Hierarchical Porous Carbon Nanospheres for Efficient Removal of

Article Cite This: J. Chem. Eng. Data XXXX, XXX, XXX−XXX

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Hierarchical Porous Carbon Nanospheres for Efficient Removal of Toxic Organic Water Contaminants of Phenol and Methylene Blue Sukanya Kundu, Ipsita Hazra Chowdhury, and Milan Kanti Naskar* Sol−Gel Division, Central Glass and Ceramic Research Institute (CSIR), Kolkata 700 032, India S Supporting Information *

ABSTRACT: Hierarchical porous carbon nanospheres were synthesized by a hydrothermal process at 130 °C/24 h using different triblock copolymers such as F108 (PEO133PPO50PEO133; PEO, poly(ethylene oxide); PPO, poly(propylene oxide)), F127 (PEO106PPO70PEO106), and L64 (PEO13PPO30PEO13) as soft templating agents. Characterization of the samples was carried out by low angle XRD, Raman spectra, FESEM, TEM, and N2 adsorption−desorption studies. The BET surface area of the samples was in the range 600−750 m2/g comprised of micropores and mesopores. Nanospherical particles of size range 60−100 nm were formed. The synthesized samples were used for the removal of phenol and methylene blue (MB), the toxic organic contaminant in water. The maximum adsorptions of 98.9 and 100% were observed within 10 min for phenol and MB, respectively. For different soft templates, the adsorption capacity of the samples followed in the order CF108 > CF127 > CL64, which was affected by the textural properties of the corresponding samples. Selective adsorption of the samples was also studied in the presence of both pollutants, phenol and MB.

1. INTRODUCTION Contamination of water by industrial waste chemicals is one of the most serious problems in recent days. Phenol and its derivatives are the topmost toxic contaminants in water. Different industries like textile, pesticide, coal, pharmaceutical, leather, petrochemical, etc., generate phenolic compounds.1,2 Phenolic compounds are hazardous to human health even at low concentrations, which includes diarrhea, corrosive to eye and skin, convulsions, liver damage, and even death.3 Industrial wastewater not only contains phenolic compounds, but a significant amount of organic dye is also present.4 A very small concentration of dye in water can change the color and odor significantly which has an evil effect on the aquatic environment. It prevents the light from reaching the aquatic life and hampers the photosynthesis process.5 MB is harmful to human beings; it causes dermatitis, skin allergies, and damage to the kidney, liver, and nervous system.6 It is difficult to remove these organic effluents due to their aromatic structures which are biologically nondegradable. However, their degradation products are mutagenic or carcinogenic. Various methods have been used for the removal of phenol and methylene blue from wastewater. They are of two types, one is destructive such as ozone and enzyme treatments,7 electrochemical oxidation,8 etc., and another one is nondestructive such as adsorption,9 biosorption,10 ion exchange,11 photolysis,12,13 extraction,14 etc. Previous studies suggested that adsorption is the most effective technique because of its easy availability, low cost, simplicity in design, and high efficiency. For a few decades, many adsorbents have been used for wastewater treatment, such as clay, zeolite, resins, silica gel, alumina, nanohydrogels, carbonaceous material, etc.15−18 © XXXX American Chemical Society

Among them, nanoporous carbon is the most effective adsorbent due to the presence of a well-organized pore structure, large surface area, thermochemical stability, and good mechanical properties.19 Preparation of cost-effective and potential porous carbons has attracted researchers in recent years for water treatment applications. Porous carbon materials with hierarchical porosity (micro-, meso-, or macropores) are synthesized in the presence of many inorganic templates.20,21 Very recently, Xiong et al. have synthesized nitrogen doped hierarchical porous carbon using F127 as coblock polymers.22 Carbonaceous materials with high porosity act as efficient adsorbents due to its high surface activity and porous nature. In the present study, we have synthesized hierarchical porous carbon nanospheres in the presence of different triblock copolymers (TBCs), namely, F108, F127, and L64, as soft templating agents. Hierarchical porous materials represent different types of pore systems that have sizes in distinctly different ranges. In the present case, the synthesized carbon samples contain different types of pores in the micropore (≤2 nm) and mesopore (2−50 nm) ranges. In this work, we have investigated the effects of different triblock copolymers (TBCs) having different hydrophilic−lipophilic balance (HLB) values and chain lengths (poly(ethylene oxide) (PEO)/poly(propylene oxide) (PPO) ratio) of the synthesized nanoporous carbons toward the change of their textural properties (BET surface area, pore size, etc.) influencing the relative adsorption efficiency for the removal of phenol and MB from water. Received: August 22, 2017 Accepted: December 26, 2017

