surfactant: process optimization, kinetics and equilibrium.

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 137 (2015) 1126–1143

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Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy journal homepage: www.elsevier.com/locate/saa

Adsorption behavior of direct red 80 and congo red onto activated carbon/surfactant: Process optimization, kinetics and equilibrium Zhengjun Cheng a,b,c,⇑, Lei Zhang a,b,⇑, Xiao Guo a, Xiaohui Jiang c, Tian Li c a

State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu 610500, Sichuan, China School of Chemistry and Chemical Engineering, Southwest Petroleum University, Chengdu 610500, Sichuan, China c Chemical Synthesis and Pollution Control Key Laboratory of Sichuan Province, China West Normal University, Nanchong 637002, China b

h i g h l i g h t s

g r a p h i c a l a b s t r a c t

The four process variables of the

In the study, the process variables (such as the concentration of surfactant, temperature, and initial concentration of the dye) of the congo red and direct red 80 adsorptions onto AC/surfactant from aqueous solution were optimized by response surface methodology (RSM). The experimental data of the two systems could be well-fitted to second order polynomial models and the two models were also examined using the analysis of variance and t test statistics, respectively. Moreover, the validation set with four independent variables was designed to evaluate the predicted ability of the two models. The results indicated that the two selected quadratic models in predicting the adsorption capacities for the two dye systems were satisfying.

congo red and direct red 80 adsorptions onto AC/surfactant were optimized by RSM. Investigating the adsorption equilibrium of the two systems using four isotherm models. The adsorption kinetics for the two dyes was also discussed. Analyzing the effects of four process variables in adsorption capacity.

a r t i c l e

i n f o

Article history: Received 2 May 2014 Received in revised form 20 August 2014 Accepted 31 August 2014 Available online 23 September 2014 Keywords: Box–Behnken design Activated carbon/surfactant Congo red Direct red 80

a b s t r a c t Adsorptions of congo red and direct red 80 onto activated carbon/surfactant from aqueous solution were optimized. The Box–Behnken design (BBD) has been employed to analyze the effects of concentration of surfactant, temperature, pH, and initial concentration of the dye in the adsorption capacity. Their corresponding experimental data could be evaluated excellently by second order polynomial regression models and the two models were also examined based on the analysis of variance and t test statistics, respectively. The optimum conditions were obtained as follows: Cs = 34.10 lM, T = 50 °C, pH = 3.5, and CCR = 160 mg/L for the congo red system, and Cs = 34.10 lM, T = 50 °C, pH = 6.1, and CDR80 = 110 mg/L for the direct red 80 system. And in these conditions, the measured experimental maximum adsorption capacities for the congo red and direct red 80 removals were 769.48 mg/g and 519.90 mg/g, which were consistent with their corresponding predicted values, with small relative errors of 2.81% and 0.67%,

⇑ Corresponding authors at: State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu 610500, Sichuan, China. E-mail addresses: [email protected] (Z. Cheng), [email protected] (L. Zhang). http://dx.doi.org/10.1016/j.saa.2014.08.138 1386-1425/Ó 2014 Elsevier B.V. All rights reserved.

Z. Cheng et al. / Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 137 (2015) 1126–1143 Adsorption kinetics Isotherms

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respectively. The adsorption equilibrium and kinetics for the two dye adsorptions onto AC/DDAC were also investigated. The experimental data were fitted by four isotherm models, and Langmuir model presented the best fit. The kinetic studies indicated that the kinetic data followed the pseudo-second-order model. Ó 2014 Elsevier B.V. All rights reserved.

Introduction Since a variety of synthetic dyes are used extensively in the manufacture (such as textile, plastics, leather, cosmetics, pulp and paper, food, paints, pharmaceuticals, carpet, and inkjet printing) to color their products, large amount of effluents with dyes were discharged from the manufactures, which would result in a major environmental pollution problem because many dyes are toxic to some organisms. Azo dyes are the largest class of synthetic dyes because it accounts for 60–70% of the dyes total consumption in business applications [1]. Its expanded uses show that some of them and their reaction products have carcinogenic action, which indicate that it is necessary to remove the dyes from the industrial wastewater before the wastewater is disposed. However, the wastewater including azo dyes is very difficult to treat because they contain one or more azo groups with aromatic ring and sulfonate groups which induce that they are resistant and stabile at aerobic digestion and oxidizing agent conditions, respectively. At present, a number of techniques [2,3] have been employed to remove the dyes from the industrial wastewater, which include coagulation, filtration, ion exchange, biological treatment, advanced oxidation processes, electrolysis, activated sludge, adsorption, and solvent extraction. Among these techniques, adsorption is regarded as a simple, impactful and economical method for the dyes treatment in the wastewater [2]. However, activated carbon (AC) is considered the most promising and effective adsorbent for the dyes removals from the wastewater because it has large surface area and high adsorption capacity for organic compounds removals [4], but the uses of AC are limited usually due to its high manufacturing cost. In order to solve the difficult question, many research groups have prepared more efficient and cheaper AC for the removals of organic compounds from the wastewater, such as eggshells[3], walnut shells [4], coir pith [5], cashew nut shell [6], wood sawdust [7], banana empty fruit bunch (BEFB) and delonix regia fruit pod (DRFP) [8], pomelo skin [9], Zizania caduciflora [10], pumpkin seed hull [11], phoenix canariensis palm frond mulch [12], Myrtus communis and pomegranate [13], rice husk [14], tea industry wastes [15], finger citron residue [16], and peanut sticks [17]. In addition, some researchers have developed alternative AC to improve its adsorption capacity for the dyes. Such as, Ghaedi et al. [18] have investigated the removal of congo red from aqueous solution using three new adsorbents (Pd NPs–AC, Ag NPs–AC, and ZnO–NRs–AC) and compared their removal efficiency. M-Cell/Fe3O4/ACCs (magnetic cellulose/Fe3O4/activated carbon composites) were prepared for removing congo red, suggesting that the adsorbent has several advantages (such as high efficiency, low cost and convenient separation) [19]. Zeolite–AC [20] was used for the acid orange 7 treatment in aqueous solution. The study of Auta and Hameed [21] indicated that WTAC-CCB composite was a promising adsorbent for the treatments of methylene blue and acid blue 29 in the wastewater. Later, a new efficient adsorbent [22], tin sulfide nanoparticle loaded on AC was also prepared, and it was used for the reactive orange 12 adsorption. And afterward, their groups [23,24] synthesized two novel adsorbents, i.e. zinc oxide nanoparticle loaded on activated carbon (ZnO–NP–AC) and Nickel sulfide nanoparticle-loaded activated carbon (NiS–NP–AC). The results

indicated that ZnO–NP–AC has high adsorption capacity (322.58 mg g1) for removing malachite green (MG) from aqueous solution in short time (15 min), and NiS–NP–AC can absorb simultaneously and rapidly methylene blue (MB, 17.8 mg/L) and Safranin-O (SO, 5 mg/L) from wastewater in 5.46 min with 99.9% removal efficiency for the two dyes. Recently, Nabil et al. [25] designed activated carbon-immobilized-cationic surfactant (AC-CS), which was employed to remove reactive black 5 from textile industrial wastewater, and the adsorption capacity of the dye by AC-CS was higher in strongly acidic and basic solutions than that in weak acid and base solutions. Later, AC/a-Fe2O3 nanocomposite was synthesized based on iron (II) gluconate for the adsorption of acid yellow 17 from water [26]. As stated above, the adsorptions of dyes onto AC are commonly studied based on traditional methods, but the congo red and direct red 80 adsorptions by AC/surfactant are not investigated, and a Box–Behnken design is rarely used for the congo red and direct red 80 systems. Then in the study, the removals of two dyes by AC/surfactant have been investigated in batch systems. The main effects and interactive effects of process variables on adsorption capacities of the two dyes were analyzed by Box–Behnken design, respectively. Moreover, the maximum response values of two dyes and their corresponding operation parameters have been obtained using the numerical optimization function based on the D-optimality index in the Minitab 15.0 software. In addition, the adsorption isotherms and kinetics for two dyes by AC/surfactant were also discussed. Materials and methods Chemicals Direct red 80 (AR grade, Scheme 1) acquired from Alfa Aesar Tianjin Co., Ltd. (Tianjin, China), and congo red (AR grade, Scheme 1) acquired from Aladdin Chemistry Co., Ltd. (Shanghai, China), were used without further purification. They were both dissolved in the double distilled water to form solutions of 200 and 400 mg L1, respectively. And their pH was regulated by HCl of 0.2 mol L1 or NaOH of 0.2 mol L1 solution. Activated carbon (AC, which is prepared from wood sawdust; particle size: more than 150 mesh size; specific surface-area: 800–900 m2/g) were purchased from Beijing kecheng guanghua new technology Co., Ltd. (Beijing, China); Bentonit and activated clay were purchased from Gongyi city yuanheng water purification materials Co., Ltd. (Henan, China); Spirulina powder was purchased from WUDI LV QI Bioengineering Co., Ltd. (Shangdong, China); Chitosan (extracted from snow crab shell, degree of deacetylaion: 95.0%, 120 mesh size) was purchased from Jinhu Crust Product Co., Ltd. (Qingdao, China). Octadecyl Trimethyl Ammonium Chloride (OTAC, 98% purity), Dioctadecyl Dimethyl Ammonium Chloride (DDAC, 97% purity), and Benzyl Hexadecyl Dimethyl Ammonium Chloride (BHDAC, 95% purity) were purchased from Aladdin Chemistry Co., Ltd. (Shanghai, China); Dodecyl Trimethyl Ammonium Chloride (DTAC, 99% purity) was purchased from Shanghai CIVI chemical technology Co., Ltd. (Shanghai, China). Other materials were of analytical reagent grade, and doubly distilled water was used throughout the experiment.

