms can help describe the adsorption mechanism. There are several isotherm equations available for analyzing experimental adsorption equilibrium data. For a newly developed adsorbent, it is important to get a correct equilibrium equation between the solid and liquid phase concentration of heavy metal. In the present study, Langmuir, Freundlich, Sips and Redlich-Peterson are tested with experimental data.

Langmuir Isotherm. The Langmuir model considers several assumptions, such as the localized adsorption, similar energies on all the active sites on the surface where no interaction between the adsorbed molecules occurs. The Langmuir equation can be expressed as follows [30]:

[q.sub.e] = [q.sub.max] [k.sub.1] [C.sub.e]/1 + [k.sub.1][C.sub.e] (3)

where [q.sub.e] is the amount of solutes adsorbed per unit volume of adsorbent at equilibrium (mg/g), [C.sub.3] the equilibrium concentration in solution (mg/L), [q.sub.m] the maximum capacity of adsorbent (mg/g), and [K.sub.L] is the "affinity parameter" or Langmuir constant (L/mg).

To predict the efficiency of the adsorption process, the dimensionless equilibrium parameter was determined using the following equation:

[R.sub.L] = 1/1 + [K.sub.L] x [C.sub.0] (4)

where [K.sub.L] is the Langmuir constant, [C.sub.0] is the initial concentration, and [R.sub.L] indicates the shape of the isotherm. [R.sub.L] value indicates the adsorption nature to be either unfavorable ([R.sub.L] > 1), linear ([R.sub.L] = 1)> favorable (0 < [R.sub.L] < 1), or irreversible ([R.sub.L] = 0) [31].

Freundlich Isotherm. Freundlich isotherm is commonly used to describe the adsorption characteristics of the heterogeneous surface. Since the adsorption centers on the surface have different values of adsorption energy, the most active sorption centers with maximum energy are filled first [32]. The Freundlich model is represented by the following equation:

[q.sub.e] = [K.sub.r][C.sup.1/n] (5)

where [q.sub.e] and [C.sub.e] are defined as above, [K.sub.r] is the Freundlich constant (L/mg) which is temperature-dependent and n is the heterogeneity factor. The value of n ranging from 2 to 10 indicate good adsorption capacity, 1-2 moderate adsorption capacity and less than one poor adsorption capacity.

Sips Isotherm. The Sips isotherm is a three parameter fitting equation and a combination of the Langmuir and Freundlich isotherms for predicting the heterogeneous adsorption systems. It suggests that at lower initial solute concentrations the equilibrium data follow the Freundlich curve, while at higher solute concentrations it follows the Langmuir trend [33]. It is given as:


In these equations [q.sub.s] (mg/g) and [K.sub.s] (L/mg) have the same meanings as [q.sub.m] and [K.sub.L] in Langmuir model, whereas 1 /[n.sub.s] is an exponent introduced from Freundlich model to indicate the heterogeneity of the adsorption sites.

Redlich-Peterson Isotherm. Redlich-Petersen has proposed an empirical isotherm with three parameters incorporating the features of the Langmuir and Freundlich isotherms as follows [34]:

[q.sub.e] = [k.sub.R][C.sub.e]/1 + [[alpha].sub.R] [C.sup.[beta].sub.e] (7)

where [K.sub.R], [[alpha].sub.R] and [beta] are Redlich-Peterson constants and the exponent [beta], is basically in the range of 0 and 1.

This equation reduces to Henry's Law at low surface coverage (when [beta] = 0):

[q.sub.e] = [k.sub.R][C.sub.e]/1 + [[alpha].sub.R] (8)

When [beta] = 1 this equation reduces to Langmuir adsorption isotherm:

[q.sub.e] = [k.sub.R][C.sub.e]/1 + [[alpha].sub.R][C.sub.e] (9)

The nonlinear Langmuir, Freundlich, Sips and Redlich-Peterson adsorption isotherms are given in Fig. 8. Furthermore parameters and correlation coefficients obtained by applying the isotherm models are summarized in Table 1. According to the values of correlation coefficients ([R.sup.2]), the Sips model with highest [R.sup.2] value is more suitable than the other model to satisfactorily describe the adsorption process. According to the Sips isotherm model, the maximum monolayer Cu(II) adsorption capacities for magnetic nanocomposite were found to be 34.25 (mg/g). This value indicates that this adsorbent is good adsorbent for copper removal from aqueous solutions.