A

DOI: 10.1021/acs.jced.7b00745 J. Chem. Eng. Data XXXX, XXX, XXX−XXX

Journal of Chemical & Engineering Data

Article

2. EXPERIMENTAL SECTION 2.1. Materials. Phenol, formaldehyde, NaCl, Na2SO4, Na3PO4, NaOH, and methylene blue (MB) were purchased from Merck, India, while triblock copolymers (F108, F127, and L64) were obtained from Sigma-Aldrich. Deionized water was used throughout the experiment. 2.2. Synthetic Procedure. In a typical experiment, 0.6 g of phenol and 2.1 mL of formaldehyde were mixed with 15 mL of NaOH solution (0.1 M), and stirred for 30 min at 70 °C. A 15 mL portion of aqueous solution of 0.07 mmol of triblock copolymers (F108, F127, and L64) was separately prepared and added to the previous solution. These solutions are kept at 65 °C for 2 h under stirring. After 2 h, 50 mL of water was poured into the solution. During this reaction time, the color of the solution changes in the sequence of colorless to red and finally to crimson red in the presence of F108 and F127, while colorless to pink to wine red in the presence of L64. After 15− 18 h, a lump deposit was noticed in each case, which disappeared after continuous stirring. Then, 18 mL of each solution was diluted with 56 mL of water, and transferred into a Teflon-lined autoclave. The autoclave was placed in an oven at 130 °C for 24 h. After the reaction, the products were collected by centrifugation followed by washing with water and dried at room temperature. The dried samples were carbonized under a controlled N2 atmosphere at a flow rate of 40 mL/min at 700 °C for 3 h with a heating rate of 4 °C/min. The synthesized samples were designated as CF108, CF127, and CL64 corresponding to the triblock copolymers F108, F127, and L64 used during the synthesis procedure. 2.3. Characterization. Low angle X-ray diffraction (XRD) was performed by a Rigaku Smartlab instrument (9 kW) using Cu Kα radiation (λ = 0.15418 nm) at 45 kV and 200 mA. The Raman spectra were recorded using a RENISHAW spectrometer at 514 nm radiation from an argon laser at room temperature. The BET (Brunauer−Emmett−Teller) surface area of the samples was analyzed by nitrogen adsorption− desorption measurements at 77 K with a Quantachrome (ASIQ MP) instrument within a relative pressure (P/Po) range of 0.05−0.20. Prior to measurement, powders were outgassed in a vacuum at 250 °C for 4 h. The Barrett−Joyner−Halenda (BJH) method was used to calculate pore size distributions in the mesopore range, while microporosity was determined by the NLDFT (nonlinear density functional theory) method. The pore volume was estimated from nitrogen adsorption volume at a relative pressure (P/Po) of 0.99. FESEM (model: Zeiss, Supra 35VP, Oberkochen, Germany) operating with an accelerating voltage of 10 kV and TEM (Tecnai G2 30ST (FEI)) operating at 300 kV were used to investigate the morphology and microstructure of the particles. A UV−vis spectrophotometer (Jasco V-730) was used to record UV−visible spectra within the wavelength range from 195 to 700 nm. 2.4. Adsorption Experiments. Adsorption experiments were carried out at 25 °C using a thermostat shaker. Adsorbent concentrations were varied from 1 to 0.1 g/L for all three samples with initial phenol and MB concentrations of 10−4 and 10−5 M, respectively. After a specified time, adsorbents were separated from aqueous solution by filtration. The concentration of pollutant water (filtrate) was measured using a UV− vis spectrophotometer at a specific time interval. The absorbance values were measured at adsorbent maxima of the respective pollutants. The amount (qt in mg/g) and % of

pollutants (phenol and MB) adsorbed by the samples were calculated by the following equations.