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Z. Cheng et al. / Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 137 (2015) 1126–1143

Scheme 1. Molecular structures of congo red (a) and direct red 80 (b).

Characterization of adsorbent

Adsorption kinetics

FT-IR spectra of the adsorbent surface before and after the adsorptions of direct red 80 and congo red were carried out using a Nicolet-6700 FT-IR spectrometer (Nicolet, USA) based on potassium bromide sheets. And their corresponding surface property was also analyzed based on SEM (ZEISS EVO MA 10/LS 10, Germany), XRD (Ultima, IV, Japan), and BET (Quantachrome ASIQ-C, USA) methods. Zero point charge (pHzpc) of AC was determined by the solid addition method [27]. A series of mixture solutions (0.1 g AC and 100 ml 0.01 mol L1 NaCl) in 150 ml conical flask were prepared. The initial pH (pHi) of the solutions was adjusted in the range of 2–11 by adding minimum amounts of 0.1 mol L1 HCl or 0.1 mol L1 NaOH, which were determined using the PHS-3C model pH-meter (Jiangsu, China). Batches were agitated in a rotary shaker with 200 rpm for 24 h at 298.15 K. The suspensions were filtered and final pH (pHf) of the filtrates was measured at equilibrium. The pHzpc value of AC was calculated from the plot of pHf versus pHi.

The adsorption kinetics was carried on preliminary selected composite adsorbent, which was conducted by adding 20 mg of AC and a certain volume of DDAC into 100 mL of the direct red 80 or congo red solution of different known concentrations (70 and 110 mg/L for the direct red 80 system, or 100 and 160 mg/L for the congo red system) and then shaking (120 rpm) for 120 or 150 min at 308.15 K. The concentrations of two dyes in the solution were determined at known time intervals. Their amounts adsorbed at time t, Qt (mg/g) is calculated as follows:

Adsorption experiments The batch adsorption tests have been carried out in the laboratory by contacting a certain volume of dyes aqueous solution (pH = 6.5 for the direct red 80, and pH = 4.0 for the congo red) with different adsorbents (such as AC, spirulina powder, bentonit, activated clay, and chitosan) at 120 rpm in a shaker and 308.15 K for 120 min (It is ascertained by the preliminary kinetic investigations) to ensure apparent equilibrium. The suspensions were filtered when the equilibrium was obtained, and their complete UV–vis spectra scan of supernatant solutions was determined using a UV-3600 spectrophotometer (Shimadzu, Japan) to avoid the error of fixed point determination. And their adsorption ratios (percent) are calculated by the following equation:

C0 Ce 100 Adsorption ð%Þ ¼ C0

ð1Þ

where C0 and Ce (mg/L) are the liquid-phase concentrations of dye at initial and equilibrium, respectively. To investigate the adsorption capacity of composite adsorbent (AC/different types of surfactants) for the two dye systems, a certain volume of direct red 80 (pH 6.5) and congo red (pH 4.0) solutions with the initial concentrations of 200 mg/L and 400 mg/L were prepared in a series of 150 mL Erlenmeyer flasks. 20 mg of AC and a certain volume of surfactant (such as OTAC, DDAC, BHDAC, or DTAC, and its concentration is fixed at 34.10 lM by adjusting the volume of surfactant added) were dripped into each flask covered with rubber plugs, respectively. Then the flasks were placed in an isothermal water bath shaker at 308.15 K with rotation speed of 120 rpm, and the aqueous samples were taken at present time interval, respectively.

Qt ¼

ðC 0 C t ÞV m

ð2Þ

where Ct (mg/L) denotes the liquid-phase concentration of dye at any time t (min), V is the volume of solution, m is the mass of adsorbent used, respectively. The pseudo-first-order, pseudo-secondorder, and Elovich kinetic models were applied to simulate the uptake of two dyes onto AC/DDAC with time t, respectively. And their linear models are given as follows [28,29]:

lnðQ e Q t Þ ¼ lnðQ e Þ k1 t

ð3Þ

t 1 1 ¼ tþ Qt Qe k2 Q 2e

ð4Þ

Q t ¼ ð1=bÞlnðabÞ þ ð1=bÞ ln t

ð5Þ

1

where Qe (mg g ) is the equilibrium adsorption capacity; k1 (min1) is the rate constant of the pseudo-first-order adsorption; k2 (g mg1 min1) is the rate constant of the pseudo-second-order adsorption; a (mg g1 min1) is the initial adsorption rate; and the parameter b (g mg1) is related to the extent of surface coverage and activation energy. Adsorption equilibriums Batch equilibrium experiments have been performed for the direct red 80 and congo red adsorptions by AC/DDAC at different temperatures (293.15, 308.15, and 323.15 K). The same procedure was followed, but their initial concentrations altered from 50 to 110 mg/L (with equal interval, 12 mg/L for the direct red 80) and from 80 to 160 mg/L (with equal interval, 16 mg/L for the congo red). Their amounts adsorbed at equilibrium (Qe) are calculated by Eq. (6):

Qe ¼

ðC 0 C e ÞV W

ð6Þ

where C0, Ce, V and W are the same as in Eqs. (1) and (2). Four theoretical models (such as Langmuir, Freundlich, Temkin, and Dubinin–Radushkevich isotherms equations) are used for describing the adsorption behaviors of two dyes onto AC/DDAC. Their linear functions are expressed as:

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Ce Ce 1 ¼ þ Q e Q m K LQ m 1 Freundlich model : ln Q e ¼ ln K F þ ln C e n RT RT Temkin model : Q e ¼ ln K T þ ln C e bT bT

Langmuir model :

ð7Þ ð8Þ ð9Þ

The essential characteristics of Langmiur isotherm can be expressed by a dimensionless equilibrium parameter, RL, which are defined as follows [30]:

RL ¼ 1=ð1 þ K L C 0 Þ

ð10Þ 2

1

where C0 (mg L ) is the initial concentration of dye, and KL (L mg1) is the Langmuir constant. The type of isotherm can be judged by the values of RL. That is to say, the adsorption equilibrium is irreversible (RL = 0), favorable (0 < RL < 1), linear (RL = 1), or unfavorable (RL > 1) [30]. In addition, Dubinin–Radushkevich model was applied to understand further the adsorption mechanisms of two adsorption reactions because it can not only evaluate the porosity apparent free energy and the adsorption characteristics, but also character the adsorption on both homogeneous and heterogeneous surfaces. Its linear form is given [31]:

lnðQ e Þ ¼ lnðQ m Þ be2

ð11Þ

where e is the Polanyi potential and equals to RTln(1 + 1/Ce); b (mmol2 J2) is a constant related to the mean adsorption energy (E) by following equation:

1 E ¼ pffiffiffiffiffiffi 2b

ð12Þ

The magnitude of E can be applied to ascertain the type of adsorption mechanism. That is to say, the E value is less than 8 kJ mol1, between 8 and 16 kJ mol1, or the range of 20–40 kJ mol1, indicating that the adsorption process follows physical adsorption, ionexchange, or chemisorption [32]. Box–Behnken design (BBD) The operational variables of the adsorption process were optimized based on Box–Behnken design (BBD) that can reduce experimentation time, overall cost, and variability with improved reaction output. A BBD (4-factor and 3-level) was employed to not only investigate the individual and interactive effects of the process variables, but also obtain the optimum operational variables for the congo red and direct red 80 systems, respectively. And the preliminary range of process variables was ascertained by single factor test, respectively. Their ranges and levels were listed in Table 1. The adsorption capacity of dye (y) is selected as a response for the combination of independent variables, which is fitted by a second order polynomial model:

y ¼ b0 þ

n X

bi xi þ

i¼1

n n1 X n X X bii x2i þ bij xi xj þ e i¼1

ð13Þ

i¼1 j¼1

Table 1 Process variable, coded values and limits of Box–Behneken design (BBD) for the congo red and direct red 80 systems. Variable

