γ-alumina nanocomposite: A comparative study for the adsorption of three different anionic dyes

γ-alumina nanocomposite: A comparative study for the adsorption of three different anionic dyes

G Model JIEC-1825; No. of Pages 11 Journal of Industrial and Engineering Chemistry xxx (2014) xxx–xxx Contents lists available at ScienceDirect Jou...

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G Model

JIEC-1825; No. of Pages 11 Journal of Industrial and Engineering Chemistry xxx (2014) xxx–xxx

Contents lists available at ScienceDirect

Journal of Industrial and Engineering Chemistry journal homepage: www.elsevier.com/locate/jiec

Synthesis and characterization of polyaniline/g-alumina nanocomposite: A comparative study for the adsorption of three different anionic dyes Hamedreza Javadian a,*, Mahmood Torabi Angaji b, M. Naushad c a b c

Department of Chemical Engineering, Shahrood Branch, Islamic Azad University, Shahrood, Iran Department of Chemical Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran Advanced Materials Research Chair, Department of Chemistry, College of Science, Building#5, King Saud University, Riyadh, Saudi Arabia


Article history: Received 3 December 2013 Accepted 30 December 2013 Available online xxx Keywords: Nano-structures Polymer-matrix composites (PMCs) Adsorption Anionic dyes Kinetic Isotherm


In this study, polyaniline/g-alumina nanocomposite was synthesized by chemical oxidation method and characterized by field emission scanning electron microscopy, transmission electron microscopy, Fourier transform-infrared spectrometer, X-ray diffraction, thermogravimetric analysis, differential scanning calorimetry, and Brunauer–Emmett–Teller method. Batch adsorption experiments were conducted for removing three types of hazardous dyes Reactive Red 194, Acid Blue 62 and Direct Blue 199 from aqueous solution and the effect of pH, adsorbent dosage, contact time, and initial concentration of dyes were investigated. Meanwhile, kinetic, isotherm, and thermodynamic parameters were also determined. ß 2014 The Korean Society of Industrial and Engineering Chemistry. Published by Elsevier B.V. All rights reserved.

1. Introduction Textile wastewaters are usually one of the primary environmental pollutants [1]. Among different industries, textile industries have greatly developed in recent years [2]. According to the United States Environmental Protection Agency (USEPA), textile industries wastewaters are divided into four groups: dispersible, hard to treat, high volume, and toxic wastewaters. Dyeing and complementary stages are the two main stages in textile industries which produce the highest amount of wastewaters with the highest dye concentration [3,4]. In the processes of dyeing nearly 10–15% of the used dyes enter the environment through wastewater discharges [5]. The reports show that the annual production of textiles (fibers) and their wastewaters are about 40 million tons and 4–8 million cubic meters all around the world, respectively [6]. The synthetic dyes are usually divided into acidic, direct, basic etc [7]. Having one or more azo bands, reactive dyes are the biggest group of synthetic dyes which are used for dyeing fibers. The reasons of using such dyes are that they are very cheap, less toxic, and so prevailed for such purposes [8,9]. Based on reports, it is estimated that almost 50% of dyes which are usually

* Corresponding authors. Tel.: +98 911 3235538. E-mail addresses: [email protected] (H. Javadian), [email protected] (M. Naushad).

produced in the world (700,000 tons) are azo dyes [8,10]. Because of their solubility in water, higher concentration in textile wastewaters, and difficulty to be eliminated from wastewaters, these kinds of dyes are considered as dangerous compounds. Acidic dyes which are from inorganic sulfonic acid groups are very important. They are as sodium salts and are mainly used for dyeing particular fibers like wool and silk. Direct dyes are highly watersoluble due to the presence of ionic sulfonic acid groups or amino groups which are often resistant to biological breakdown. Consequently, they are not eliminated by usual methods. Different methods have so far been used to treat textile wastewaters. Biological treatment methods are not applicable because of their toxic nature which is not appropriate for microorganisms existed in the process. Also the high existence of some dyes in biological treatment and low efficiency in dye removal are the other two reasons [11,12]. Ultra filtration and reverse osmosis techniques are not economical due to high costs of utilization [11,13,14]. Electrochemical process is an environmental friendly process and economically competitive with other methods of treatment [15]. This method is highly-efficient for textile wastewater treatment and has some advantages including simple equipment requirement [16,17], high speed and short retention time for pollutant removal [18,19], easy navigation, and little need to use chemical consumption [18,20]. However, absorption process is one of the best method in comparison to other methods because it can cause physical removal of contaminants from wastewater

1226-086X/$ – see front matter ß 2014 The Korean Society of Industrial and Engineering Chemistry. Published by Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jiec.2013.12.095

