Adsorption Characteristics of Activated Carbon for the Reclamation of

Dec 23, 2016 - Department of Chemical Engineering, Pondicherry Engineering College, Pondicherry 605014, India. ‡. Department of Chemical Engineering...
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Adsorption Characteristics of Activated Carbon for the Reclamation of Colored Effluents Containing Orange G and New Solid−Liquid Phase Equilibrium Model R. Gopinathan,† Avijit Bhowal,‡ and Chandrasekhar Garlapati*,† †

Department of Chemical Engineering, Pondicherry Engineering College, Pondicherry 605014, India Department of Chemical Engineering, Jadavpur University, Kolkata 700 032, India



ABSTRACT: Adsorption characteristics of activated carbon for the removal of orange G, an acid dye from aqueous solutions, have been investigated. The effect of initial dye concentration, temperature, and pH on the removal of orange G was investigated. The removal of orange G decreased from 95% to 82%, when the pH was increased from 2 to 12. The study of the effect of temperature and associated thermodynamic properties revealed the process of removal of dye is endothermic and spontaneous. Kinetic and mass transfer studies of the process were also carried out. The experimental data were used to develop a new solid− liquid phase equilibrium isotherm model. The average absolute relative deviation of the experimental data from the proposed model equation was 5.68%. In order to scale up the batch process for the removal of orange G, the concentration versus time data were analyzed to obtain mass transfer coefficient. The liquid-phase volumetric mass transfer coefficient (kLapL) was found to decrease from 0.008057 to 0.002827 s−1 when the initial concentration varied from 50 to 125 mg·L−1



INTRODUCTION Dyes are commonly used in textile, printing, pharmaceutical, paper, leather, and cosmetic industries.1−6 These industries release a considerable amount of dyes along with their effluents. Several treatment methods are available to remove dyes from effluents, which are broadly classified as physical, chemical, and biological methods.6,8 The physical treatment methods includes adsorption, ion exchange, and membrane filtration. The chemical flocculation, froth flotation, and chemical oxidation are the chemical treatment methods.3,7 The physical treatment methods generates a lesser amount of byproducts when compared to chemical and biological methods.7 Among the physical methods, adsorption is a less energy intensive treatment method; hence it is widely used in the treatment of dye effluents.3,8 Among all adsorbents that are employed in industrial effluent treatment, activated carbon is the best because of its unique characteristics such as availability and a larger surface area.9,10 The treatment of effluents takes place usually either by batch or continuous modes. The effective implementation of adsorption technology depends on the accurate adsorption data.11 Therefore, adsorption data measurements are essential. The adsorption isotherm modeling is also very important to implement adsorption technology in industry. Single component adsorption isotherm data can be obtained accurately by batch experiments or frontal analysis method.12,13 Most of the adsorption isotherm data available in literature is based on batch experimental technique. Therefore, we have also used batch tests in our study. In the present work the activated carbon has been used for the removal of the orange G dye from aqueous solutions. The © XXXX American Chemical Society

effect of parameters such as temperature, initial dye concentration, and pH on the removal of orange G has been reported. Kinetics and mass transfer studies for the removal of orange G have also been conducted. A new solid−liquid phase equilibrium model based on phase equilibrium criteria has been proposed, and its correlations were reported. The proposed model equation comprising of six adjustable parameters correlates the isotherms as a function of temperature. The adjustable parameters are the dilute liquid phase activity coefficient (γ∞L A ) and solid phase activity coefficients, α and β. The ratio of β and α gives the sorbate melting temperature.



EXPERIMENTAL PROCEDURE Materials. The activated carbon was purchased from Merck. Inc. (Germany). The activated carbon was washed several times with DM water to remove surface impurities. The activated carbon was dried at 100 °C for about 72 h. The orange G (CAS No. 1936-15-8) was purchased from Nice, India and used without further purification. Adsorbent Characterization. Chemical Characteristics. The point of zero charge (PZC), acidity, and basicity are the very important characteristics for activated carbon.6 The Boehm titration method was used to estimate the acidity and basicity of the activated carbon, whereas the pH drift method was employed to estimate PZC of the activated carbon.14−16 Received: September 28, 2016 Accepted: December 13, 2016

A

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The chemical characteristics evaluated in this study are listed in Table 1. Table 1. Chemical Characteristics of the Activated Carbon adsorbent commercial activated carbon

pHPZC

basicity (mmol·g−1)

acidity (mmol·g−1)