Cs (x1) T (x2) pH (x3) C (x4)

where y is the predicted response value associated with each factor level combination; b0 is constant; and bi, bii, and bij are linear effect, quadratic effect, and 2-way linear by linear interaction effect, respectively; xi and xj are the coded values of independent variables; and e is the residual error. Analysis of variance (ANOVA) was carried out to identify the accuracy and reliability of developed model, the significance of independent variables and their interactions. In addition, nonlinear analysis (v2) is a useful method, which can compare the experimental and model predicted data. And it is obtained from Eq. (14):

Unit

lM °C – (mg L1)

Congo red

Direct red 80

Limit

Limit

Chi ¼

X ðQ meas Q pred Þ2

where Qmeas (mg/g) and Qpred (mg/g) are the adsorption capacities of direct red 80 and congo red onto AC/DDAC by experiment determined and model predicted, respectively. Model validation and optimization The model validation was performed through eight different combinations of four independent variables based on the Taguchi design, and their response variable values were calculated by two models, respectively. Batch experiments of the validation set defined were done to determine the response variable values under fixed conditions of all the process variables. Comparing the R2 values of the model predicted and experimental verify the validity and accuracy of two models. In addition, the optimization of direct red 80 and congo red removals was done to select the levels of the process variables which resulted in a maximum response value by the D-optimality index in the Minitab 15.0 software. Results and discussion Selection of adsorbent for the direct red 80 and congo red adsorptions Five adsorbents (Table 2) were selected to investigate their adsorption capacities for the direct red 80 and congo red systems. As could be seen from Table 2, AC has the biggest adsorption ability (195.38 and 361.18 mg/g) and adsorption efficiency (35.52% and 45.15%) for the direct red 80 and congo red systems, respectively, possibly because it has bigger surface area than other adsorbents. Therefore, AC was selected as a suitable adsorbent for adsorbing the direct red 80 and congo red from aqueous solution. In order to enhance the adsorption capacities of direct red 80 and congo red onto AC, compound adsorbent, i.e. different types of surfactants and AC in a one-step process have been investigated for the adsorptions of two dyes (Fig. 1). It could be seen from Fig. 1, AC/DDAC showed higher adsorption efficiency for the two dyes than that of other three surfactants, and the adsorption efficiency for the direct red 80 onto AC/surfactant followed the order DDAC > OTAC > DTAC > BHDAC. However, for the congo red adsorption, its order is DDAC > BHDAC > DTAC > OTAC. Moreover, the adsorption efficiency of compound adsorbent (AC/DDAC) for the direct red 80 and congo red increased 87.05% and 88.59%

Table 2 Adsorption parameters for the direct red 80 and congo red onto different adsorbents. Name

0

+

0

+

17.05 20 3.0 80

25.58 35 7.4 120

34.10 50 11.8 160

17.05 20 3.6 50

25.58 35 7.8 80

34.10 50 12 110

ð14Þ

Q pred

AC Bentonit Activated clay Spirulina powder Chitosan

Direct red 80

Congo red

Qe (mg/g)

Adsorption (%)

Qe (mg/g)

Adsorption (%)

195.38 35.40 22.56 57.22 64.44

35.52 6.44 4.10 10.40 11.72

361.18 201.14 174.81 82.52 116.21

45.15 25.14 21.85 10.32 14.53

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Fig. 1. The effects of different surfactants for the direct red 80 (A) and congo red (B) adsorptions at different time (initial concentration of the direct red 80 = 110 mg/L, adsorbent dose = 20 mg, the concentration of surfactant = 34.10 lM, pH = 6.5, and T = 35 °C for the direct red 80 system; initial concentration of the congo red = 160 mg/L, adsorbent dose = 20 mg, the concentration of surfactant = 34.10 lM, pH = 4.0, and T = 35 °C for the congo red system).

Table 3 Adsorption parameters for the direct red 80 (CDR80 = 110 mg/L, pH = 6.5, T = 35 °C) and congo red (CCR = 160 mg/L, pH = 4.0, T = 35 °C) onto only AC and AC/different types of surfactants. Name

Only AC AC/OTAC AC/DTAC AC/BHDAC AC/DDAC

Direct red 80

Congo red

Qe (mg/g)

Adsorption (%)

Qe (mg/g)

Adsorption (%)

195.38 420.83 171.63 121.25 478.75

35.52 76.51 31.21 22.04 87.05

361.18 156.48 372.79 463.91 708.75

45.15 19.56 46.60 57.99 88.59

comparing with those of only AC for the direct red 80 (35.52%) and congo red (45.15%) (Table 3). Therefore, AC/DDAC was selected as a compound adsorbent for the two dye adsorptions in the study. Adsorption kinetics of the direct red 80 and congo red Fig. 2 showed the changes of adsorption capacity with time at different initial concentrations of the two dyes. It could be seen from Fig. 2, the adsorption capacity of direct red 80 increased quickly in the first 45 min and then increased slowly until the

Fig. 2. The adsorption capacities of direct red 80 (A) and congo red (B) onto AC/ DDAC versus time at different initial concentrations of the dyes (AC dose = 20 mg, the concentration of DDAC = 34.10 lM, pH = 6.5, and T = 35°Cfor the direct red 80 system; AC dose = 20 mg, the concentration of DDAC = 34.10 lM, pH = 3.0, and T = 35 °C for the congo red system), respectively.

equilibrium was attained at 90 min. However, for the congo red adsorption, its adsorption rate rose rapidly in the first 20 min and then rose slowly until the equilibrium was reached at 100 min. The adsorption kinetics data for the two systems were analyzed by the pseudo-first-order, pseudo-second-order and Elovich models, which were shown in Fig. 1S (see support information), and the relevant parameters were calculated and summarized in Table 4. It could be seen from Table 4, the R2 values obtained for the pseudo-first-order model did not show a consistent trend especially at low initial concentrations of the two dyes, and the pseudofirst-order kinetic model predicted significantly lower values (Qe,fit) than their corresponding experimental values (Qe,exp), which indicated the inapplicability of this model for the adsorptions of direct red 80 and congo red onto AC/DDAC. From Fig. 1S, we found that the experimental data were fitted better by the pseudo-second-order model than that by other two models because their correlation coefficient values were very high (R2 > 0.993, Table 4) and their fitted values Qe,fit by Eq. (4) have small deviations with the experimental data, suggesting that the two adsorption reactions could be described well based on the pseudo-second-order kinetic model. Ardejani et al. [33], Attallah et al. [34], and Dawood and Sen [35] reported similar results with the direct red 80 adsorption onto almond shells, and congo red adsorption onto metal hydroxides sludge (MHS) and raw pine and acid-treated pine cone powder, respectively. It could be

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Z. Cheng et al. / Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 137 (2015) 1126–1143 Table 4 Kinetic parameters of three models at two concentration levels. Model

Parameter

Direct red 80 C0 (mg L1) 70

110

100

160

Pseudo first order

Qe,fit (mg g1) k1 (min1) R2

78.81 0.0598 0.9383

304.51 0.0553 0.9864

34.23 0.0376 0.8497

87.92 0.0274 0.9671

Pseudo second order

Qe,fit (mg g1) Qe,exp (mg g1) k2 (g (mg min)1) R2

344.83 340.21 0.0023 0.9997

497.51 478.75 0.0004 0.9932

473.93 477.41 0.0054 0.9997

714.29 708.45 0.0017 0.9996

Elovich

a (mg (g min)1)

21503.6 0.0302 0.9595

1084.7 0.0151 0.9747

9.55E+35 0.1820 0.8250

6.59E+13 0.0478 0.9855

b (g mg1) R2

Congo red C0 (mg L1)

observed from Table 4 that the k2 values for two systems decreased with increasing their initial concentrations. The reason for this phenomenon may be attributed to the lower competition for the surface active sites of AC at lower dye concentrations. In contrast, at higher dye concentrations, the competition for its adsorption sites is high; therefore lower adsorption rates would be obtained. The half-adsorption time, t½, denotes the time required for adsorbent (AC/DDAC) to uptake half of the amount adsorbed dye (direct red 80 or congo red) at equilibrium, which is often considered as a measure of adsorption rate. Its relationship for the pseudo-second-order model is described as [35]:

t 1=2 ¼

1 k2 Q e

ð15Þ

For the direct red 80 and congo red adsorptions onto AC/DDAC, their t½ values were 1.28 and 4.93 min, and 0.39 and 0.83 min for different initial concentrations 70 and 110 mg/L, and 100 and 160 mg/L, respectively. In addition, the experimental data for the two systems were also analyzed by Elovich equation. The results indicated that the Elovich equation may be used for predicting the adsorption kinetics of direct red 80 and congo red at their high initial concentrations by AC/DDAC probably because AC possesses heterogeneous surface active sites. Adsorption mechanism As suggested above, the adsorption kinetics data for the direct red 80 and congo red systems could be fitted well based on the pseudo-second-order model, but the diffusion mechanism of the two adsorption reactions was blurry. To explore the adsorption mechanism, particle and liquid film diffusion models were used for the two adsorption systems. The particle (Eq. (16)) and liquid film diffusion (Eq. (17)) equations are given as follows [36]:

t¼

i br0 Q h 3 3ð1 FÞ2=3 2F 6Dc0

t¼

br0 Q F 3c0 kf

2

ð16Þ

Fig. 3. The liquid film (a) and particle diffusion (b) models for the adsorptions of direct red 80 (110 mg/L) and congo red (160 mg/L) onto AC/DDAC at 308.15 K.