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without producing any dangerous by-product during the process [21]. In the last two decades, conducting polymers are of particular interest due to their potential applications in areas such as: anticorrosion coatings, batteries, sensors [22,23], electrochromic displays [24], artificial muscles [25], microelectronics [26], supercapacitor [27], and diodes [28]. Among all the conducting polymers, polyaniline is one of the most important conducting polymers because of easy preparation, high electrical conductivity, environmental stability, and cost-effectiveness [29]. Polyaniline nanocomposites have been tested in various acidic and basic media with different concentrations of metals which indicate the ability of these nanocomposites for adsorbing metals from water. One application of these nanocomposites can be in removing dyes from industrial wastewaters, which has been less taken into account. This polymer can be coated on other adsorbents and materials such as alumina which has no functional groups leading to produce an effective adsorbent because there are plenty of amine and imine groups in polyaniline which can adsorb the anionic dye species through electrostatic interactions or hydrogen bonds. In this study, polyaniline/g-alumina (PAn/g-Al2O3) was synthesized by in situ chemical polymerization method using APS (ammonium peroxydisulfat) as an oxidant and characterized by FE-SEM, TEM, FTIR, XRD, TGA, DSC, and BET techniques. It’s capacity for the removal of dyes from aqueous solutions was investigated and the effect of different parameters including pH of solution, reaction time, adsorbent dosage, and initial concentration of dye on the removal efficiency were investigated in detail. Adsorption kinetics, adsorption isotherms, and thermodynamic parameters were also obtained. 2. Experimental 2.1. Reagents and standard solutions Aluminum isopropoxide Al (OC3H7)3, toluene, methanol, ammonia, hydroxypropyl cellulouse (HPC, Mw = 106), aniline monomer, H2SO4, and NaOH were purchased from Merck (Darmstadt, Germany). Textile dyes were bought from DyStar Co. (Germany). Some of the important physicochemical properties of the investigated dyes are given in Table 1. Distilled deionized water was used throughout this work and aniline monomer was purified by simple distillation.

2.2. Preparation of nano g-Al2O3 particles Nano g-Al2O3 particles were synthesized by sol–gel method using Al (OC3H7)3, toluene, NH4OH, and CH3OH (95%). At first, NH4OH (20 mL) was dissolved in CH3OH 95% (90 mL) and stirred on a magnetic stirrer for 10 min. Then, Al (OC3H7)3 solution (5 g Al (OC3H7)3 in 60 mL toluene) was slowly added dropwise to the NH4OH solution. The obtained solution was kept under fast-speed constant stirring for 5 h at room temperature. After 5 h, the obtained gel was filtrated, washed with acetone, and dried in a vacuum oven at 60 8C for 18 h. Finally, the dried gel was calcined for 2 h in a furnace at 500 8C for transforming of Al (OH)3 into gAl2O3. 2.3. Preparation of PAn/g-Al2O3 nanocomposite The PAn/g-Al2O3 nanocomposite was synthesized by ‘in situ’ polymerization of aniline in the presence of g-Al2O3 nanoparticles and H2SO4 as the dopant. A typical preparation process for PAn/gAl2O3 is as follows: 0.4 g surfactant and 0.3 g of g-Al2O3 nanoparticles was stirred in 50 mL of distilled water for 1 h. Then, 50 mL of sulfuric acid (2 M) and 1 g of ammonium peroxydisulfate (APS) was added to the solution. Finally, 1.0 mL aniline was injected to stirred aqueous solution. After 10 h, nanocomposite was filtered and washed several times with acetone and dried in a vacuum oven at 40 8C for 24 h, until the total mass became constant. 2.4. Instrumental characterization The surface morphology was obtained using field emission scanning electron microscopy (FE-SEM, S-4160, Hitachi, Japan). TEM micrograph was taken using a LEO-906E transmission electron microscopy operated at 200 kV. The functional groups were identified by Fourier transform-infrared spectrometer (FTIR, 8400S, Shimadzu, Japan). The specific surface area was determined by fitting the linear portion of the BET plot to BET equation. The Xray diffraction (XRD) patterns of g-Al2O3 and PAn/g-Al2O3 were obtained using X-ray diffractometer (Philips made, Australia) at 35 kV and 28.5 mA, using Cu Ka radioactive source and 2u scanning range was set between 10 8 and 90 8. The thermal gravimetric analysis (TGA) was carried out using DuPont Instruments

Table 1 Basic properties of the investigated dyes. Characteristic Chemical formula Commercial name Class C.I. number Molecular weight (g mol1) lmax (nm) Molecular structure

RR-194 C27H18N7Na4O16S5Cl Remazol Red 133 Azo 18214 984.21 542

AB-62 C20H19N2NaO5S Nylanthrene Blue B-2RF Anthraquinone 62045 422.43 620

DB-199 C32H14CuN8O6S2NaNH4 Solophenyl Turquoise BRLE Phthalocyanine 74190 775.219 608