6.7

0.48

0.35

Physical Characteristics. The activated carbon surface area and pore size was evaluated using a Brunauer−Emmett−Teller (BET) instrument (Beckman Coulter). The value of surface area was calculated by the BET method, and the values of mesopore volume and size were calculated by the Barret, Joyner, and Halenda (BJH) method. Figure 1a and b shows the

Figure 2. (a) Pore size distribution of activated carbon (BET). (b) Particle size distribution of activated carbon (Horiba LA90).

analyzed using spectrophotometer (Jasco UV model V-630) at 480 nm. The UV response curves and calibration graphs used for the experiments were shown in Figure 3. The adsorption isotherms were studied by a batch adsorption method. Fifty milliliters of aqueous dye solutions of known initial concentration (i.e., orange G initial concentration was 506 mg/L) were shaken with 0.1−0.6 g activated carbon samples in 250 mL stoppered conical flasks T = 303−323 K for 3 days in a temperature-controlled water bath. When adsorption equilibrium was attained, the concentrations of the dye in the aqueous solutions were accurately determined. The concentrations of the dye compounds were determined by the absorbance of ultraviolet light, using a spectrophotometer.17 Scanning Electron Micrograph (SEM) of Activated Carbon. The surface morphology of the activated carbon was analyzed using a JSM 6390 (USA) high-performance, scanning electron microscope with a high resolution. The micrograph of activated carbon is shown in Figure 4. This micrograph represents a rough surface and seems to be suitable for the adsorption of dyes from the liquid phase. Figure 5 represents the micrograph after adsorption. Thermodynamic Parameters. The thermodynamic parameters such as enthalpy change, entropy change, and Gibbs free energy change were estimated with the help of Langmuir isotherm parameters. The appropriate equations were listed below. More details related to these equations were reported elsewhere.18

Figure 1. (a) Activated carbon hysteresis isotherm (BET). (b) Activated carbon pore area vs pore diameter (BET).

nitrogen adsorption and desorption isotherm at 77 K and pore area against pore diameter, respectively. The average particle size is analyzed using HORIBA laser scattering particle size distribution Analyzer model LA-960. Figure 2a and b shows the pore size distribution and particle size distribution, respectively. The physical characteristics evaluated in this study were listed in Table 2. Batch Adsorption. The dye solutions were prepared by dissolving accurately weighed amounts of orange G in distilled water. The concentration of dye in the sample solution was B

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Table 2. Physical Characteristics of the Activated Carbon adsorbent

BET surface area (m2·g−1)

t-plot surface area (m2·g−1)

micropore volume (mL·g−1)

average particle size (μm)

commercial activated carbon

1155.20

407.161

0.33615

26.514

Figure 5. SEM of orange G loaded activated carbon.

ΔG ο = −RT ln d

(1)

⎛ TT ⎞ ⎛d ⎞ ΔH ο = −R ⎜ 2 1 ⎟ln⎜ 2 ⎟ ⎝ T2 − T1 ⎠ ⎝ d1 ⎠

(2)

ΔH ο − ΔG ο T

(3)

ΔS ο =

where d, d1, and d2 are the Langmuir isotherm constants at different temperatures (i.e., T, T1, and T2, respectively).



THEORETICAL SECTION New Solid−Liquid Phase Equilibrium Model. In this model we assume that adsorbent is highly porous. The solute is well-distributed into the porous adsorbent, and the solute molecules are uniformly absorbed on an adsorbent. The solid phase is treated as a solid solution.19,20 At equilibrium the fugacity of sorbate in liquid and solid can be equated as,

Figure 3. (a) Absorbance vs wavelength for orange G. (b) Absorbance vs concentration for orange G.