2

ð17Þ

where b is the chemical measurement constant (8.315); r0 (cm) is the particle diameter of AC; Q (mg/g) is the adsorption capacity of AC/DDAC for the direct red 80 or congo red; D (cm2/s) is the diffusion coefficient of particles; c0 (mg/L) is the concentration of dye; kf (cm/s) is the liquid film mass transfer coefficient; and F = Qt/Qe. The plots of F versus t and [3–3(1 F)2/3 2F] versus t for the direct red 80 and congo red systems were shown in Fig. 3a and b. If the plots of Fig. 3a are linear, then the slowest step in the

adsorption process is governed by a film diffusion mechanism; if the plots of Fig. 3b are linear, then the slowest step in the adsorption process is governed by a particle diffusion mechanism. It could be seen from Fig. 3, the plots of Fig. 3b for the direct red 80 and congo red adsorptions onto AC/DDAC have slightly more excellent linearity than those of Fig. 3a, indicating that we could not confirm the particle diffusion was the rate-controlling step in the adsorptions of the direct red 80 and congo red by AC/DDAC. To understand better the diffusion mechanism of the two systems,

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their adsorption kinetics data were further analyzed by the Weber–Morris intraparticle diffusion model, which is express as follows [37]:

Q t ¼ kdi t 0:5 þ B

ð18Þ 1

0.5

where B is the intercept and kdi (mg g min ) is the intraparticle diffusion rate constant. The kdi values for the two systems can be evaluated from the slope of the linear plot of Qt versus t0.5 (Fig. 2S, see support information). It could be observed from Fig. 2S, the plots of Qt versus t0.5 were not linear in the whole time range, but they could be separated into two linear regions, suggesting the multistage adsorptions should be happened for the two adsorption processes. The first linear portion of the plots (Fig. 2S) represented external mass transfer, i.e. the dye molecules could be transported to the external surface of AC by the film diffusion. The second linear portion of the plots denoted intraparticle diffusion, i.e. the dye molecules entered the interior of AC. The stage of gradual adsorption rate was controlled based on the intraparticle diffusion, and then when the adsorption reactions were slowly close to equilibrium, their intraparticle diffusion rates started to slow and become stagnant because all the active sites of AC were occupied by the dye molecules. These steps indicated that both external mass transfer and intraparticle diffusion might occur simultaneously. At the same time, the experimental data of the two systems could be the best fitted by the pseudo-second-order model, reconfirming that two or more steps were involved in the two adsorption processes. However, the linear plots at each concentration did not pass through the origin (Table 5), which indicated that the intraparticle diffusion was not the only sole rate-controlling step for the adsorptions of direct red 80 and congo red and the external mass transfer was also significant in the rate-controlling step due to the large intercepts of the second linear portion of the plots (Table 5). Ahmad and Rahman [38] reported similar trends for Remazol Brilliant Orange 3R adsorptions by coffee husk-based activated carbon. In addition, the kdi values of the direct red 80 and congo red increased with increasing their initial concentrations (Table 5), indicating that the increased driving force at high initial concentrations of the dye could enhance the intraparticle diffusion of the two dyes onto AC/DDAC. The discussion above makes it clear that both intraparticle and external mass transfer processes play an important role in the adsorptions of the two dyes. However, it is not clear as to which one exerted a greater influence on the adsorption rates of the two dyes by AC/DDAC. Therefore Boyds model was employed and it is calculated as follows:

F ¼1

6

p2

expðBtÞ

ð19Þ

where Bt is a mathematical function of F (F = Qt/Qe). Eq. (19) can be represented as:

Bt ¼ 0:4977 lnð1 FÞ

ð20Þ

The plots of Bt versus t for the direct red 80 and congo red systems were shown in Fig. 4. If the plots are linear and pass through the origin, then the slowest step in the adsorption process is governed by

Fig. 4. Boyd kinetic model for the adsorptions of direct red 80 and congo red onto AC/DDAC at different initial concentrations of the two dyes (pH = 6.1 for the direct red 80 system; pH = 3.5 for the congo red system).

the intraparticle diffusion mechanism; otherwise it is governed based on the film diffusion. The plots for the two systems (Fig. 4) were not only nonlinear, but also they did not pass through the origin, indicating that the film diffusion controlled the adsorption rates of the two adsorption reactions. The similar results have been reported by Ghaedi et al. [37]. Adsorption isotherms for the direct red 80 and congo red systems Adsorption isotherm studies are important to describe adsorption behavior between liquid and solid phases at equilibrium. In the study, Langmuir, Freundlich, Temkin isotherms, and Dubinin– Radushkevich isotherm models were used for the direct red 80 and congo red adsorptions onto AC/DDAC. In order to find out a better adsorption isotherm model for the two systems, the isotherm models were compared by their correlation coefficients (R), which was helpful to optimize the adsorption process design for the direct red 80 and congo red systems. The adsorption isotherms of two dyes onto AC/DDAC were investigated at three temperatures (293.15, 308.15, and 323.15 K) as shown in Figs. 5 and 6. The Langmuir and Freundlich isotherms are the most commonly used models for describing the adsorption isotherms. The Langmuir adsorption model is based on the assumption that adsorbate molecules occur on a homogenous surface with a finite number of adsorption sites, by monolayer adsorption without mutual interactions between the adsorbed molecules. The Freundlich model assumes that the dye molecules are adsorbed on the heterogeneous surfaces of adsorbate, which is characterized based on the adsorption sites at different energies. The plots of lnQe versus lnCe were given in Figs. 5b and 6b for the direct red 80 and congo red systems and their corresponding model parameters were calculated and listed in Table 6. As could be seen from Table 6, the values of KF increased with rising the temperature, indicating that the two adsorption reactions were endothermic. The n value is an indication of the favorability of adsorption, and its values obtained for the two systems were

Table 5 Intraparticle diffusion model parameters at two concentration levels for the direct red 80 and congo red systems. System

C0 (mg L1)

kd1 (mg (g min0.5)1)

kd2 (mg (g min0.5)1)

B1

B2

R1

R2

Direct red 80

70 110

30.05 43.71

1.50 12.35

189.40 173.44

325.95 369.34

0.9726 0.9869

0.9882 0.9827

Congo red

100 160

3.18 24.03

5.87 8.64

445.95 580.28

429.14 622.38

0.9959 0.9931

0.9792 0.9971


1133

Fig. 5. Adsorption isotherms of the direct red 80 onto AC/DDAC using Langmuir (a), Freundlich (b), Temkin (c), and Dubinin–Radushkevich (d) models at different temperatures (pH = 6.5, t = 90 min, agitation speed, 120 rpm).

greater than 1 and less than 10, which suggested that the adsorptions of two dyes by AC/DDAC were favorable [39]. The Temkin isotherm assumes that the adsorption free energy is a function of the surface coverage, at the same time; it takes into account interaction between adsorbent and adsorbate. Their corresponding parameters could be calculated from the slope and intercept of a linear plot of Qe versus ln Ce (Figs. 5c and 6c) and were listed in Table 6. If the bonding energy is less than 40 kJ mol1, the adsorption reaction is dominated by the physical adsorption, and the ion-exchange mechanism is reported due to its bonding energy in the range of 8–16 kJ mol1 [40]. In the study, their corresponding values of bT (Table 6) indicated that the chemical adsorption were involved in the two adsorption reactions. The parameters of three isotherm models and their R values were summarized in Table 6. As shown in Table 6, the experimental data could be fitted better at different temperatures (R > 0.995) by the Langmuir isotherm model than those by the Freundlich and Temkin models. Our results showed that the adsorptions of direct red 80 and congo red onto AC/DDAC were favorable due to their RL values in the range of 0–1 (Table 6). The results agreed with the works reported by previous researchers for the adsorptions of pollutants (such as heavy metal ions, phenol, safaranin O, dyes, etc.) onto AC or modified AC [15,20,41–45]. For the direct red 80 and congo red adsorptions, their monolayer adsorption capacities increased (from 274.73 to 526.32 mg g1 for the direct red 80, and from 666.67 to 769.23 mg g1 for the congo red) with increase in the temperature (from 293.15 to 323.15 K), reconfirming that the two adsorption processes are endothermic reaction. The equilibrium data were also analyzed by the Dubinin– Radushkevich isotherm model (Figs. 5d and 6d). The fits were not as good as those of the Langmuir isotherm, but their E values