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(TGA 951) analyzer. The thermal gravimetric analyzer was used at temperature of 30– 677 8C at heating rate of 10 8C/min in N2 atmosphere. Differential scanning calorimeter (DSC) was recorded on a Perkin Elmer pyris 6 DSC under nitrogen atmosphere (20 cm3 min1) at a heating rate of 10 8C/min. Adsorption experiments were analyzed by UV–vis spectrophotometer (JENWAY-UV 6505) for determination of dye concentration. 2.5. Batch sorption tests Batch adsorption experiments were carried out for dye removal in 250 mL beaker under magnetic stirring with rotating speed of 300 rpm. All the tests transferred 50 mL of dye solution prepared from the dilution of 10 g L1 stock solutions with a desired pH and initial concentration into the beaker on the magnetic stirrer. Then, a known amount of PAn/g-Al2O3 was added to the solution and the resulting suspension was stirred for a predefined time. After mixing time ended, samples were conducted at predetermined time intervals, centrifuged at 4000 rpm for 20 min and the solution analysis of dye residual was conducted colorimetrically using a UV–vis spectrophotometer (JENWAY-UV 6505). The absorbance value for RR-194, AB-62, and DB-199 was read at 542 nm, 620 nm, and 608 nm, respectively. The calibration graph of absorbance versus concentration obeyed the linear Beer–Lambert relationship. The adsorption percent of each dye, i.e., the dye removal efficiency, was determined using the following formula:   Ci  Ct removal efficiency ð%Þ ¼ (1)  100 Ci where Ci and Ct represent the initial and final (at any time t) dye concentrations, respectively. The adsorption capacity at the time t, qt (mg g1), was obtained as follows: qt ¼ ðC i  C t Þ 



where Ci and Ct (mg L1) were the liquid-phase concentrations of solutes at initial and a given time t, V is the volume of the solution and M is the mass of PAn/g-Al2O3 (g). The amount of adsorption at equilibrium qe, was calculated using this formula: qe ¼ ðC i  C e Þ 




where Ce (mg L1) was the dye concentration at equilibrium. 3. Results and discussion 3.1. Characterization of nanocompostie The size distribution and morphology of the products were analyzed by FE-SEM. Fig. 1a shows the FE-SEM micrograph of gAl2O3 prepared by the sol–gel method. As shown in Fig. 1a, the particle size was about 20 nm, roughly spherical, and uniform in distribution. In Fig. 1b, the composite as its substrate (g-Al2O3) formed almost spherical and uniform in particle size distribution. Fig. 1c shows the TEM image of PAn/g-Al2O3 nanocomposite. The TEM image illustrated that g-Al2O3 nanoparticles were surrounded by polyaniline. The light and black spots were g-Al2O3 nanoparticles and polyaniline in the nanocomposite, respectively. The FTIR spectra were recorded to identify the peaks of the products in the range of 4000–400 cm1. In Fig. 2a, the main peaks of g-Al2O3 nanoparticles were as follow: broad and wide band at 3425.34 cm1 related to the structure of the surface hydroxyl groups (Al–OH) and vibrations of Al–O at 609.46 cm1. The FTIR spectrum of PAn/g-Al2O3 indicated that polyaniline had two main peaks at 1481 and 1566 cm1 for the C5 5C stretching deformation of benzonoid and quinonoid rings, respectively. Also, the reduction in intensity of 3425.34 and 609.46 cm1 peaks confirmed that gAl2O3 nanoparticles were dispersed in the polymer matrix. Fig. 2b shows the X-ray diffraction patterns of g-Al2O3 and PAn/g-Al2O3. The two peaks at 2u = 45.47 8 and 66.51 8 were characteristic peaks of g-Al2O3 and the broad peak with 2u = 24.958 was connected with diffraction of amorphous polyaniline. By comparing these spectra, it is quite clear that both curves have two similar peaks at 2u = 45.478 and 66.518 that proved the g-Al2O3 nanoparticles were dispersed in the polymer matrix. The specific surface area was determined using BET equation applied to the adsorption data. The results of the BET method showed that the average specific surface area of g-Al2O3 and PAn/g-Al2O3 were 163 and 60 m2 g1, respectively. Fig. 3a shows the mass loss of PAn/g-Al2O3 upon heating in a nitrogen atmosphere at a rate of 10 8C/min. Initial weight loss for PAn/g-Al2O3 curve started at 65 8C and continued up to 130 8C, approximately. The second step of weight loss continued until a temperature of about 295 8C and then intensive

Fig. 1. (A) FE-SEM images of g-Al2O3, (B) PAn/g-Al2O3 and (C) TEM image of PAn/g-Al2O3.

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Fig. 2. (a) FT-IR spectra and (b) X-ray diffraction patterns of g-Al2O3 and PAn/g-Al2O3.

weight loss continued until 677 8C. The initial weight loss was due to loss of water molecules. The next weight loss was related to the loss of the oligomeric and finally the third step was the decomposition of the polymer chains. The first step of weight loss for PAn/g-Al2O3 was about 7 wt% in the temperature range of

65–130 8C which was related to the moisture evaporation of water molecules in the polymer. The second weight loss that occured in the temperature range of 130 –295 8C related to evaporation and degradation of hydroxypropyl cellulose (HPC) stabilizer. Weight loss at higher temperature, indicated an oxidation process of

Fig. 3. (a) TGA curve and (b) DSC curve of PAn/g-Al2O3 under N2 at a heating rate of 10 8C/min.