L S f = fÂ

(4)

In eq 4, subscript A is the solute, and superscripts (L and S) represent the liquid and solid phases, respectively. Equation 4 can be rewritten in terms of the activity coefficients as L

f = γALxAf AL

(5a)

S

f = γASzAf AS

(5b)

where γLA and γSA are the activity coefficients of solute in liquid and solid phase. xA and zA are the mole fractions of solute in liquid and solid phase, respectively. fLA and fAS are pure component fugacities of solute in the respective phases. For dilute systems the liquid phase activity coefficient γLA may be treated as infinite dilution (i.e.,γ∞L A ), and it has been used as an adjustable parameter in this model. The solid phase activity coefficient can be obtained from the truncated Redlich−Kister expansion as suggested by Riazi and Khan.20

Figure 4. SEM of activated carbon. C

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Article

(6)

where (1 − zA) is the mole fraction of the adsorbent, and A′, B′, and C′ are temperature-dependent parameters related to constants in the relation for excess Gibbs free energy, GE. Equation 4, eq 5a, and eq 5b were combined and rearranged to give: ⎛ γ S ⎞⎛ f S ⎞ xi = zi⎜⎜ ∞AL ⎟⎟⎜⎜ AL ⎟⎟ ⎝ γA ⎠⎝ f A ⎠

(7)

The fugacity of the pure solid and fugacity of the pure liquid at the system pressure and temperature21 as ⎛ f S ⎞ −ΔH ⎛ T ⎞ f ln⎜⎜ AL ⎟⎟ = − 1⎟ ⎜ RT ⎝ Tm ⎠ ⎝ fA ⎠

(8)

If the physical properties are not available for a compound of interest, the term α − β/T may be used as an alternate of the term21 ΔHf/RT(T/T m−1) in eq 8, hence, f AS /f AL = exp(α − β /T )

Figure 6. Effect of pH on the removal of orange G dye by activated carbon at a dosage of 0.5 g and volume of 5 × 10−4 m3 at T = 303 K: □, 50 mg·L−1; ○, 75 mg·L−1.

(9)

where α and β are constants. Combining eq 6, eq 7, and eq 9 gives

moderate decrease in adsorption capacity for orange G was observed under basic conditions. The removal of orange G decreased from 95% to 82%, when the pH was increased from 2 to 12. The highest adsorption was observed at pH 4.0. Similar adsorption behavior with variation in solution pH has been reported in the literature for orange G−bagasse fly ash system.23 A comparison of the influence of solution pH on adsorption of orange G with some recent results obtained using various types of adsorbents is presented in Table 3. The dye adsorption efficiency moderately decreases with an increase in solution pH. The main interaction between activated carbon and dye molecule is electrostatic in nature. The reduction in dye adsorption at highly basic conditions can be attributed to electrostatic repulsion between the negatively charged activated carbon and the deprotonated dye molecules.7 Effect of Temperature on Dye Adsorption and Correlations. The experimental results for the batch adsorption of orange G from aqueous solutions on activated carbon were determined at T = 303, 313, and 323 K and p = 0.1 MPa as shown in Table 4. The adsorption capacity of activated carbon is found to increase with increase in temperature. The adsorption data of orange G obtained in this study were correlated with the new model and with the model proposed by Khan et al. The advantage of the new model over the existing model is its flexibility in terms of number of adjustable parameters. The new model is capable of giving the infinite dilution activity coefficient and melting point of the solute from the equilibrium adsorption data. The deviation of experimental data from the model was quantified in terms of AARD% (average absolute relative deviation percentage) and given by,

⎛ exp((1 − z )2 (A′ + B′z + C′z 2 )) ⎞ A A A ⎟ xA = zA ⎜⎜ ⎟ ∞L γ ⎝ ⎠ A × (exp(α − β /T ))

(10)

In general the adsorption equilibrium data are reported in terms of qe and Ce from such data xA and zA can be calculated from the following equations xA =

zA =

Ce/M Ce/M + ρB (1 − Ce/ρA )

(11)

qe /M 1000/12 + qe /M

(12)

where Ce is the sorbate (i.e., solute) concentration in liquid mg· L−1, qe is mg·g−1, and M is the molar mass of the solute. ρB is the molar density of the pure solvent (mol·m−3), and ρA is the molar density of the pure liquid solute (A) of interest in mol· m−3. The solid density can be measured by the additive method of Immirzi and Perini.22 For pure liquids, density can be calculated by dividing the solid density with a factor of 1.02.21 Existing Solid−Liquid Phase Model. There is only one model available in the literature for modeling liquid isotherms based on phase equilibrium criteria. Hence, it is only considered for the comparison. The Khan et al. model19 relates mole fractions of sorbate in solution that is in equilibrium adsorbent, xA, with the mole fraction of sorbent on adsorbent, zA, as follows: x = z exp[(1 − z)2 (a + bz + cz 0.5)]

AARD% = (100/Ni)|xical − xiexp| /xiexp

(13)

(14)

In eq 14, Ni is the number of data points, xi represents the mole fraction of the adsorbate (solute) in liquid that is in equilibrium with adsorbent (solid), and the superscripts cal and exp denote the calculated and experimental values, respectively. The optimization procedure directly gives these parameters. The Nelder−Mead simplex algorithm, implemented in Matlab 6.1, was used to determine the interaction parameters.24 In Table 5 the values of γA∞L, A′, B′, C′, α, and β were reported. In

where a, b, and c are temperature-dependent model parameters.