can give information about the adsorption mechanism of the two reactions. As shown in Table 6, the values of E were 13.36, 12.31, and 13.36 kJ mol1 for the congo red, 13.13, 12.91, and 12.70 kJ mol1 for the direct red 80 at 293.15, 308.15, and 323.15 K, respectively, which suggested that the two adsorption processes were governed by the ion exchange mechanism. In addition, we have compared adsorption capacities of the two dyes based on other adsorbents (Table 7). It could be seen from Table 7, the adsorption capacity of the direct red 80 onto AC/DDAC was higher than those of the direct red 80 by other adsorbents reported except for poly (amidoamine-co-acrylic acid) copolymer (PAC) and Poly (propylene imine) (PPI) dendrimer (PPI dendrimer). However, the adsorption capacity of the congo red onto AC/DDAC were higher than those of most other adsorbents and lower than those of Pr(OH)3 nanowires, porous hierarchical MgO, and hierarchical hollow structure c-Al2O3. Therefore, the method would be worth considering for the removal of congo red from printing and dyeing sewage, particularly for the removal of direct red 80. Optimization of congo red and direct red 80 adsorptions process variables Box–Behnken design and regression model Response surface methodology (RSM) is more advantageous than the traditional single parameter optimization because it can save time, space and raw material. In experimental design, a Box–Behnken design (BBD) is a type of RSM. In the study, the BBD is employed to optimize the important operating parameters (such as the concentration of surfactant, temperature, pH, and initial concentration of the dye) for the congo red and direct red 80

1134


Fig. 6. Adsorption isotherms of the congo red onto AC/DDAC using Langmuir (a), Freundlich (b), Temkin (c), and Dubinin–Radushkevich (d) models at different temperatures (pH = 4.0, t = 100 min, agitation speed, 120 rpm).

Table 6 Isotherm parameters for the congo red and direct red 80 onto AC/DDAC. Model

Parameter

Congo red T (K)

Direct red 80 T (K)

293.15

308.15

323.15

293.15

308.15

323.15

Langmuir

Qmax (mg g1) KL (L mg1) RL R

666.67 0.28 0.0427–0.0218 0.9987

714.29 0.57 0.0215–0.0108 0.9988

769.23 0.94 0.0131–0.0066 0.9990

274.73 0.30 0.0625–0.0294 0.9970

492.61 1.06 0.0185–0.0085 0.9994

526.32 0.94 0.0002–0.0001 0.9959

Freundlich

KF (mg g1) n R

280.62 4.17 0.9613

369.08 4.76 0.9940

427.19 4.55 0.9885

165.83 9.09 0.9258

278.67 4.76 0.9351

282.11 4.17 0.9293

Temkin

KT (L mg1) bT (kJ mol1) R

6.37 0.021 0.9677

23.83 0.023 0.9953

35.00 0.022 0.9891

254.70 0.089 0.9244

43.88 0.035 0.9605

23.34 0.030 0.9529

Dubinin–Radushkevich

Qm (mmol g1) b (mmol2 J2) E (kJ mol1) R

1.194 0.0028 13.36 0.9806

1.284 0.0033 12.31 0.9970

1.451 0.0028 13.36 0.9885

0.418 0.0029 13.13 0.9290

0.928 0.0030 12.91 0.9450

1.046 0.0031 12.70 0.9275

removals by AC/DDAC. The codified values of four important factors (x1, x2, x3, and x4) together with their corresponding response values were listed in Table 8. Runs 16, 22 and 27 at the center point were applied to calculate the pure error and the variance. The regression coefficient, sum of squares, T-value, and PC values were shown in Table 9. The regression coefficient of model was calculated based on dividing the net effects by two. The T-value was obtained based on dividing the regression coefficient by standard error. By substituting the coefficients in Eq. (13) with their values from Table 9, the two best fitted equations in terms

of coded factors for the congo red (Eq. (21)) and direct red 80 (Eq. (22)) adsorptions were described as follows:

y ðmg=gÞ ¼ 537:450 þ 49:659 x1 þ 47:290 x2 19:232 x3 þ 114:405 x4 11:952 x21 22:676 x22 25:594 x23 22:310 x24 14:933 x1 x2 4:268 x1 x3 þ 42:034 x1 x4 2:716 x2 x3 þ 30:253 x2 x4 19:325 x3 x4

ð21Þ

1135

Z. Cheng et al. / Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 137 (2015) 1126–1143 Table 7 Comparison of the maximum adsorption capacities for the direct red 80 and congo red systems using different adsorbents. Direct red 80

Congo red 1

Adsorbent

Qe (mg g

SA/n-TiO2 Polyurethane foam (PUF) Orange peel Egg shell membrane Soy meal hull Mixture almond shells PAC Canola Hull Mentha pulegium SF-CNT PPI dendrimer AC/DDAC

130 4.50 21.05, 21.052 161.29 178.57 22.422 3448 8.7032 52.356 120.48 33333 526.32

)

Refs.

Adsorbent

Qe (mg g1)

Refs.

[46] [47] [48,49] [50] [51] [33] [52] [53] [54] [55] [56] Present study

MgO(111) Palm kernel seed coat Hollow nestlike a-Fe2O3 spheres Hierarchical NiO Spheres Kapok fiber oriented polyaniline Pr(OH)3 nanowires SiO2-CD Porous hierarchical MgO Graphene oxide/chitosan/silica fibers XG-g-PAM/SiO2 Hierarchical hollow structure c-Al2O3 AC/DDAC

303.0 66.23 160 440 40.82 837.4 70.1 2409 294.12 209.205 835.0 769.23

[57] [58] [59] [60] [61] [62] [63] [64] [65] [66] [67] Present study

Table 8 BBD matrix with four independent variables (coded values) and corresponding experimental data for the congo red and direct red 80 systems. Run

Adsorption capacity (mg g1)

Factor

Congo red

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

Direct red 80

x1

x2

x3

x4

Exp.1

Exp.2

Average

Exp.1

Exp.2

Average

0 0 0 0 + + 0 0 + + 0 0 0 0 0 0 + 0 0 + 0

0 0 0 0 0 0 0 + + + + 0 0 0 0 0 0 + + 0 0

+ + 0 0 0 0 0 + 0 + 0 0 0 + + 0 0 0 0 0 0

+ 0 + 0 + 0 + 0 0 0 0 0 0 0 0 0 0 + 0 + 0

369.32 558.70 452.53 535.36 397.86 512.90 381.36 646.31 572.66 711.95 523.85 518.50 563.96 387.62 422.57 540.50 447.14 378.34 368.35 435.39 536.13 534.32 397.95 673.87 577.87 526.56 539.08

369.78 557.78 450.87 534.41 397.86 513.14 383.84 650.87 570.59 713.85 521.94 526.51 563.55 388.10 420.05 540.74 461.64 379.30 366.21 434.71 534.29 533.60 396.05 679.11 580.49 524.89 536.46

369.55 558.24 451.70 534.89 397.86 513.02 382.60 648.59 571.62 712.90 522.89 522.50 563.75 387.86 421.31 540.62 454.39 378.82 367.28 435.05 535.21 533.96 397.00 676.49 579.18 525.73 537.77

239.87 349.87 268.18 283.31 246.15 325.87 249.29 402.59 380.86 466.88 296.34 331.60 356.77 239.09 224.26 346.73 303.26 243.58 233.95 269.85 364.85 350.26 221.25 451.16 389.09 315.73 359.56

234.48 356.84 273.49 284.60 246.47 317.52 246.81 399.40 378.03 473.62 298.91 324.95 360.31 234.27 226.47 349.61 294.76 235.88 240.37 263.20 365.80 355.39 216.11 442.81 389.41 314.44 356.03

237.18 353.36 270.84 283.95 246.31 321.69 248.05 400.99 379.45 470.25 297.63 328.28 358.54 236.68 225.36 348.17 299.01 239.73 237.16 266.53 365.33 352.82 218.68 446.98 389.25 315.08 357.80

Table 9 Statistical parameters of Box–Behneken design for the congo red and direct red 80 systems. Term

Constant x1 x2 x3 x4 x21 x22 x23 x24 x1 x2 x1 x3 x1 x4 x2 x3 x2 x4 x3 x4 *

Congo red

Direct red 80

Coefficient

Sum of squares

T-value

PC*

Coefficient

Sum of squares

T-value

PC*

537.450 49.659 47.290 19.232 114.405 11.952 22.676 25.594 22.310 14.933 4.268 42.034 2.716 30.253 19.325

– 29,592 26,836 4439 157,063 31 733 1978 2655 892 73 7067 30 3661 1494

105.298 19.458 18.53 7.536 44.829 3.122 5.924 6.686 5.828 3.378 0.966 9.509 0.614 6.844 4.372

– 12.51 11.35 1.88 66.40 0.01 0.31 0.84 1.12 0.38 0.03 2.99 0.01 1.55 0.63

352.931 44.635 41.639 15.070 68.792 10.195 34.431 19.699 21.845 2.848 4.589 37.147 3.802 40.878 9.190

– 2.677 2.677 2.677 2.677 4.015 4.015 4.015 4.015 4.636 4.636 4.636 4.636 4.636 4.636

65.925 16.675 15.556 5.630 25.700 2.539 8.575 4.906 5.441 0.614 0.990 8.012 0.820 8.817 1.982

– 19.24 16.74 2.19 45.69 0.13 2.98 0.74 2.05 0.03 0.07 4.44 0.05 5.38 0.27

PC ð%Þ ¼ PSSSS 100.