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polyaniline. The glass-transition temperature value (Tgs) of the nanocomposite was obtained from the DSC curve with a heating rate of 10 8C min1 under nitrogen. DSC curve of PAn/g-Al2O3 in Fig. 3b did not show melting endothermic peak which emphasize the amorphous nature of this polymer. The Tg value was read at the middle of the first break down observed in the DSC curve and found to be 153 8C. 3.2. Effect of pH The effect of pH is an important parameter which has an impact on the adsorption process. Something that influences on both aqueous chemistry and surface binding sites of the adsorbents is pH solution that affects the overall adsorption process. In the present study, the effect of initial pH on the adsorption of each dye was studied from pH of 2–12 at room temperature (25 8C) where 50 mL of constant initial dye concentration of 50 mg L1, adsorbent dose 0.1 g, stirring speed 300 rpm, and contact time 25 min were taken. Fig. S1 indicates the effect of pH on the adsorption of three dyes onto PAn/g-Al2O3. The optimum removal efficiency for all dyes was acquired at pH 2. Owing to higher concentration of H+ ions in acidic medium, the surface of adsorbent (PAn/g-Al2O3) was positively charged (protonated). Consequently, a significantly high electrostatic attraction existed between the positively charged surface of the adsorbent and anionic dyes [30]. So, for the adsorption of anionic dyes, positively charged surface site on the adsorbent seems to be favorable. Lower adsorption of anionic dyes under alkaline conditions was due to the presence of hydroxyl ions on the surface of adsorbent competing with the adsorbate for adsorption sites [31]. 3.3. Effect of contact time Time of contact of adsorbate and adsorbent is of great importance in adsorption since. To determine the time equilibrium for optimum removal efficiency and kinetic studies, 50 mL of constant initial dye concentration of 50 mg L1, adsorbent dose of 0.1 g and stirring speed of 300 rpm were used. The amount of dyes adsorbed onto the nanocomposite is shown as a function of time (Fig. S2). The equilibrium condition was obtained when the removal efficiency of RR-194 increased from 87.22 to 99.79% as the stirring time was increased from 2 to 20 min. As the stirring time was continued from 2 to 20 min, the removal efficiency for AB-62 increased from 88.208% to 99.85%, respectively. Hence, for both dyes, the equilibrium and full adsorption time were equal. For DB199, the removal efficiency was higher than the other two dyes and its value reached from 91.45 to 99.91% as the stirring time was reached from 2 to 10 min. During the first 2 min of stirring time, the excessive amount of active sites on the sorbent surface may caused rapid adsorption of dyes. Rapid adsorption of these three dyes by PAn/g-Al2O3 is one of the parameters that can be taken into consideration for economical wastewater treatment plant applications. For further experiments, the best contact time for adsorption of RR-194, AB-62, and DB-199 by PAn/g-Al2O3 was believed to be 20, 20, and 10 min, respectively. 3.4. Effect of adsorbent dosage Adsorbent dosage is also an important parameter because it determines the capacity of adsorbent for a given initial concentration of the adsorbate at the operating conditions. The effect of dose of PAn/g-Al2O3 on the removal of dyes is shown in Fig. S3, which indicates the adsorption of dyes with change of PAn/g-Al2O3 dose from 0.01 to0.1 g. This investigation was done by contacting 50 mL of dye solution with initial concentration of 50 mg L1 at optimum conditions of time and


pH. After equilibrium condition, the samples were centrifuged and then concentrations of supernatant solutions were analyzed. As inferred from Fig. S3, for a fixed dye initial concentration, increasing the PAn/g-Al2O3 dose resulted in a higher removal efficiency of dyes. Increase in the removal efficiency was due to more surface area and active sites on the adsorbent at the higher amount of adsorbent, thus making easier penetration of dyes to the sorption sites. As we observed in Fig. S3, the optimum dosage for adsorption of RR-194, AB-27, and DB-199 was 0.06, 0.05, and 0.05 g, respectively. Further increase of the adsorbent dosage did not affect the removal efficiency of dyes. 3.5. Effect of initial concentration The initial dye concentration provides necessary driving force to overcome the resistance to the mass transfer between the aqueous and solid phase. In order to evaluate the effect of initial concentration on removal efficiency and maximum sorption capacity of PAn/g-Al2O3, it was necessary to generate the equilibrium sorption data at various initial dye concentration. Experiments were carried out at optimum conditions of pH, time, and dose of PAn/g-Al2O3. Figs. S4 and S5 show the effect of initial concentration of dyes onto the removal efficiency and sorption capacity of PAn/g-Al2O3. As illustrated in Fig. S4, removal efficiency for RR-194 and AB-27 decreased from 99.79% and 99.85% to 17.15% and 26.87%, respectively. For DB-199, removal efficiency was slightly decreased in comparison to the other two dyes and its decreasing range was from 99.91% to 85.91%. This illustrated that PAn/g-Al2O3 had more affinity for DB-199 than RR-194 and AB-27. Generally, the total number of available sorption sites was constant for a determined adsorbent dose thereby adsorbed nearly the same amount of adsorbate, therefore resulting in a decrease in the removal efficiency of the adsorbate corresponding to an increase in initial concentration of adsorbate. In Fig. S5, sorption capacity of PAn/g-Al2O3 increased first with the increasing of initial concentration of RR-194 and AB-27 then reached a plateau value at initial concentration of 500 and 800 mg L1, respectively, which represented the saturation of the active binding sites of the reactive functional groups on the PAn/g-Al2O3. It is apparent from Fig. S5, as the initial concentration of DB-199 increased, qe was also increased without reaching to a plateau value at even higher concentrations. 3.6. Kinetics of sorption The results as obtained in Section 3.3 were further analyzed to obtain the information on the adsorption kinetics of dye ions on the PAn/g-Al2O3 nanocomposite. The pseudo-first-order kinetic model is based on the approximation that the adsorption rate relates to the number of the unoccupied, adsorptive sites. The model, in its final form, can be written as follows [32]:

lnðqe  qt Þ ¼ lnqe  kt


where qe and qt are the amount of dye adsorbed (mg g1) at equilibrium and at any time t, k is the rate constant (min1). The plot of ln(qe  qt) versus t gave a straight line for the pseudo-firstorder adsorption kinetic model. The values of qe and k can be obtained from the antilogarithmic value of the y-intercept and the slope of the plot, respectively. On the other hand, the adsorption rate could also be approximated on the basis of the pseudo-secondorder kinetic model. This model is based on the notion that the adsorption should relate to the squared product of the difference between the number of the equilibrium adsorptive sites available on an adsorbent and that of the occupied sites. The model can be

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Table 2 Kinetic constants for dye adsorption.

observed values than do the values from the pseudo-first-order kinetic model.

expressed as follows [33]: qt ¼

k2 q2e t ð1 þ k2 qe tÞ


3.7. The isotherm model

where qt and qe are the amount of ion adsorbed at time t and at equilibrium (mg g1) and k2 (g mg1 min1) is the pseudo-secondorder rate constant for the adsorption process. Linear plots should be obtained and the values of qe and k2 can be obtained from the inverse values of the slope and the y-interception values, respectively. However, Eq. (5) can be linearized to four different forms. The different linearized types of the pseudo-second-order model are given in Table 2. The results showed that adsorption of dyes by PAn/g-Al2O3 could be made fit using Type 1, Type 2, Type 3, and Type 4 models; Also, Type1 model offered the best correlation factor for these three dyes. The rate constant was calculated from the slope of the straight line. The experimental results have also been checked by another two kinetic models, namely Morris– Weber and Elovich models which are defined by Eqs. (6) and (7), respectively [34,35].

The adsorption isotherms describe the relationship between the concentration of metal in solution and the amount of metal adsorbed on a specific adsorbent at a constant temperature. Adsorption isotherm gives important information about the mechanism of adsorption and helps us in the design of new adsorbing systems. Various mathematical models can be used to analyze adsorption data. The most common ones are the Langmuir and the Freundlich models. The Langmuir model is derived to describe the adsorption of an adsorbate on a homogeneous, flat surface of an adsorbent, and each adsorptive site can be occupied only once in a one-on-one manner. Mathematically, the model can be written as follows [36]:

qt ¼ kid ðtÞ0:5 þ C

where qe is the amount of dye adsorbed per specific amount of adsorbent (mg g1), Ce the equilibrium concentration of the solution (mg L1), qm the maximum amount of adsorption of (mg g1), and KL is Langmuir adsorption constant (L mg1). This equation can be remodeled and rearranged into four different linear types (Table 3) to determine of Langmuir constant (KL) and adsorption capacity (qm). The best fit was obtained by Langmuir Type 1 as compared with the other Langmuir models. The fundamental characteristic of a Langmuir isotherm parameter (RL) can be expressed in terms of a dimensionless separation factor or an equilibrium parameter, which is defined by the following equation [37]:



lnða bÞ þ






where qt is the adsorbed concentration of dye at time t, and kid in Eq. (6) can be calculated from the slope of the linear plot. In Eq. (7), a (mmol g1 min1) is the initial adsorption rate and b (g mmol1) is the desorption constant. The slope and intercept of the plot of qt versus ln t in Eq. (7) result in the determination of the kinetic constants a and b. The results obtained from Eqs. (4)–(7) are also listed in Table 2. On the basis of the values of the correlation coefficient (R2), the experimental data was fitted better with the pseudo-second-order kinetic model than the pseudo-first-order kinetic model. Moreover, the qe values as obtained from the pseudo-second -order kinetic model appeared to be very close to the experimentally

qe ¼

RL ¼

qm K L C e ð1 þ K L C e Þ

1 ð1 þ K L C i Þ



where Ci is the initial concentration of dye. Obtained qm and KL parameters and also correlation coefficient R2 and RL (Langmuir

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Table 3 Isotherm constants for dye adsorption.

isotherm parameter) values are reported in Table 3. According to the value of RL, the isotherm shape may be interpreted as follows: RL > 1: unfavorable adsorption, RL = 1: linear adsorption, 0< RL < 1: favorable adsorption, RL = 0: irreversible adsorption [38]. The values of RL in Table 3 indicated that the adsorption of dyes onto PAn/g-Al2O3 was favorable. Unlike the Langmuir model, the Freundlich model is used to describe the adsorption of an absorbate on a heterogeneous surface of an adsorbent. The mathematical expression of the model is given as follows [39]:

log ðqe Þ ¼ logðK f Þ þ

  1 logðC e Þ n


where Kf is a constant related to the adsorption capacity and 1/n is an empirical parameter related to the adsorption intensity, which varies with the heterogeneity of material. 1/n values indicate the type of isotherm to be irreversible (1/n = 0), favorable (0 < 1/n < 1), unfavorable (1/n > 1) [40]. The experimental results were also checked by two other isotherm models: the Tempkin isotherm is commonly simplified as the linear form [41]: qe ¼ BlnK T þ BlnC e


here B = (RT/AT) and KT is Tempkin constant. And the Dubinin–Radushkevick (D–R) isotherm which is employed to specify the nature of adsorption process through physisorption or chemisorption [42]. The linear form of this model is described as: ln qe ¼ ln qm  be2