Determination of Kinetic Rate

The kinetics of the adsorption process by PS@[alpha]-[F.sub.e2][O.sub.3] at pH 5.0 were also measured in order to determine the necessary time to reach the equilibrium conditions at room temperature. About 84% of the total Cu(II) adsorption occurred during the first 5 h of the reaction, while only a very small part of the remained adsorption appeared during the following 19 h of contact. To predict the mechansm involved during the present sorption process and the potential rate controlling steps such as mass transport, pore diffusion and chemical reaction processes, the kinetic data obtained from batch experiments have been analyzed using a pseudo-first-order rate equation and pseudo-second-order rate equation.

Pseudo-First-Order. Lagergren pseudo-first-order kinetics is one of the most frequent kinetic models used to describe the adsorption of different adsorbates from an aqueous solution by solid adsorbent. It could be written as the following [35]:


where [q.sub.e] and [q.sub.t] refer to the adsorption capacity of [Cu.sup.2+] (mg/g) at equilibrium and at any time, t (min), respectively and [k.sub.1], is the rate constant of pseudo-first-order adsorption ([min.sup.-1] ).

Pseudo-Second-Order. The nonliner form of the pseudo-second-order rate equation is given as [36]:

[q.sub.t] = [q.sup.2.sub.e][K.sub.2]t/1 + [q.sub.e] [K.sub.2]t (11)

where [k.sub.2] is the rate constant of pseudo-second-order adsorption (g/mg/min) and [q.sub.e] and [q.sub.t] are the values of the amount adsorbed per unit mass at equilibrium and at any time t, respectively. The values of [q.sub.e], [k.sub.1], [k.sub.2] and the correlation coefficients were determined from the nonlinear plots of q, versus t (Fig. 9). The corresponding kinetic parameters from both models are listed in Table 2. As can be seen, the coefficient of determination ([R.sup.2]) of the pseudo-second order kinetic model (0.993) was higher than the other model indicating that the adsorption perfectly complies with pseudo-second order reaction. In addition, the theoretical [q.sub.e] values found from the second-order kinetic model are in accordance with the experimental [q.sub.e] values.

Thermodynamic Parameters for the Adsorption

Thermodynamic parameters such as change in Gibbs free energy [DELTA]G[degrees], enthalpy [DELTA]H[degrees], and entropy change [DELTA]S[degrees] were evaluated to understand the influence of temperature on the adsorption process. These parameters can be determined by using the following thermodynamic functions [37]:

[DELTA]G[degrees] = -RT ln [K.sub.L] (12)

[K.sub.L] = [q.sub.e]/[C.sub.e] (13)

ln [K.sub.L] = [DELTA]S[degrees]/R - [DELTA]H[degrees]/RT (14)

where [K.sub.L] is the equilibrium constant obtained from the Langmuir isotherm equation, T is the absolute solution temperature (K), and R is the ideal gas constant (8.314 J/mol/K). [DELTA]H[degrees] and [DELTA]S[degrees] were calculated from the slope and intercept of Van's Hoff plots of ln[K.sub.L] versus 1/T as shown in Fig. 10. The results were listed in Table 3.

Negative [DELTA]G[degrees] values are obtained at all temperatures reveal the spontaneous nature of these adsorptions and the negative values of [DELTA]H[degrees] suggest the exothermic nature of the adsorption. Furthermore, negative [DELTA]S[degrees] of the adsorption process shows that the organization of the adsorbate at the solid/solution interface becomes less random.