RESULTS AND DISCUSSION Effect of pH. The effect of pH on adsorption was studied by altering the aqueous solution pH from 2 to 12 at 303 K. Dilute NaOH and HCl of 0.1 N was used to adjust the pH of the solution. The experimental results are shown in Figure 6. A D

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Table 3. Comparison of pH (Corresponds to Maximum % Removal), Kinetic Behavior, and Adsorption Capacity (i.e., qm Corresponds to Monolayer) of Commercial Activated Carbon towards Orange G with Various Adsorbents T/K

adsorbent bagasse fly ash mesoporous fertilizer commercial activated commercial activated commercial activated

plant waste carbon carbon carbon carbon

pH corresponds to maximum % removal

303 298 303 313 323

kinetic behavior nd

2 order 2nd order 2nd order

3.0−4.0 3.0−7.0 4.0

qm/mg·g−1

ref

18.796 236.07 127.61 137.86 147.22

23 28 this study this study this study

Table 4. Experimental Final Concentration of Solute (Orange G) in the Solution at Equilibrium, Ce, the Moles of Solute Adsorbed onto Activated Carbon per kg of Activated Carbon qe at T = 303, 313, and 323 K and p = 0.1 MPaa T/K = 303 −1

T/K = 313 −1

−1

T/K = 323

dye

10 Ce (mol·kg )

qe (mol·kg )

10 Ce (mol·kg )

qe (mol·kg )

10 Ce (mol·kg−1)

qe (mol·kg−1)

orange G

52.06 41.79 32.89 25.36 20.07 16.47 13.76 11.76 7.33 5.35 4.26

0.241 0.235 0.227 0.217 0.205 0.191 0.179 0.167 0.131 0.107 0.089

48.48 37.65 28.18 21.43 17.44 14.21 11.81 10.09 6.55 4.95 3.92

0.256 0.249 0.241 0.227 0.210 0.196 0.182 0.170 0.132 0.107 0.090

44.52 33.78 24.81 18.70 14.18 11.79 9.87 8.23 5.66 4.43 3.65

0.272 0.262 0.250 0.234 0.218 0.201 0.186 0.173 0.133 0.108 0.090

5

5

−1

5

The densities of solvent39 (water) are 995.647, 992.215, and 988.037 kg·m−3 at T = 303, 313, and 323 K, respectively. Standard uncertainties u are as follows: u(T) = ±0.1 K, u(P) = ±0.0013 MPa and the relative standard uncertainties ur in ur(Ce) = 0.03, ur(qe) = 0.03.

a

Table 5. Correlation Parameters for Dye Compound Obtained Using New Model eq 10 correlation parameters dye

T/K

γA∞L

A′

B′

C′

α

β

AARD (%)

orange G

303 313 323

2.8021 2.4737 2.3115

405.58 345.06 367.87

−423.30 −402.69 −472.58

506460 424310 415700

1275.6 1117.9 1286.2

511050 459690 536100

5.11 5.68 3.91

Table 6, the values of the Khan et al. model parameters along with AARDs were reported. From Tables 5 and 6 it is clearly Table 6. Correlation Parameters for Dye Compound Obtained Using the Khan et al. Model eq 13 correlation parameters dye

T/K

a

b

c

AARD (%)

orange G

303 313 323

−1.3528 −1.9812 −1.6244

4484.5 3899.8 3907.9

−324.96 −288.99 −302.29

6.06 6.72 5.66

evident that the new model present in this study is better than the existing Khan et al. model. To indicate this visually, the adsorption of orange G on activated carbon are correlated by the model equations represented in Figure 7. The solid line, which represents correlation of the new model, indicates that this model is able to correlate better than the Khan et al. model. The parameter, γA∞L, in the new model indicates the solution behavior either positively deviating or negatively deviating from Raoult’s law. If the γA∞L value is more than one we can say that the solution is positively deviating from Raoult’s law; for other case (i.e., γA∞L < 1) we say that the solution is negatively deviating. The value of γA∞L varies with temperature.25 Conceptually, the ratio of parameters β and α gives the melting point of the solute. From Table 5 we can say that the orange G