Mean adsorption energy, E (kJ mol1), is determined using the following equation [43]: 1 E¼p 2b


This amount (E), obtained from the D–R model, is very useful because it provides us information about the mechanisms of adsorption process. If E value is between 8 and 16 kJ mol1, the type of adsorption process is chemical; however, if E < 8 kJ mol1, the process occurs physically [44]. Hereby, the mean adsorption energy was found to be 7.071, 3.535, 2.5 kJ mol1 for RR-194, AB62, DB-199, respectively. All the results calculated from the above isotherm models are listed in Table 3. As can be seen from this table, Langmuir and Freundlich isotherm models indicated that both models are able to adequately describe the relationship between the qe and Ce values. However, comparing the results demonstrated that Langmuir model offered a remarkable correlation factor for RR-194 and AB-62 but for DB-199 Freundlich model fitted equilibrium data better than the Langmuir isotherm model. Application of Freundlich model to the equilibrium data of DB199 indicated the monolayer coverage of PAn/g-Al2O3 by the DB199 ions but this was to non-distinct, or multiple, sites of adsorption, unlike the Langmuir model which is to distinct localized adsorption sites.


where qe is the amount of adsorbed dye per unit which is the dosage of adsorbent (mg g1), qm adsorption capacity, b activity coefficient pertinent to mean adsorption energy and e Polanyi potential, which can be calculated through:   1þ1 e ¼ RTln (13) ce

Table 4 The effect of temperature on the removal efficiency. Temperature (8C)

15 25 35

Removal efficiency (%) RR



68.12 71.44 74.62

87.78 90.94 94.12

95.14 98.38 99.92

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Fig. 4. Plots for (a) ln KC vs. T1 and ln(1  u) vs. T1 for the adsorption of dyes onto PAn/g-Al2O3.

3.8. Effect of temperature on adsorption and thermodynamic parameters

lnK C ¼

Since most of the textile dye effluents are produced at relatively high temperatures, the temperature influence is an important controlling factor in the real applications of the proposed adsorptive dye removal process. The temperature has two major effects on the adsorption process. Increasing the temperature is known to increase the rate of diffusion of the adsorbate molecules across the external boundary layer and in the internal pores of the adsorbent particle, owing to the decrease in the viscosity of the solution. In addition, changing the temperature will change the equilibrium capacity of the adsorbent for a particular adsorbate. To study the effect of temperature on the removal efficiency, experiments were carried out from 158C to 358C at optimum conditions in 50 mL of dye solutions with initial concentration 100 mg L1. The percentage of adsorption was increased with the rise of temperature from 15 8C to 35 8C. The results are shown in Table 4 which revealed the endothermic nature of adsorption process. In order to specify what process will happen spontaneously, both energy and entropy attention must be taken into account in any adsorption process. For practical application of a process, the values of thermodynamic parameters are the actual indicators. The amount of dye (initial concentration: 100 mg L1) adsorbed at equilibrium at different temperatures (15, 25, and 35 8C), have been examined to obtain thermodynamic parameters for the adsorption system. Thermodynamic constants were calculated using the following equations [45]: KC ¼

Fe ð1  F e Þ






DG ¼ RTlnK c



where Kc, DH, DS, DG, R, and T are standard thermodynamic equilibrium constant, enthalpy change (J mol1), entropy change (J mol1), Gibbs free energy, universal gas constant (8.314 J mol1 K1), and temperature (K), respectively. The data in Fig. 4a shows a linear relation between ln KC versus T1 according to Eq. (16). The thermodynamic parameters for the adsorption of these three dyes in aqueous solutions onto PAn/g-Al2O3 nanocomposite are summarized at various temperatures in Table 5. The standard enthalpy change (DH) computed from the slope was assessed to be 11.775, 29.479, and152.404 kJ mol1 for RR-194, AB-62, and DB199, respectively which showed the increased supply of heat would lead to enhance the adsorption of dyes onto the PAn/gAl2O3. The positive values of DS indicated the increase randomness at solid solution interface during the adsorption of dyes on PAn/gAl2O3. The Gibbs free energy change (DG) values were found to be decreasingly negative with temperature which indicated the feasibility and spontaneity of the adsorption process of dyes onto the PAn/g-Al2O3. 3.9. Desorption of dye from the sorbent Reusability of an adsorbent is of crucial importance in industrial practice for dye removal from wastewater. Desorption of the adsorbed dye from the PAn/g-Al2O3 was studied using a batch system. In this study, the ability of NaOH to desorb dye uptake by

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Table 5 Thermodynamic parameters for dye adsorption. Dye


DH (kJ mol1)

11.775 29.479 152.404

DS (kJ Kmol1)