1136


Table 10 Analysis of variance (ANOVA) of the two fitted quadratic polynomial models. Source

Degrees of freedom

Sum of squares

Adj. sum of squares

Adj. mean squares

F-value

p-Value (F > F0.05)

Remarks

Congo red Regression x1 x2 x3 x4 x21 x22 x23 x24 x1 x2 x1 x3 x1 x4 x2 x3 x2 x4 x3 x4 Lack of fit Residual error Pure error Total

14 1 1 1 1 1 1 1 1 1 1 1 1 1 1 10 12 2 26

236,542 29,592 26,836 4439 157,063 31 733 1978 2655 892 73 7067 30 3661 1494 916 938 22 237,480

236,542 29,592 26,836 4439 157,063 762 2742 3494 2655 892 73 7067 30 3661 1494 916 938 22

16895.9 29,592 26,836 4439 157,063 762 2742 3494 2655 892 73 7067 30 3661 1494 91.6 78.2 11.2

216.19 378.63 343.37 56.79 2009.64 9.75 35.09 44.7 33.96 11.41 0.93 90.43 0.38 46.84 19.11 8.19

0.000 0.000 0.000 0.000 0.000 0.009 0.000 0.000 0.000 0.005 0.353 0.000 0.550 0.000 0.001 0.114

Significant Significant Significant Significant Significant Significant Significant Significant Significant Significant

Direct red 80 Regression x1 x2 x3 x4 x21 x22 x23 x24 x1 x2 x1 x3 x1 x4 x2 x3 x2 x4 x3 x4 Lack of fit Residual error Pure error Total

14 1 1 1 1 1 1 1 1 1 1 1 1 1 1 10 12 2 26

124,280 23907.6 20805.6 2725.4 56788.7 166.6 3700.2 925.1 2545.2 32.4 84.2 5519.6 57.8 6684 337.8 985 1032 46 125,312

124,280 23907.6 20805.6 2725.4 56788.7 554.4 6322.6 2069.5 2545.2 32.4 84.2 5519.6 57.8 6684 337.8 985 1032 46

8877.2 23907.6 20805.6 2725.4 56788.7 554.4 6322.6 2069.5 2545.2 32.4 84.2 5519.6 57.8 6684 337.8 98.5 86 23.2

103.25 278.06 241.98 31.70 660.49 6.45 73.54 24.07 29.60 0.38 0.98 64.20 0.67 77.74 3.93 4.25

0.000 0.000 0.000 0.000 0.000 0.026 0.000 0.000 0.000 0.550 0.342 0.000 0.428 0.000 0.071 0.205

Significant Significant Significant Significant Significant Significant Significant Significant Significant Significant

y ðmg=gÞ ¼ 352:931 þ 44:635 x1 þ 41:639 x2 15:070 x3 þ 68:792 x4 10:195 19:699

x23

21:845

x24

x21

34:431

x22

2:848 x1 x2

þ 4:589 x1 x3 þ 37:147 x1 x4 þ 3:802 x2 x3 þ 40:878 x2 x4 9:190 x3 x4

ð22Þ

where y is the adsorption capacity of congo red or acid direct red 80, and x1, x2, x3, and x4 denote the concentration of DDAC, temperature, pH, and initial concentration of the dye (congo red or acid direct red 80), respectively. Eqs. (21) and (22) were applied to evaluate the influence of process variables for the two dye adsorptions onto AC/DDAC. Analysis of variance (ANOVA) method was used for estimating further the significance and accuracy of the two models and their corresponding results were calculated and listed in Table 10. Fisher F-test is the distribution of the ratio for respective mean-square effect and mean-square error, which could be used for evaluating the presence of a significant difference from control response, and calculating standard errors. The p-value could be used for identifying whether experimental parameters have a statistically significant influence on the particular response or not. It could be seen from Table 10, the two models were highly significant due to having big F values (Fmodel = 216.19 and 103.25) and a very low probability value (pmodel = 0.000) for the congo red and direct red 80 systems, respectively. The F and p values of the lack of fit for the two models were 8.19 and 0.114, and 4.25 and 0.205, respectively, indicating

Significant Significant Significant

Significant Significant

that the lack of fit of the two models was nonsignificant. Hence the experimental data could be fitted well by Eqs. (21) and (22) for the removals of congo red and direct red 80 from the aqueous solution. A normal probability plot of the residuals (difference between the predicted and experimental values) (Fig. 7) was also applied to verify whether they can fit a normal distribution or not. The regression data in Fig. 7 fit almost near to a straight line, indicating that the hypothesis of the analysis was fulfilled. The plots of the experimental versus predicted values were shown in Fig. 8. As could be seen from Fig. 8a and b, the predicted values based on Eqs. (21) and (22) were in good agreement with their corresponding experimental values for the congo red and direct red 80 adsorptions. The squares of the correlation coefficient values (R2) were 0.9961 and 0.9918, indicating that only 0.39% and 0.82% of the total variations could not be explained based on the two models for the congo red and direct red 80 systems, respectively. The squares of the adjusted correlation coefficient values (R2adj) for the two models were 0.9914 and 0.9822, respectively. Both R2adj values are close to 1.0, suggesting that the two models (Eqs. (21) and (22)) have high reliability for predicting their corresponding experimental data, respectively. Moreover, in order to verify further the significant difference between the experimental data and model predicted values, the chi-square (v2) test was employed. The calculated chi-square values (v2cal.) were 1.94 and 4.17 for the congo red and direct red 80 systems, respectively. They were less than the critical value (v2crit = 40.11), which suggested that there were no significant


1137

Fig. 7. Normal probability plots of residuals for the adsorption capacities of congo red (a) and direct red 80 (b) onto AC/DDAC.

Fig. 8. Predicted versus experimental values for the congo red (a) and direct red 80 (b) adsorptions onto AC/DDAC.

difference between the experimental and the predicted response values for the two systems. The chi-square (v2) test deduced with 95% confidence level that the two models were satisfactory to fitting their corresponding experimental data. In addition, the significance of the two models coefficients (Table 10) was also investigated based on the Student’s T test and p-value. If the T-value and p-value of a factor are larger and smaller (i.e. closer to zero), the factor has more significance than other factors. However, for a 95% confidence level, a factor can be considered statistically significant when its p-value is less than or equal to 0.05 [68]. According to the p-values obtained (Table 10), for the congo red system, all the linear and quadratic terms were found to be statistically significant (p < 0.05). According to their interactive terms, only the interactions (x1x3 and x2x3) are not statistically significant at the 95% confidence level. However, for the direct red 80 system, it is evident that all linear and quadratic terms are statistically significant (p < 0.05). In their interactive terms, only the interactive terms (x1x4 and x2x4) are statistically significant at the 95% confidence level. Moreover, the main effects of all the four independent variables (x1, x2, x3, and x4) are more significant than their corresponding quadratic effects (x21, x22, x23, and x24) for the two models due to high PC values (Table 9). The T-value and p-value obtained (Tables 9 and 10) indicated that all the four variables have a direct relationship for the removals of congo red and direct red 80 by AC/DDAC. From Table 9, we discovered that initial concentration of the dye (x4) has the highest contribution (66.40% for the congo red, and 45.69% for the direct red 80) as compared to other components for the removals of two dyes from aqueous solution. Model validation In order to evaluate the predicted ability of the two models (Eqs. (21) and (22)), the validation set with four independent variables was designed by Taguchi design matrix. The four