qt = (Co − C t) ·V /m

(1)

% of pollutants adsorbed = (Co − Ce)/100Co

(2)

where Co, Ct, and Ce are the concentrations of pollutant (mg/ L) at initial time, at time t, and at equilibrium time, respectively. V is the volume (mL) of the solution, and m is the mass of the adsorbent in g. For the kinetic experiment, 10 mL of each contaminant (10−4 M of phenol and 10−5 M MB) was mixed with 10 mg of the carbon samples. The decrease in absorption intensity for phenol and MB with time indicates the adsorption of the corresponding pollutants. Here, kinetic data was fitted with the linear form of the pseudo-first-order (eq 3) and pseudo-secondorder models (eq 4) ln(qe − qt) = −k1t + ln qe

(3)

t /qt = 1/k 2qe 2 + (1/qe)t

(4)

where qe and qt (mg g−1) are the amounts of pollutants adsorbed at equilibrium and time t (min), respectively, while k1 (min−1) and k2 (g mg−1 min−1) are the first-order and secondorder rate constants, respectively. Surface properties of adsorbent and affinities between adsorbent and adsorbate are determined from the parameters obtained from different isotherm models (initial concentration of phenol and MB was 10−4 and 10−5 M, respectively, adsorbent concentration varied from 1 to 0.1 g/L, temperature 30 °C). In this purpose, the adsorption data were fitted with Langmuir, Freundlich, Temkin, and Dubinin−Radushkevich models. According to the Langmuir isotherm model, the adsorption layer is a homogeneous and monomolecular layer. The Langmuir equation is represented as qe = qmbCe/(1 + KLCe)

(5)

The linear form of the Langmuir isotherm is expressed as Ce/qe = Ce/qm + 1/KL ·qm

(6)

where qe is the amount of pollutant adsorbed per 1 g of carbon sample (mg/g), qm is the maximum single layer adsorption capacity (mg/g), Ce is the unadsorbed amount of pollutant left at equilibrium (mg/L), and KL is the adsorption constant related to free energy and adsorption enthalpy (L/mg). A linear plot of Ce/qe versus Ce indicates compatibility of adsorption with the Langmuir model. qm and KL can be calculated from the slope and intercept of the curve, respectively. The Freundlich isotherm model represents the nonuniform distribution of heat of adsorption over the heterogeneous surface, as expressed by the following equation log qe = log KF + 1/nF log Ce

(7)

where KF and nF are the constant associated with the adsorption capacity and the numerical parameter related to the adsorption intensity, respectively. A straight line is obtained from the graph of log Ce vs log qe, where KF and 1/nF are measured from the intercept and slope of the plot. The Temkin model provides the information about the uniform distribution of binding energies. The parameters of the model are obtained from the plot of qe vs ln Ce. The Temkin isotherm model is expressed as B



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Figure 1. (a) Raman spectra and (b) low angle XRD of porous carbon nanospheres.

Table 1. Textural Properties of Porous Carbon Nanospheres surface areaa (m2 g−1)

a

sample

SBET

Smicropore

Smesopore

Vp‑Totalb (cm3 g−1)

average pore diameter (nm)

d(100) (nm)

ao (nm)

pore wall thickness (W) (nm)

CF108 CF127 CL64

751.6 757.3 596.6

505.3 489.9 500.5

246.3 267.3 96.1

1.155 0.995 0.457

6.145 5.255 3.068

12.71 12.9 13.57

14.67 14.89 15.66

8.52 9.63 12.59

BET, micropore and mesopore surface area. bTotal pore volume.