0.047 0.1185 0.551

DG (kJ mol1) 15 8C

25 8C

35 8C

(kJ mol

1.817 4.721 7.121

2.271 5.714 10.174

2.761 7.1 18.258

1.01 3.236 18.113

PAn/g-Al2O3 was investigated. The adsorbent was loaded with initial concentration of 50 mg L1of dye was placed in the desorption medium containing 50 mL of 0.2 M NaOH and the amount of dye desorbed in 10 h was measured. Table 6 clearly shows that PAn/g-Al2O3 could be used repeatedly without significantly loosing the adsorption capacity for these three dyes. The ability of NaOH at 0.2 M concentration to strip most of the adsorbed dye may be attributed to ion exchange. It has been postulated that the high concentration of OH ions at high pH is responsible for the displacement of adsorbed dye via ion exchange mechanism. After a sequence of three cycles, the recovery of dye the uptake capacity of PAn/g-Al2O3 had been decreased. The gradual reduction of dye uptake in three cycles of adsorption–


Ea 1

) 9.56  103 1.64  106 3.28  1029

Table 6 Reusing the PAn/g-Al2O3 nanocomposite after desorption. Dye


Removal efficiency (%) First time

Second time

Third time

71.16 90.52 97.83

68.31 86.85 94.26

63.47 81.36 90.14

desorption indicated that the binding sites on the surface of the adsorbent were either destroyed or morphologically altered. In order to further support the assertion that physical adsorption is the predominant mechanism, the values of activation

Fig. 5. The pathway leading to the synthesis of PAn/g-Al2O3 and adsorption of dye.

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energy (Ea) and sticking probability (S*) were estimated from the experimental data. They were calculated using a modified Arrhenius type equation related to surface coverage (u) as follows [46,47]: S ¼ ð1  uÞ eðEa =RTÞ

(18) *

The sticking probability, S , is a function of the adsorbate/ adsorbent system under investigation, its value lies in the range 0 < S* < 1 and is dependent on the temperature of the system. The parameter S* indicates the measure of the potential of an adsorbate to remain on the adsorbent indefinite. The surface coverage, u, can be calculated from the following equation:   1  Ce u¼ (19) Co The activation energy and sticking probability were estimated from a plot of ln(1  u) versus T1 (Fig. 4b). The activation energy, Ea, calculated from the slope of the plot was found to be 8.4, 26.9, and 150.59 kJ mol1 for adsorption of RR-194, AB-62, and DB-199 onto PAn/g-Al2O3, respectively. The positive values of Ea indicated the endothermic nature of the adsorption process. The sticking probability values were less than 1 (Table 5), which indicated that the probability of the dyes to stick on surface of PAn/g-Al2O3 was very high as S*  1, these values confirmed that the sorption process was physisorption. 3.10. Suggested mechanism According to the adsorption of dyes onto the surface of PAn/gAl2O3, different mechanisms may be involved such as ionic attraction between the cationic amino groups of protonated PAn/g-Al2O3 and anionic sulphonate groups of dissolved dye molecules. Woo and coworkers have suggested the conceivable mechanisms in the adsorption process of chitosan and acid dyes [48]. PAn has also the same NH2 functional groups as chitosan, so these mechanisms can also be offered for adsorption process of PAn/g-Al2O3 and dyes. In aqueous media, dyes are first dissolved and the sulphonate groups of dyes (D-SO3Na) are dissociated and converted to anionic dye ions. þ D-SO3 Na ! D-SO 3 þ Na


Also, the amino groups of PAn (R–NH2) were protonated in the presence of H+. R-NH2 þ H2 @ R-NHþ 3


Due to the electrostatic attraction between these two counter ions the adsorption process then proceeds,  R-NHþ 3 þ D-SO3 @ R-NH3    O3 SD


The pathway leading to the synthesis of PAn/g-Al2O3 and adsorption of dye is shown in Fig. 5. 4. Conclusions The PAn/g-Al2O3 nanocomposite showed considerable potential for the removal of dyes such as: RR-194, AB-62, and DB-199 from aqueous solutions. The optimum conditions of adsorption were found to be: pH 2 for all dyes, adsorbent dosage 0.06, 0.05, and 0.05 g, contact time of 20, 20, and 10 min for RR-194, AB-62, and DB-199, respectively. The results gained from the studies were well described by the theoretical Langmuir for RR-194 and AB-62 and Freundlich for DB-199. The kinetic data indicated that the adsorption process was controlled by pseudo-second-order model for all dyes. The results showed the endothermic nature of the adsorption. The negative DG values indicated thermodynamically