independent variables (x1, x2, x3, and x4) together with their corresponding response values were shown in Table 11. It could be seen from Table 11, the adsorption capacities of congo red and direct red 80 altered from 440.51 to 617.20 mg/g, and from 269.07 to 404.83 mg/g for their corresponding validation batch experiments, respectively. The plots of the experimental versus predicted values of the validation sets were shown in Fig. 9. As could be seen in Fig. 9a and b, the predicted values were in good agreement with their corresponding experimental values of the validation sets because of high correlation coefficients (R2 = 0.9896 for the congo red system, R2 = 0.9970 for the direct red 80 system), indicating that the two selected quadratic models in predicting their corresponding response variables (i.e. the adsorption capacities of the two dyes) were appropriate. Effects of process variables In order to better understand the effects of independent variables and their interactions on the dependent variable, 3D response surface plots based on the predictive quadratic models (Eqs. (21) and (22)) for the congo red and direct red 80 adsorption capacities were shown in Figs. 10a–f and 11a–f, respectively. From Figs. 10a, d and e and 11a, d and e, the effect of temperature was remarkable for the removals of congo red and direct red 80 by AC/DDAC. The two dyes uptake increased with increasing the temperature. For the congo red system, at the optimum condition (C = 160 mg/L (obtained by Fig. 10e), Cs = 34.10 lM (obtained by Fig. 10c), and pH = 4.0 (obtained by Fig. 10f)), the adsorption capacities based on the prepared adsorbent were found to be increased from 639.45 to 766.48 mg g1 as the temperature increase from 20 to 50 °C; similarly, the direct red 80 uptake increased from 366.96 to 516.82 mg g1 in the range of 20–50 °C and at the optimum condition (C = 110 mg/L (obtained by Fig. 11e), Cs = 34.10 lM (obtained by Fig. 11c), and pH = 6.0 (obtained by Fig. 11f)), which indicated that the two adsorption reactions were endothermic

1138


Table 11 Taguchi design matrix with four independent variables (natural values) in the validation set and their corresponding experimental data for the congo red and direct red 80 systems. Run

1 2 3 4 5 6 7 8

Congo red

Direct red 80

Cs (lM)

T (°C)

pH

C (mg L1)

Exp.(Average) (mg g1)

Cs (lM)

T (°C)

pH

C (mg L1)

Exp.(Average) (mg g1)

20.46 20.46 20.46 20.46 30.69 30.69 30.69 30.69

30 30 40 40 30 30 40 40

5 10 5 10 5 10 5 10

100 140 140 100 140 100 100 140

440.51 499.81 560.93 456.76 617.20 471.09 481.35 615.91

20.46 20.46 20.46 20.46 30.69 30.69 30.69 30.69

30 30 40 40 30 30 40 40

5 10 5 10 5 10 5 10

60 90 90 60 90 60 60 90

274.88 300.87 354.52 269.07 384.80 288.02 295.84 404.83

process. However, an endothermic process relies upon diffusion. Since higher temperature results in larger diffusion rate of the adsorbate molecules across the external boundary layer and within the pores, the adsorption capacities of congo red and direct red 80 increased with increasing the temperature (from 20 to 50 °C). This phenomenon can also be explained based on the thermodynamic parameters of adsorption reaction (such as DH°, DS° and DG°). The Gibbs free energy changes (DG°) of the two adsorption processes are evaluated by Eq. (23) based on the prior equilibrium constant calculation (Eq. (24)) [69], and their enthalpy changes (DH°) and entropy changes (DS°) can be estimated from Eq. (25):

DG ¼ RT ln K c Q Kc ¼ e Ce DH DS þ ln K c ¼ RT R

ð23Þ ð24Þ ð25Þ

where Ce and Qe are the same as in Eq. (6), R is the gas constant (8.314 J mol1 K1), T is the experimental temperature (K). According to Eq. (25), the values of DH° and DS° can be determined from the slope and intercept of the plot of ln Kc versus 1/T, respectively. The values of thermodynamic parameters for the two systems were calculated and summarized in Table 12. It could be seen from Table 12, the values of DG° were negative, suggesting that the two adsorption processes were spontaneous and feasible in the nature of adsorption, while decrease in the values of DG° with rising the temperature indicated increase in the spontaneity of the two adsorption processes. The positive sign of enthalpy changes (DH°) proved that the two adsorption processes were endothermic reaction, indicating that the adsorption capacities of the two dyes increased with increasing the temperature. Their entropy changes (DS°) have been evaluated as 122.47 and 228.23 J mol1 K1, which suggested increase in randomness at the solid-solution interface [70]. The adsorptions of congo red (Fig. 10c, e and f) and direct red 80 (Fig. 11c, e and f) onto AC/DDAC were carried out with different initial concentrations of the two dyes in the range of 80–160 mg L1 and 50–110 mg L1, respectively. As shown in Figs. 10c, e and f and 11c, e and f, the adsorption capacities of the two dyes increased markedly with increasing their initial concentrations. The results were well consistent with the ANOVA analyses for the two systems. That is to say, the congo red uptake increased from 391.84 to 766.48 mg g1 in the range of 80–160 mg L1 and at the optimum condition, but their corresponding removal efficiency decreased from 98.0% to 95.8%; in the same way, the adsorption capacity and removal efficiency of the direct red 80 increased (from 199.71 to 516.82 mg g1) and decreased (from 99.71% to 93.97%) with the optimum condition in the range between 50 and 110 mg L1. During adsorption, the main driving force can overcome mass transfer resistance between the dye and adsorbent phase, which can be provided by initial

Fig. 9. Predicted versus experimental values of the validation set for the congo red (a) and direct red 80 (b) adsorptions onto AC/DDAC.

concentration of the dye, adsorption sites, and available adsorption surface. Then, for constant adsorbent dosage, lower removal efficiency for the congo red and direct red 80 systems were obtained due to lower available adsorption sites of AC at higher initial concentration of the dye, and the adsorptions of two dyes became rely on their initial concentrations. The adsorption capacities of two dyes increased with increasing their initial concentrations because of enhancing the interactions between adsorbent and the dye molecules [71]. The solution pH is one of the most important factors for adsorption process, which controls magnitude of electrostatic charges imparted by ionized dye molecules. Therefore, in the study, the removals of congo red (Fig. 10b, d and f) and direct red 80


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Fig. 10. Response surface plots for the combined effects on the congo red adsorption capacity: (a) the concentration of DDAC (Cs) and T, pH = 7.4, C = 160 mg/L; (b) Cs and pH, T = 50 °C, C = 160 mg/L; (c) Cs and initial concentration of the congo red (C), pH = 7.4, T = 50 °C; (d) T and pH, Cs = 34.10 lM, C = 160 mg/L; (e) T and C, Cs = 34.10 lM, pH = 7.4; (f) pH and C, T = 50 °C, Cs = 34.10 lM.

(Fig. 11b, d and f) onto AC/DDAC were investigated with different pH from 3.0 to 11.8, and from 3.6 to 12.0, respectively. It could be seen from Fig. 10b, d and f, the adsorption capacity of the congo red based on AC/DDAC decreased slightly with increasing pH of the solution. However, for the direct red 80 adsorption, its adsorption capacity was lower at high pH and slightly higher at pH 3.6–6.5 (Fig. 11b, d and f). At an acidic solution, the congo red and direct red 80 are dissociated to polar groups (R-SO 3 ). The acidic medium is favorable for the adsorptions of congo red and direct red 80 onto AC/DDAC because the surface of AC seems to be acidic that increase the protonation at its surface, which induced electrostatic interactions between its surface and R-SO 3 . In addition, the zero point charge (pHzpc) of adsorbent is an important factor. The pHzpc of AC was found to be 8.1 and was shown in Fig. 3S (see support information). At low pH (pH < pHzpc), the adsorptions of anions (R-SO 3) onto AC/DDAC become favored [72], and the exchange sites on the AC are positive, the two dyes and the H+ ions compete for the

active sites and then higher adsorptions would be happened [2]. However, at high pH (pH > pHzpc), the surface of AC has more negative charges, which indicated that the removals of anionic dyes from aqueous solution were unfavourable due to the electrostatic repulsion. Similar results were also reported for the adsorption of the congo red onto CoTiO3 [2] and activated carbon [72], and the direct red 80 onto orange peel [48]. The effects of increasing DDAC concentrations have also been investigated in Figs. 10a–c and 11a–c. The results showed that the congo red uptake increased from 604.89 to 766.48 mg g1 with increasing DDAC concentrations (from 17.05 to 34.10 lM) and at the optimum condition; in the same way, the adsorption capacity of the direct red 80 increased (from 369.89 to 516.82 mg g1) with increase in the concentrations of DDAC (from 17.05 to 34.10 lM) and under the optimum condition. At an acidic solution, the surfactant (DDAC) was adsorbed on the AC surface in the form of DDAC+ cations, and then self-assembled AC could absorb the anionic dyes

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Fig. 11. Response surface plots for the combined effects on the direct red 80 adsorption capacity: (a) the concentration of DDAC (Cs) and T, pH = 7.8, C = 110 mg/L; (b) Cs and pH, T = 50 °C, C = 110 mg/L; (c) Cs and initial concentration of the direct red 80 (C), pH = 7.8, T = 50 °C; (d) T and pH, Cs = 34.10 lM, C = 110 mg/L; (e) T and C, Cs = 34.10 lM, pH = 7.8; (f) pH and C, T = 50 °C, Cs = 34.10 lM.