Adsorption Mechanism

To understand the adsorption mechanism of metal ions by PS@[alpha]-[Fe.sub.2][O.sub.3] nanoparticles, the effect of pH was studied. Solution pH has been the most important variable governing the adsorption of metal ions by the sorbent. pH affects both the solubility of metal ions, the ionization states of functional groups and the surface charge of the adsorbent [38], The adsorption properties of iron oxide are mainly due to the existence of OH, O[H.sub.2+], and [O.sup.-] functional groups at adsorbent surface. In aqueous systems, iron oxide particles are hydrated, and FeOH groups cover completely their surface. At acidic pH, nanocomposites are protonated and O[H.sup.2+] functional groups cover completely their surface. So the net surface charge is positive and the surface can adsorb anionic species. Hence the electrostatic repulsion between the copper species and the surfaces of the nanocomposites increased with the formation of more positive charges sites on the surface of adsorbent. As the pH increases, the hydroxyl group on the iron-oxide coated nano adsorbent surfaces are increasingly deprotonated and [O.sup.-] groups cover completely their surface. So, the [O.sup.-] groups forms on the surface of nanocomposite are dominant and responsible for the selective binding of ionic forms of copper species. It can be explained that high pH plays an important role in dissociating proton of functional groups, resulting in more negatively charged functional groups, and the capacity of combination and probability of reaction between functional groups and Cu(II) can also be enhanced. The surface protonation and deprotonation of the magnetic nanocomposites can be described by the following equations [39]:

--FeOH + [H.sup.+] [right arrow] - FeO[H.sup.+.sub.2] (15)

--FeOH [right arrow] -Fe[O.sup.-] + [H.sup.+] (16)

The mechanism of surface hydroxyl group protonation and deprotonation are depicted in Fig. 11.

This shows the adsorption capacity of Cu(II) is significantly affected with functional groups on the adsorbent. Therefore surface complexes occurs between the positive sorbate species and the negatively charged adsorbent, which ultimately resulted in the increased adsorption of metal ions.

Thus, a possible mechanism of adsorption of positive sorbate species from the aqueous in high pH could be considered as follow: Cu(II) a divalent heavy-metal ion attaches itself to two [O.sup.-] groups, and two oxyl group could donate two pairs of electrons to metal ions. Thus the surface complexes occurs between the copper species and the negatively charged adsorbent [40] (Scheme 1).


Hematite nanoparticles were initially synthesized and then were loaded on the surface of polystyrene core to reduce agglomeration. PS@[alpha]-[Fe.sub.2][O.sub.3] nanocomposites were synthesized using the microemulsion polymerization. The results of both TEM and FTIR analysis confirmed the presence of hematite in the magnetic nanocomposite structure. The PS@[alpha]-[Fe.sub.2][O.sub.3] nanocomposites were then used for the removal of copper ions. The adsorption capacity is determined at different operating parameters that affect the adsorption of Cu(II) onto magnetic nanocomposite (pH, initial ion concentration, time and effect of temperature). The results indicate that the adsorption efficiency increases with increasing pH and time values and then decreases with increasing initial concentration and temperature values. The adsorption isotherm of the magnetic nanocomposite agreed well with Sips adsorption equation, and the maximum adsorbed amount of copper was 34.25 mg/g. The kinetics of the adsorption were found to follow the pseudo-second order model. Moreover, the thermodynamic parameters indicated that the adsorption process was spontaneous and exothermic.


[1.] M. Bilal, J.A. Shah, T. Ashfaq, S.M.H. Gardazi, A.A. Tahir, A. Pervez, H. Haroon, and Q. Mahmood, J. Hazard. Mater., 2, 263 (2013).

[2.] A. Demirbas, J. Hazard. Mater., 2, 157 (2008).

[3.] D.W. O'Connell, C. Birkinshaw, and T.F. O'Dwyer, Bioresoar. Technol., 99, 15 (2008).

[4.] N. Li and R. Bai, Sep. Purif. Techno!., 3, 42 (2005).