Figure 7. Mole fraction of orange G on solid phase (z) against the mole fraction of orange G in liquid phase (x). Experimental values: □, T = 303 K; ○, T = 313 K; △, T = 323 K. The solid lines are models predictions based on new model in this study. The dash−dot lines are the predictions based on the Khan et al. model.

solution is positively deviating from Raoult’s law, the γA∞L value is decreasing with increase in temperature, and the predicted E

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melting point (ratio of β and α) for the orange G is 400−416 K. The new model derived in this study was used to correlate the equilibrium adsorption data of phenol−activated carbon system taken from the literature.26 The correlation coefficients of phenol−activated carbon system were found to be γA∞L = 23.24, A′ = 45.86, B′ = 145.17, C′ = 1793.6, α = 815.77, and β = 255300.0 with AARD of 3.3%. Figure 8 shows the plot for a new model. This indicates the applicability of the new model to the data other than investigated in this study.

Figure 9. Pseudo-second-order adsorption kinetics of orange G dye on activated carbon at a dose of 0.5 g and solution volume of 5 × 10−4 m3 at T = 303 K. Dye concentration: □, 50 mg·L−1; ○, 75 mg·L−1; △, 100 mg·L−1; ×, 125 mg·L−1.

Freundlich and Langmuir Equilibrium Isotherm Models. The correlation of experimental adsorption data with the conventional adsorption models were considered to gain an understanding of the adsorption behavior and heterogeneity of the activated carbon surface. The Freundlich isotherm model30 can be represented as follows. Figure 8. Mole fraction of phenol on solid phase (z) against mole fraction of phenol in liquid phase (x). Experimental values:23 □, T = 294 K. The solid lines are model predictions based on a new model in this study.

qe = KFCe1/ n

(16)

where: qe is the uptake of orange G per unit weight of activated carbon, Ce is the equilibrium orange G concentration corresponding to qe, KF is a Freundlich isotherm constant for orange G-activated carbon system, and n is another Freundlich isotherm constant that is restricted to values greater than unity. It is important to know that a fit to the Freundlich equation cannot be related to the adsorption mechanism. However, we can model equilibrium adsorption data by writing eq 16 in logarithmic form as 1 ln(qe) = ln(KF) + ln(Ce) (17) n

Kinetic Studies. The kinetics of adsorption is an important characteristic which determines the efficiency of the adsorption process.27 In order to test the suitability of the activated carbon for the removal of Orange G, the concentration versus time data were analyzed. A detailed discussion is presented as follows. Kinetic Model. There are several methods available in literature to describe the adsorption kinetics.27−29 Kinetics studies were performed with 0.0005 m3 of solution at 303 K by varying the solution concentration from 50 to 125 mg·L−1 by keeping the adsorbent dosage at 0.5 g. The contact time of 120 min was maintained for all of the experiments. The adsorption kinetics data are represented in Figure 9. The pseudo-first-order kinetic model is not found to fit the kinetic data, whereas the pseudo-second-order kinetic model is found to fit the kinetic data. The mathematical form of this model can be defined as t 1 t = + 2 qt qe k 2qe (15)

Since eq 17 is linear, a plot of ln(qe) versus ln(Ce) will yield a straight line provided that the equilibrium data obey the Freundlich equation. Figure 10 represents equilibrium data fit to the Freundlich equation. KF and n are determined from intercept and slope. The Langmuir isotherm model31 can be represented as follows qe =

−1

where: k2 is the pseudo-second order rate constant (g·mg · min−1), k and qe are determined from the slope and intercept. The calculated parameters are shown in Table 7. The square of regression coefficient value was 0.999. A similar kinetic behavior has been reported in the literature for orange G− bagasse fly ash system and orange G−mesoporous fertilizer plant waste carbon system.23,28 A comparison of kinetic behavior of orange G with some recent results obtained using various types of adsorbents is presented in Table 3.