Figure 2. N2 adsorption−desorption isotherms of porous carbon nanospheres: (a) CF108, (b) CF127, and (c) CL64.

qe = RT /b ln(A TCe)

(8)

qe = RT /bT ln A T + (RT /b) ln Ce

(9)

K), absolute temperature, and constant related to heat of sorption (J/mol), respectively. The Dubinin−Radushkevich (DR) isotherm describes the adsorption process on a heterogeneous surface related to Gaussian energy distribution. The equation of DR isotherm is expressed as

B = RT /bT

(10)

qe = B ln A T + B ln Ce

(11)

qe = qs exp( −BDε 2)

(12)

where AT, bT, R, T, and B are the equilibrium binding constant (L/g), isotherm constant, universal gas constant (8.314 J/mol/

ln qe = ln qs − BDε 2

(13)

C



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Figure 3. Pore size distributions of porous carbon nanospheres: (a) CF108, (b) CF127, and (c) CL64 by the BJH method. The insets show pore size distributions by the DFT method.

(16)

desorption isotherms of the samples (a) CF108, (b) CF127, and (c) CL64 are shown in Figure 2. The isotherms represent the hierarchical pore structure comprised of micropores and mesopores in carbon samples. The curves show pseudotype-1 isotherms with an H1 hysteresis loop.24−26 The microporosity is confirmed by a steep rise in isotherm at low relative pressure, while the increase in adsorption at higher relative pressure (P/ Po ≥ 0.9) could be attributed to N2 condensation in the interstitial voids among the carbon particles.27,28 For the samples (a) CF108, (b) CF127, and (c) CL64, the BJH pore size distributions in the mesopore range are depicted in Figure 3 (the insets show the pore size distributions in the micropore range as determined by the NLDFT method). The curves (Figure 3) reflect that, in the mesopore region, the pore size varies from 3 to 12 nm, while, in the micropore region, the pore size varies from 0.75 to 2 nm for all of the samples. It indicates the nonuniformity in pore size in both mesopore and micropore ranges. The textural properties (BET surface area, pore volume, pore diameter) of the samples are shown in Table 1. Interestigly, the BET surface area of the samples CF108 and CF127 is comparable, while it is decreased for CL64. However, the total pore volume and pore size of the samples decreased in the order of CF108 > CF127 > CL64. Table 1 also shows that d(100), ao, and W increased in the order of CF108 < CF127 < CL64. It is worth noting that physical properties of the TBCs (Table 2) could have an influence on the textural properties,

(17)

Table 2. Physical Properties of Triblock Copolymers Used for Synthesis of Porous Carbon Nanospheres

ε = RT ln(1 + 1/Ce)

(14)

E = 1/ 2 BD

(15)

where qs, BD, and ε are the isotherm saturation capacity (mg/ g), Dubinin−Radushkevich isotherm constant (mol2/kJ2), and potential energy, respectively.

3. RESULTS AND DISCUSSION 3.1. Characteristics of Porous Carbon Nanospheres. Figure 1a shows the Raman spectra of the samples CF108, CF127, and CL64. The appearance of two peaks at 1344 and 1592 cm−1 is corroborated with the D and G bands, respectively.23 The D band signifies the presence of disorder structure in porous carbon materials, and the G band represents the vibration of the C−C bond with the sp2 electronic configuration of carbon atoms. Another broad peak from 2500 to 3000 cm−1 was observed for all three samples, which is due to the G″ band, also known as the overtone of the D band. Figure 1b shows the low angle XRD patterns of the samples, CF108, CF127, and CL64. The 2θ values are observed at 0.70, 0.68, and 0.64° for the samples CF108, CF127, and CL64, respectively, corresponding to their d100-spacing of 12.71, 12.90, and 13.57. The ao values (unit cell parameter) were calculated from the given equation: ao = d(100) × 2/ 3