[5.] M.S. Rahman and M.R. Islam, Chem. Eng. J., 1, 149 (2009).

[6.] X. Chen, J. Cai, Z. Zhang, L. Liu, and G. Yang, Colloid. Polym. Sci., 9, 292 (2014).

[7.] Y. Chen, B. Pan, H. Li, W. Zhang, L. Lv, and J. Wu, Environ. Sci. Technol., 9, 44 (2010).

[8.] N. Nagireddy, M. Yallapu, V. Kokkarachedu, R. Sakey, V. Kanikireddy, J. Pattayil Alias, and M. Konduru, J. Polym. Res., 6, 18 (2011).

[9.] A. Keranen, T. Leiviska, B.-Y. Gao, O. Hormi, and J. Tanskanen, Chem. Eng. Sci., 1, 98 (2013).

[10.] M. Kilic, C. Kirbiyik, O. Cepeliogullar, and A.E. Piitiin, Appl. Surf. Sci., 283 (2013).

[11.] Y. Guo, W. Tang, J. Wu, Z. Huang, and J. Dai, J. Environ. Sci., 10, 26 (2014).

[12.] X. Yu, S. Tong, M. Ge, L. Wu, J. Zuo, C. Cao, and W. Song, J. Environ. Sci., 5, 25 (2013).

[13.] R. Herrero, P. Lodeiro, L.J. Garcia-Casal, T. Vilarino, C. Rey-Castro, C. David, and P. Rodriguez, Bioresour. Techno!., 3, 102 (2011).

[14.] Y. Ge, Z. Li, Y. Kong, Q. Song, and K. Wang, J. Ind. Eng. Chem., 6, 20 (2014).

[15.] Q. Yao, J. Xie, J. Liu, H. Kang, and Y. Liu, J. Polym. Res., 6, 21 (2014).

[16.] M. Abdel Saiam, G. Al-Zhrani, and S.A. Kosa, J. Ind. Eng. Chem., 2, 20 (2014).

[17.] M. Luz Godino-Salido, A. Santiago-Medina, P. Arranz-Mascaros, R. Lopez-Garzon, M.D. Gutierrez-Valero, M. Melguizo, and F. Javier Lopez-Garzon, Chem. Eng. Sci., 114, (2014).

[18.] M. Abbas, S. Kaddour, and M. Trari, J. Ind. Eng. Chem., 3, 20 (2014).

[19.] S. Salahi, M. Parvini, and M. Ghorbani, Polycyclic Aromat. Compd., 3, 34 (2014).

[20.] M. Omraei, H. Esfandian, R. Katal, and M. Ghorbani, Desalination, 1-3, 271 (2011).

[21.] M. Ghaemy, S. Qasemi, K. Ghassemi, and M. Bazzar, J. Polym. Res., 10, 20 (2013).

[22.] W. Wang, Y. Kang, and A. Wang, J. Polym. Res., 3, 20 (2013).

[23.] S. Kalia, S. Kango, A. Kumar, Y. Haldorai, B. Kumari, and R. Kumar, Colloid. Polym. Sci., 9, 292, (2014).

[24.] M. Hua, S. Zhang, B. Pan, W. Zhang, L. Lv, and Q. Zhang, J. Hazard. Mater., 1, 211 (2012).

[25.] Y. Zhang, J. Zhu, L. Zhang, Z. Zhang, M. Xu, and M. Zhao, Desalination, 1, 278 (2011).

[26.] A. Idris, N.S.M. Ismail, N. Hassan, E. Misran, A.-F. Ngomsik, J. Ind. Eng. Chem., 5, 18 (2012).

[27.] Y. Yonemochi, M. Iijima, M. Tsukada, H. Jiang, E. Kauppinen, M. Kimata, M. Hasegawa, H. Kamiya, Adv. Powder Techno!., 6, 16 (2005).

[28.] A.R. Iftikhar, H.N. Bhatti, M.A. Hanif, and R. Nadeem, J. Hazard. Mater.,2, 161 (2009).