qmdCe 1 + dCe

(18)

where qm is the amount of orange G adsorbed at complete monolayer coverage and d is a Langmuir adsorption isotherm constant for orange G-activated carbon system. The higher the value of d is indicative of a favorable adsorption process. The Langmuir equation can be linearized in the following form

Ce C 1 = e + qe qm dqm F

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Table 7. Pseudo-Second-Order Kinetics Constants for Orange G Adsorption on Activated Carbon dye concentration (mg·L−1)

qe(exp) (mg·g−1)

qe(cal) (mg·g−1)

k2 (g·mg−1·min−1)

R2

50 75 100 125

40.3 48.3 62.5 63.6

40.3 48.4 63.4 65.0

0.1482 0.0730 0.0096 0.0067

0.999 0.999 0.999 0.999

parameters and their correlation coefficients are reported in Table 8. From regression values and Figures 10 and 11, we can infer that the experimental adsorption equilibrium data is more consistent with Langmuir model when compared to Freundlich model. The literature reported values for the orange G− mesoporous fertilizer plant waste carbon system are in the same order of magnitude.28 A comparison of isotherm parameters of orange G with some recent results obtained using various types of adsorbents is presented in Table 3. McClellan and Harnsberger32 proposed the following empirical equation for the estimation of surface area occupied by one adsorbate molecule on activated carbon, σ, as follows ⎛ M ⎞2/3 σ(Å ·mol ) = 1.091 × 10 ⎜ ⎟ ⎝ ρN ⎠ 2

−1

16

(20)

where M is the molecular mass of adsorbate (i.e., orange G) molecule (g·mol−1), ρ is the density of the orange G (g·cm−3), and N is the Avogadro’s number (6.022 × 1023). The fraction of the activated carbon surface that is occupied by orange G molecules (θ) can be calculated using the following equation.7

Figure 10. Linear Freundlich isotherm plot for orange G adsorption onto activated carbon. Experimental values: □, T = 303 K; ○, T = 313 K; △, T = 323 K. The dash−dot lines are the Freundlich model predictions.

Figure 11 represents equilibrium data fit to Langmuir equation. The Freundlich isotherm and Langmuir model

θ=

qmNσ × 10−20 SBET

(21)

where θ is the fraction of the activated carbon surface that is occupied by orange G molecules at saturation, qm (mol·g−1) is the amount of orange G adsorbed (i.e., for monolayer layer coverage) at saturation based on the Langmuir model, and SBET (m2·g−1) is the specific surface area of the activated carbon. The θ values should be unity for monolayer layer coverage. The value of θ much less than 1 indicates incomplete formation of a monolayer and is indicative of large fractions of unoccupied adsorbent surface. The values of σ and θ for orange G-activated carbon system are given in Table 9. The incomplete formation of monolayer may be attributed to the large molecular diameter of the orange G molecule which cannot fully access the available activated carbon micropores that account for 64.75% of the total surface area of the activated carbon. Thermodynamic Studies. The Langmuir isotherm model parameters reported in Table 8 were used in the estimate of thermodynamic properties. The enthalpy, entropy, and Gibbs free energy change of orange G adsorption from aqueous solutions are shown in Table 10. The negative value of ΔH° and ΔG° indicates that the process is exothermic and spontaneous.33−35 The positive value for entropy change ΔS°

Figure 11. Linear Langmuir isotherm plot for orange G adsorption onto activated carbon. Experimental values: □, T = 303 K; ○, T = 313 K; △, T = 323 K. The dash−dot lines are the Langmuir model predictions.

Table 8. Freundlich and Langmuir Isotherm Constants for Orange G Adsorption on Activated Carbon Freundlich constants −1

Langmuir constants 2

dye

T/K

KF (L·mg )

n

R

orange G

303 313 323

14.76 14.40 14.82

2.56 2.41 2.33

0.930 0.925 0.907 G

qm (mg·g−1)

d (L·mg−1)

R2

127.61 137.86 147.22

0.02686 0.02686 0.02819

0.999 0.998 0.998

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Table 9. Values of σ and θ for Orange G−Activated Carbon System dye

density (g·cm−3)

molecular weight (g·mol−1)

T/K

105 qmax (mol·g−1)

σ (Å2·mol−1)