The pore wall thickness (W) is calculated as W = ao − pore diameter

The unit cell parameter (ao) is determined by the powder X-ray diffraction method, and the pore wall thickness (W) is calculated on the basis of the BJH model. The d spacing values (d(100)), unit cell parameters (ao), and pore wall thickness (W) are shown in Table 1. N2 adsorption− D

molecular structure

molecular weight

PEO/PPO

HLB value

F108 (PEO133PPO50PEO133) F127 (PEO106PPO70PEO106) L64 (PEO13PPO30PEO13)

14600 12600 2900

5.32 3.03 0.87

27 18−23 12−18



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Figure 4. FESEM images of porous carbon nanospheres: (a) CF108, (b) CF127, and (c) CL64.

efficiency of the materials for the removal of phenol and MB from water. Figure 4 shows the FESEM images of the samples (a) CF108, (b) CF127, and (c) CL64; the corresponding high magnified images are shown with an arrow. Spherical nanoparticles were obtained for all of the samples. The size of the particles for the samples CF108 and CF127 was in the range 60−100 nm, while a bit larger particles with a wide size distribution in the range 50−200 nm were found for the sample CL64. Figure 5 shows the TEM microstructure of the samples (a) CF108, (b) CF127, and (c) CL64; the corresponding high magnified images are shown with a arrow. It also confirmed the size and spherical shape of the particles as revealed by the FESEM images. The porous nature of the carbon particles is evident from the high magnified TEM images. 3.2. Adsorption Studies of Phenol and MB. 3.2.1. Effect of Contact Time. The effect of contact time for the adsorption of phenol and MB is significant for assessing the adsorption capacity of the adsorbents (porous carbon nanospheres). The

lattice spacing, cell parameters, and pore wall thickness of the porous carbon materials. With increasing HLB values and PEO/PPO ratio of the TBCs, hydrophilicity of the TBCs increased in the order of L64 < F127 < F108. During synthesis, phenol and formaldehyde form resol,29,30 a soluble low molecular weight polymer under base catalyzed polymerization reaction. With the progress of reaction, resol-TBC micelles are formed through hydrogen bond interaction. Hydrophilicity of TBCs enhanced the hydrogen bond interaction, rendering an increase in the pore size and pore volume of the porous carbon in the order of CL64 < CF127 < CF108. It also affects decreasing lattice spacing, cell parameters, and pore wall thickness in the order of CL64 > CF127 > CF108. Interestingly, the BET surface area, mesopore surface area, pore volume, and pore size of CL64 are significantly low compared to those of the samples CF108 and CF127 because of lower values of molecular weight, HLB, and PEO/PPO ratio of L64. These textural properties strongly affect the adsorption E



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Figure 5. TEM images of porous carbon nanospheres: (a) CF108, (b) CF127, and (c) CL64.

Figure 6. UV−vis spectra of phenol adsorption at different times of porous carbon nanospheres: (a) CF108, (b) CF127, and (c) CL64.

UV−vis spectra of phenol (initial concentration: 10−4 M) and MB adsorption (initial concentration: 10−5 M) with irradiation time at 25 °C are represented in Figures 6 and 7, respectively, for the samples CF108, CF127, and CL64. Parts a and b of Figure 8 show the percentage removal of phenol and MB, respectively, with time for all of the samples. Interestingly, for

the samples CF108 and CF127, the adsorption of phenol and MB sharply increased within 5 min followed by a slow change up to 15 min. However, for the sample CL64, the adsorption of phenol and MB changes steadily even after 5 min. A very fast adsorption of organic pollutants at the initial stage is due to the presence of a large number of available active adsorption sites F



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Figure 7. UV−vis spectra of MB adsorption at different times of porous carbon nanospheres: (a) CF108, (b) CF127, and (c) CL64.

Figure 8. Percentage of (a) phenol and (b) MB adsorption with time of porous carbon nanospheres: CF108, CF127, and CL64.