[29.] S. Liang, X. Guo, N. Feng, and Q. Tian, J. Hazard. Mater., 1, 174 (2010).

[30.] I. Langmuir, J. Am. Chem. Soc., 11, 38 (1916).

[31.] E. Malkoc, Y. Nuhoglu, and M. Dundar, J. Hazard. Mater., 1, 138 (2006).

[32.] H. Freundlich, J. Phys. Chem., 57, 385 (1906).

[33.] R. Sips, J. Chem. Phys., 5, 16 (1948).

[34.] O. Redlich and D.L. Peterson, J. Phys. Chem., 6, 63 (1959).

[35.] S. Lagergren, Handlingar, 4, 24 (1898).

[36.] Y.-S. Ho and G. McKay, Process Biochem., 5 34 (1999).

[37.] F. Liu, L. Li, P. Ling, X. Jing, C. Li, A. Li, and X. You, Chem. Eng. J., 1, 173 (2011).

[38.] R.J. Murphy, J.J. Lenhart, and B.D. Honeyman, Colloids Surf. Physicochem. Eng. Aspects, 3, 157 (1999).

[39.] H. Tamura, E. Matijevic, and L. Meites, J. Colloid Interface Sci., 2, 92 (1983).

[40.] S. Lazarevic, I. Jankovic-Castvan, V. Djokic, Z. Radovanovic, D. Janackovic, and R. Petrovic. J. Chem. Eng. Data, 12, 55 (2010).

Elahe Fallah TAIooki, (1) Mohsen Ghorbani, (2) Ali Asghar Ghoreyshi (2)

(1) M. Sc. student of Chemical Engineering Department, Babol University of Technology, P.O. Box 484, Babol, Iran

(2) Faculty of Chemical Engineering, Babol University of Technology, P.O. Box 484, Babol, Iran

Correspondence to: M. Ghorbani; e-mail:

DOI 10.1002/pen.24l62

Published online in Wiley Online Library (

TABLE 1. Adsorption isotherm parameters of [Cu.sup.2+] on to
PS@[alpha]-[Fe.sub.2][O.sub.3] nanoparticles by Langmuir. Freundlich,
Sips and Redlich-Peterson equation.


                    [q.sub.L]         [K.sub.L]
[R.sub.L]         (mg/[g.sup.-1])   (L/[mg.sup.-1])   [R.sup.2]

0.19                   29.69             0.041         0.9945


(mg/[g.sup.-1])      [K.sub.s]        l/[n.sub.s]     [R.sup.2]

34.25                  0.028            0.7493         0.9982


                        1/n      [K.sub.F]      [R.sup.2]

                      0.3031       5.5081         0.9846


[K.sub.R]         [[alpha].sub.R]        [beta        [R.sup.2]

1.725                 0.1068            0.8889         0.9975

TABLE 2. Kinetic parameters of the pseudo-first order and pseudo-
second order models and intraparticle diffusion of [Cu.sup.2+] onto
the PS@[alpha]-[Fe.sub.2][O.sub.3].

                           pseudo-first order

Experimental       [q.sub.e]   [K.sub.1]
[q.sub.e] (mg/g)    (mg/g)      (1/min)    [R.sup.2

9.1                  8.52       0.7274      0.9694

        pseudo-second order

[q.sub.e]     [K.sub.2]
(mg/g)        (g/mg/min)  [R.sup.2]

9.32            0.12       0.9932

TABLE 3. Thermodynamic parameters [DELTA]H[degrees],
[DELTA]S[degrees], and [DELTA]G[degrees] for adsorption of copper
onto PS@[alpha]-[Fe.sub.2][O.sub.3] at 25, 35, 45, and 55[degrees]C.

Temperature   [DELTA]G[degrees]  [DELTA]H[degrees]  [DELTA]S[degrees]
(K[degrees])      (KJ/mol)           (KJ/mol)          (KJ/mol/K)

298                 -0.26
308                 -1.24              -35.1              -0.12
318                 -2.74
328                 -3.71

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