feasible and spontaneous nature of the adsorption. The positive value of DS revealed the increased randomness at the solid– solution interface during the fixation of ion on the active sites of sorbent. Desorption of dyes from PAn/g-Al2O3 nanocomposite has been studied using 0.2 M NaOH. Maximum desorption efficiency were 79, 86, 90% for RR-194, AB-62 and DB-199, respectively. After the desorption process, PAn/g-Al2O3 nanocomposite showed considerable removal efficiency for dyes adsorption and its reduction for all dyes was less than 10% in the third stage in comparison with the first. The results showed that PAn/g-Al2O3 nanocomposite could be used as a suitable adsorbent for textile wastewaters purification. Acknowledgement The authors (H. Javadian and M.T. Angaji) acknowledge the financial support provided by Islamic Azad University of Shahrood and University of Tehran. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.jiec.2013.12.095. References [1] C.S. Lu, C.C. Chen, F.D. Mai, H.K. Li, J. Hazard. Mater. 165 (1–3) (2009) 306–316. [2] N. Daneshvar, Principles of Water Quality Control, Publication of Tabriz University, 2004, pp. 34–47. [3] N. Daneshvar, A.R. Khataee, N.D. Jafarzadeh, J. Hazard, Materials B137 (2006) 1788–1795. [4] Sh. Song, Zh. He, J. Qiu, Xu.L. Chen, J. Sep. Purif. Technol. 55 (2007) 238–245. [5] B. Merzouk, B. Gourich, A. Sekki, K. Madani, C. Vial, M. Barkaoui, Chem. Eng. J. 149 (1–3) (2009) 207–214. [6] L.K. Wang, Y. Hung, H.H. Lo, C. Yapijakis, Handbook of Industrial and Hazardous. Wastes Treatment, second edition, Mercel Dekker, 2004, pp. 65–71. [7] P. Ji, J. Zhang, F. Chen, M. Anpo, Appl. Catal. B: Environ. 85 (3–4) (2009) 148–154. [8] Y.S. Mok, J.O. Jo, J.C. Whitehead, Chem. Eng. J. 142 (1) (2008) 56–64. [9] A.A. Atia, A.M. Donia, W.A. Al-Amrani, Chem. Eng. J. 150 (1) (2009) 55–62. [10] F. Olak, N. Atar, A. Olgun, Chem. Eng. J. 150 (1) (2009) 122–130. [11] M. Kobya, M. Bayramoglu, M. Eyvaz, J. Hazard. Mater. 148 (2007) 311–318. [12] N. Daneshvar, A. Oladegaragoze, N.D. Jafarzadeh, J. Hazard. Mater. B129 (2006) 116–122. [13] S. Song, Z. He, J. Qiu, X.L. Chen, J. Sep. Purif. Technol. 55 (2007) 238–245. [14] O.T. Can, M. Kobya, E. Demirbas, M. Bayramoglu, J. Chemosphere 62 (2006) 181– 187. [15] M.A. Sanroman, M. Pazos, M.T. Ricart, T. Cameselle, Chemosphere 57 (2004) 233– 239. [16] T.H. Kim, C. Park, E.B. Shin, S. Kim, Desalination 150 (2002) 165–175. [17] A.H. Essadki, M. Bennajah, B. Gourich, Ch. Vial, M. Azzi, M. Delmas, J. Chem. Eng. Process.V 47 (2008) 1211–1223. [18] S. Yildiz Yalcin, J. Hazard. Mater. 158 (2008) 194–200. [19] N. Daneshvar, H. Ashassi Sorkhabi, M.B. Kasiri, J. Hazard. Mater. B112 (2004) 55– 62. [20] I. Arslan-Alaton, I. Kabdas, D. Hanbaba, E. Kuybu, J. Hazard. Mater. 150 (2008) 166–173. [21] Mu. Naushad, Z.A. Al-Othman, M. Islam, Inter. J. Environ. Sci. Technol. 10 (2013) 567–578. [22] J. Huang, Pure. Appl. Chem. 78 (2006) 15–27. [23] M. Kulkarni, A. Viswanath, R. Aiyer, P. Khanna, J. Polym. Sci., Part B: Polym. Phys. 43 (2005) 2161–2169. [24] D.M. DeLongchamp, P.T. Hammond, Chem. Mater. 16 (2004) 4799–4805. [25] G.M. Spinks, V. Mottaghitalab, M. Bahrami-Samani, P.G. Whitten, G.G. Wallace, Adv. Mater. 18 (2006) 637–640. [26] X. Guo, J.P. Small, J.E. Klare, Y. Wang, M.S. Purewal, I.W. Tam, B.H. Hong, R. Caldwell, L. Huang, S. O’Brien, J. Yan, R. Breslow, S.J. Wind, J. Hone, P. Kim, C. Nuckolls, Science 311 (2006) 356–359. [27] K.S. Ryu, Y. Lee, K.S. Han, Y.J. Park, M.G. Kang, N.-G. Park, S.H. Chang, Solid State Ionics 175 (2004) 765–768. [28] C. Zhao, S. Xing, Y. Yu, W. Zhang, C. Wang, Microelectron. J. 38 (2007) 316–320. [29] I. Karatchevtseva, Z. Zhang, J. Hanna, V. Luca, Chem. Mater. 18 (20) (2006) 4908– 4916. [30] R. Ansari, Z. Mosayebzadeh, Iran. Polym. J. 19 (7) (2010) 541–551. [31] V.K. Konaganti, R. Kota, S. Patil, G. Madras, Chem. Eng. J. 158 (2010) 393–401. [32] S. Lagergren, Kung. Sven. Veten. Hand 24 (1898) 1–39. [33] Y.S. Ho, G. McKay, Process Biochem. 34 (1999) 451–465. [34] W.J. Morris, C.I. Weber, J. San. Eng. Div. ASCE 89 (1963) 31–59. [35] F.C. Wu, R.L. Tseng, R.S. Juang, Chem. Eng. J. 150 (2–3) (2009) 366–373.

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