Table 12 Thermodynamic parameters for the adsorptions of congo red and direct red 80 onto AC/DDAC. System

Ci (mg L1)

DH° (kJ mol1)

DS° (J mol1 K1)

R

Congo red Direct red 80

160 110

14.73 62.71

122.47 228.23

0.9996 0.9650

(congo red and direct red 80) and accompanied with the interactions between DDAC+ (in solution) and dye anions during initial reaction. When the initial concentrations of DDAC increased, the self-assembled AC has bigger adsorption capacities for the congo red and direct red 80 removals because the cooperative adsorption and synergistic effect between DDAC+ and the two dye anions may take place to a large extent in solution [73]. Process optimization of the two dyes removal In order to optimize the independent variable values that can obtain a maximum response, the numerical optimization function based on the D-optimality index in the Minitab 15.0 software were employed. A desirability function is used in the approach. For all the factors, the D-optimality index changes from 0 (completely undesirable) to 1 (completely desirable). Combining the individual

DG° (kJ mol1) 293.15 K

308.15 K

323.15 K

7.04 3.76

8.81 8.58

10.72 10.52

desirability function for each variable is applied to obtain the composite desirability of a multi-response system, which can determine the optimal operating conditions [74]. The optimality plots for the response variable values were shown in Fig. 12. The profiles showed the composite desirability of the two systems and the adsorption capacities of the congo red and direct red 80 as a function of each factor (Fig. 12A and B). The D-optimality values of two systems were calculated for all levels of four process variables (the concentration of DDAC, temperature, pH, and initial concentration of the dye), respectively. For the congo red system, the composite desirability values of concentration of DDAC, T, and initial concentration of the dye gradually increased and subsequently reached a peak value. However, its pH desirability values varied slowly in the starting stage and later decreased rapidly. So the adsorption capacity of the congo


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Fig. 12. Optimization plots for the congo red (A) and direct red 80 (B) adsorptions onto AC/DDAC.

red by AC/DDAC was obtained the maximum response value at low pH level, high concentration of DDAC, T, and initial concentration of the congo red. Likewise, the maximum adsorption capacity for the direct red 80 system was attained at high concentration of DDAC, T, initial concentration of the dye, and under acidulous condition. In summary, a D-optimality of 0.9926 with the maximum response value of 769.48 mg/g was obtained at Cs = 34.10 lM, T = 50 °C, pH = 3.5, and C = 160 mg/L for the congo red adsorption, and a D-optimality of 0.9980 with the maximum response value of 519.90 mg/g was obtained at Cs = 34.10 lM, T = 50 °C, pH = 6.1, and C = 110 mg/L for the direct red 80 removal. In addition, five additional experiments for the two dye adsorptions were accomplished to ascertain the experimental data were not biased toward the predicted values under the aforementioned optimum conditions, respectively. Their average experimental values were 748.42 mg/g and 516.36 mg/g for the congo red and direct red 80 systems, which were consistent with the predicted values based on the two regression models, with small relative errors of 2.81% and 0.67%, respectively. The results indicated that the

two models (Eqs. (21) and (22)) were adequate for reflecting the expected optimization. SEM, BET, FT-IR spectra and XRD analysis The changes in the surface topography of AC after the congo red and direct red 80 adsorptions were observed by SEM (Fig. 4S, see support information). The surface of AC was smoother than those of AC/DDAC sorbing the two dyes, which were in agreement with their corresponding results of BET analysis (The surface area of AC (827.71 m2/g) was smaller than those of AC/DDAC sorbing the congo red (1000.26 m2/g) and direct red 80 (950.35 m2/g)). The results indicated that the dyes adhered to the AC surface. Moreover, the results of energy dispersive X-ray spectrum (EDS) analysis from an average of scanned points showed that the elements of AC particles are: C, S and O (Fig. 5Sa, see support information). After adsorption process (Fig. 5Sb and c, see support information), the appearance of N could be observed due to the trapped dye molecules which contain azo groups, and the contents of S and O for AC

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adsorbing the two dyes were higher than those of them for only AC, which reconfirmed that the adsorptions of congo red and direct red 80 onto the external surface of AC proceeded because of electrostatic interactions between sulfonate groups of the adsorbed dyes and H+ or DDAC+ ions on the AC surface. Fig. 6S (see support information) showed the XRD patterns of AC, AC/DDAC sorbing the congo red, and AC/DDAC sorbing the direct red 80. It could be seen from Fig. 6S, a high-intensity peak of 2h (25.70) was observed in the non-adsorbed AC, which was confirmed to be a peak created by AC. This peak was not found on the congo red and direct red 80 adsorbed AC. This phenomenon could be explained by formation of new crystals on the external surface of AC by H+ and DDAC+ ions as adsorptions of the two dye anions took place, covering the surface of the original AC [75]. The results were in good agreement with their SEM micrographs (Fig. 4S) and corresponding EDS analysis (Fig. 5S). FT-IR spectra of AC, only dye (the congo red or direct red 80), DDAC, and the dye loaded AC/DDAC were shown in Fig. 7S (see support information). For the AC sample, there is a strong peak centering at 3438 cm1 that can be mainly assigned to O-H stretching vibration because of the water and oxygen-containing functional groups on the AC surface. However, there are more peaks in the spectra taken after the two dye adsorptions, and these peaks refer to DDAC-congo red/direct red 80 complexes, congo red and direct red 80 molecules. That is to say, the peaks at 1476 cm1 and 617 cm1 are assigned to the characteristic peaks of aromatic ring; and the peak in 1126 cm1 is due to the asymmetric sulfonate vibration. Their corresponding peak ratios and locations altered after the direct red 80 was adsorbed onto AC. When AC adsorbed the congo red, the peaks in 1623 and 671 cm1 (the characteristic peaks of aromatic ring), 1180 cm1 (the asymmetric sulfonate vibration, 1178 cm1 for the pure dye salts) and 1044 cm1 (the symmetric sulfonate vibration, 1061 cm1 for the congo red salts) [76] were discovered. This fact suggested that the interactions + + between the adsorbed two dye anions (R-SO 3 ) and H or DDAC ions on the external surface of AC were carried through the sulfonate groups, which were in good agreement with above discussion.

Conclusion In the study, activated carbon (as adsorbent) acquired from the business company, were used without further purification for the removals of the congo red and direct red 80 because it can fit better actually application environment. The process variables of two dye adsorptions onto AC/DDAC from aqueous solution have been optimized using the Box–Behnken design. The results indicated that all the four process variables have a direct relationship for the treatment of the two dyes by AC/DDAC, and the solution pH (x3) and initial concentration of the dye (x4) have the lowest and highest contributions (1.88% and 66.40% for the congo red system, and 2.19% and 45.69% for the direct red 80 system) for removing them. To search the process variable values that can result in the maximum response, the numerical optimization function based on the D-optimality index in the Minitab 15.0 software were employed. The two maximum response values (769.48 and 519.90 mg/g) were discovered at the optimal conditions, which were in good agreement with their corresponding experimental values determined (748.42 mg/g for the congo red removal, and 516.36 mg/g for the direct red 80 adsorption). The two dye adsorptions were evaluated with the aspect of thermodynamics and kinetic. The thermodynamics results suggested that the two adsorption processes were spontaneous and feasible. Kinetic studies indicated that the two adsorption equilibriums were achieved within 100 and 90 min for the congo red and direct red 80 systems, and the pseudo-second-order model could

be fitted well for the two systems. From the plot of Qt versus t0.5, the intraparticle diffusion was not the only sole rate-controlling step for the adsorptions of the direct red 80 and congo red and the external mass transfer was also significant in the rate-controlling step. In addition, the adsorption isotherm data were analyzed by Langmuir, Freundlich, Temkin, and Dubinin–Radushkevich isotherm models, and the Langmuir model was the best fit, showing the maximum monolayer adsorption capacities of 769.23 and 526.32 mg g1 at 323.15 K for the congo red and direct red 80 systems, respectively. The study would be helpful to remove the congo red and direct red 80 from printing and dyeing sewage by inexpensive AC/DDAC because it has bigger adsorption capacities for the two dyes than those of other adsorbents. Unfortunately, the compound adsorbent is difficult to recycle. Therefore next work is to solve the question. Acknowledgements Financial support from Sichuan Provincial Science & Technology Fund for Distinguished Young Scholars (2012JQ0058), with the NSFC (20873104) and SKLOGRGE (PLN-ZL002, SWPU) is gratefully acknowledged. Appendix A. Supplementary material Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.saa.2014.08.138. References [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30]

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