Figure 9. Adsorption isotherm obtained for adsorption of phenol with change in adsorbent amount of porous carbon nanospheres: (a) CF108, (b) CF127, and (c) CL64.

Figure 10. Adsorption isotherm obtained for adsorption of MB with change in adsorbent amount of porous carbon nanospheres: (a) CF108, (b) CF127, and (c) CL64.

in the porous carbon samples. However, the number of available active adsorption sites is becoming less near equilibrium stage because of the repulsive force acting between the adsorbed organic pollutants (phenol and MB) onto the adsorbent (porous carbon nanosphere) and the same unadsorbed pollutants in the solution stage. The initial rapid

adsorption of pollutants on the surface of the carbon nanospheres can also be explained thermodynamically by using the following equation Γ1 = −(dγ /dμ1) G

(18) DOI: 10.1021/acs.jced.7b00745 J. Chem. Eng. Data XXXX, XXX, XXX−XXX


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Figure 11. Adsorption isotherm obtained for adsorption of (a) phenol and (b) MB with change in adsorbate concentration of porous carbon nanospheres CF108, CF127, and CL64.

Table 3. Comparison of the Adsorption Capacity (qm) of Porous Carbon Nanospheres with Other Different Adsorbents for Phenol and MB Adsorption phenol

MB

sample

qm (mg/g)

ref. no.

sample

qm (mg/g)

ref. no.

activated carbon (ACK1) c-Fe2O3/2C nanocomposite orange peel coffee residue derived carbon seeds derived carbon commercial activated carbon sugar cane bagasse fly ash CF108 CF127 CL64

17.8 42.3 88 88.31 90 49.72 23.83 99 94.25 75

32 33 34 35 36 37 38 present work present work present work

cellulose-based wastes activated carbon carbon nanotubes graphene/magnetite composite rattle-type magnetic carbon nanospheres Delonix regia pods derived activated carbon acid activated carbon CF108 CF127 CL64

20.8 47.62 64.7 43.82 45.15 24 60.61 68.49 30.86 20.83

39 40 41 42 43 44 45 present work present work present work

where Γ1 is the surface excess (mass adsorbed per unit surface area of adsorbent), γ is the surface tension, and μ is the chemical potential of adsorbate (pollutants). Organic adsorbates reduce the surface tension of water. With a decrease in surface tension, Γ is increased. Therefore, at the initial stage of adsorption due to the high concentration of the pollutants, the surface excess is enhanced, leading to the higher adsorption of organic pollutants on porous carbon. A complete adsorption (100%) of phenol and MB took place at 15 and 10 min, respectively, for the sample CF108. For the sample CF127, the maximum percentage adsorption of phenol (96.3%) and MB (99%) occurred at 30 and 15 min, respectively. The sample CL64 rendered a maximum 84.6% of phenol and 84.2% of MB adsorption at 30 min each. The kinetics of adsorption of both pollutants was fitted with both the pseudo-first-order (Figures S1 and S2, Supporting Information) and pseudo-second-order models (Figures S3 and S4, Supporting Information), and the values of qe, K2, and R2 are shown in Table S1. Values of R2 indicate that the data were well fitted with the pseudo-secondorder model where the chemisorption process is the ratedetermining step. From the above study, it is revealed that the % adsorption of phenol and MB is higher for the samples CF108 and CF127 compared to CL64. The increased surface area, pore volume, and pore size of CF108 and CF127 could be the reason for their higher adsorption capacity. 3.2.2. Effect of Adsorbent Dosage and Adsorbate Concentration. The adsorption of phenol and MB was studied by varying the amount of adsorbent (0.1−1 g/L). The maximum adsorption capacities of the samples were obtained from the qe vs Ce plot (Figures 9 and 10 for the adsorption of