θ

orange G

0.43

452.37

303 313 323

28.2 30.5 32.5

158.0

0.23 0.25 0.27

Table 10. Thermodynamic Parameter for the Adsorption of Dye Compound on Activated Carbon −ΔG° (J·mol−1)

dye T = 303 K 25705

orange G

T = 313 K 26551

−ΔS° (J·mol−1·K−1) T = 323 K 27530

T = 303 K 71.31

indicates that the orange G dye molecules shows increased randomness condition at solid−solution interface and no significant changes occur in the internal structure of the adsorbent with the adsorption of orange G on activated carbon.36,37 The decrease in the values of ΔG° with increase in temperature indicates that the orange G dye adsorption process is favorable at higher temperatures.37 Estimation of Liquid Side Volumetric Mass Transfer Coefficient. In order to scale up the batch process for the removal of orange G, the concentration versus time data were analyzed to obtain mass transfer coefficient. A detailed discussion is presented as follows. Transient Material Balance Model. In an adsorption process, if the solid-phase resistance is neglected, then only the liquid-phase mass transfer resistance kL needs be evaluated. Let the volume of the liquid be treated be vL (m3), initial concentration co (mol solute A/volume), Ss the mass of adsorbate free solid, aps the surface of solid per unit mass of solid, and apL the surface of the solids per volume of liquid.38 If c is the concentration of the solute in the bulk liquid at time t and c* is the equilibrium concentration of the solute in the liquid at equilibrium, then the liquid side transient material balance gives39 − dc = kL(c − c*) a p dt

NA =

L

where a p = L

∫C

C 0

(22)

t

kLa pL dt

T = (303 to 323) K 4087.71

Table 11. Liquid-Phase Volumetric Mass Transfer Coefficient, kLapL, at 303 K

vL

∫0

T = 323 K 72.54

Figure 12. Plot of c/co versus time for orange G dye on activated carbon at a dosage of 0.5 g and a solution volume of 5 × 10−4 m3 at T = 303 K. Experimental values at dye concentration: □, 50 mg·L−1; ○, 75 mg·L−1; △, 100 mg·L−1; ×, 125 mg·L−1.

a psSs

− dc = (c − c*)

T = 313 K 71.73

−ΔH° (J·mol−1)

co (mg·L−1)

c* (mg·L−1)

103 kLapL (s−1)

R2

50 75 100 125

9.7 26.8 37.5 61.4

8.057 4.931 3.559 2.827

0.999 0.999 0.985 0.969

(23)

resistance has increased to 185% when initial concentration increased to 150%.

⎡ c − c* ⎤ ⎥ = kLa pLt −ln⎢ ⎣ c 0 − c* ⎦

(24)

c − c* = exp[−kLa pLt ] c 0 − c*

(25)

c /c0 = exp(−kLa pLt ) + (c*/c0)(1 − exp[ −kLa pLt ])

(26)



CONCLUSIONS The removal of orange G decreased from 95% to 82%, when the pH was increased from 2 to 12. The process of removal followed the pseudo-second-order kinetics equation. The adsorption data were correlated with a new thermodynamic model. The average absolute relative deviation of the experimental data from the new model equation was 5.68%. The thermodynamic parameters were determined, and the process of removal of orange G by adsorption on activated carbon was found to be spontaneous. The liquid-phase volumetric coefficient was found to be in the order of 10−3 s−1.

The concentration versus time data for various initial concentrations are given in Figure 12. The calculated mass transfer coefficients are shown in Table 11. The square of regression coefficient value was more than 0.966 for all concentrations studied. The liquid-phase volumetric mass transfer coefficient (kLapL) was found to decrease from 0.008057 to 0.002827 s−1 when the initial concentration varied from 50 to 125 mg·L−1. Since the reciprocal of mass transfer coefficient is a representative of resistance, we can say that the



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DOI: 10.1021/acs.jced.6b00845 J. Chem. Eng. Data XXXX, XXX, XXX−XXX

Journal of Chemical & Engineering Data

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Chandrasekhar Garlapati: 0000-0002-6259-476X Funding

The author is thankful to TEQIP II, Pondicherry Engineering College and Govt. of India for funding the mass transfer lab under which this work was carried out. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The author is thankful to Ramesh, ME Department of Chemical Engineering of BITS for taking SEM images. REFERENCES

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DOI: 10.1021/acs.jced.6b00845 J. Chem. Eng. Data XXXX, XXX, XXX−XXX