phenol and MB, respectively). With increasing adsorbent dosage, the adsorption of pollutants increased, which is due to the increased number of available adsorption sites.31 For both pollutants, the maximum adsorption capacities (qm) of the samples followed in the order of CF108 > CF127 > CL64, which can be explained by the same order of pore volume and pore size of the samples. It is to be noted that CF108 shows the maximum adsorption capacities (qm) of 57.5 and 21.6 mg/g for phenol and MB, respectively, obtained from variation of adsorbent doses. The adsorption capacity of phenol and MB was also studied by changing the concentration of adsorbate. For phenol, the concentration was varied from 10−4 to 5 × 10−4 M, whereas, for MB, the varied concentration was 10−5 to 10−4 M. It was observed that with increasing concentration of the pollutants the adsorption capacity increases up to 5 × 10−4 M for phenol and 10−4 M for MB (where the adsorbent dose is 0.2 g/L); further increase in pollutant concentration showed no change in adsorption capacity. With an increase in initial pollutant concentration, the driving force for the mass transfer increases lead to a higher adsorption capacity. The corresponding qe vs Ce plots are shown in Figure 11, and the maximum adsorption capacity is tabulated in Table S2, Supporting Information. qm (maximum adsorption capacity) for phenol adsorption capacity was found to be 99, 94.25, and 75 mg/g for CF108, CF127, and CL64, respectively. For MB, the maximum adsorption capacity was observed to be 68.49, 30.86, and 20.83 mg/g for CF108, CF127, and CL64, respectively. Table 3 shows a comparative study of phenol and MB adsorption by different adsorbents and our synthesized hierarchical porous carbon nanosperes. It is to be noted that CF108 shows the H



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Figure 12. Adsorption capacity of porous carbon nanospheres with temperature for adsorption of phenol at concentrations of (a) 10−4 M, (b) 1.5 × 10−4 M, and (c) 2.5 × 10−4 M and for MB at concentrations of (d) 10−5 M, (e) 5 × 10−5 M, and (f) 10−4 M.

Figure 13. Adsorption of (a) phenol and (b) MB with pH of porous carbon nanospheres: CF108, CF127, and CL64.

maximum adsorption capacities (qm) of 99 and 68.49 mg/g for phenol and MB, respectively, which are better than the previously reported data on carbon and carbon-based materials.32−45 3.2.3. Effect of Temperature. The effect of temperature for the adsorption of phenol and MB at different initial concentrations is shown as a bar diagram in Figure 12. For

all of the samples, the % adsorption decreased in the order of CF108> CF127> CL64 for each temperature with an exception at 330 K for phenol adsorption at 10−4 M. Interestingly, for the adsorption of phenol, the adsorption capacity decreased with increasing temperature for each sample. It contradicts the normal adsorption phenomena on the temperature effect. For phenol adsorption on a carbon surface, heat is evolved,46 I



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Figure 14. Adsorption of (a) phenol and (b) MB in the presence of different coexisting ions onto porous carbon nanospheres: CF108, CF127, and CL64.

Table 4. Parameters Obtained from Langmuir, Freundlich, Temkin, and Dubinin−Radushkevich Models Varying the Adsorbent Concentration adsorption of phenol

adsorption of MB

Langmuir

Langmuir 2

sample ID

qm(mg/g)

KL (L/mg)

R

CF108 CF127 CL64

57.5 51.2 25.5

1.23 0.19 0.26 Freundlich

0.962 0.822 0.868

sample ID

nF

CF108 CF127 CL64

1.7 1.4 1.9

sample ID

AT (L/mg)

CF108 CF127 CL64

4.1 3.6 2.8

sample ID CF108 CF127 CL64

qs (mg/g) 227 23.8 40.44

KF 24.5 17.4 8.9 Temkin bT

BD (mol2/kJ2) −5

1.8 × 10 4.49 × 10−7 1.35 × 10−7

10.5 2.6 3.2 Freundlich

nF

KF (mg/g)

0.989 0.980 0.850

2.3 2.2 4.7

23.3 13.3 3.9 Temkin

R2

AT (L/mg)

0.993 0.946 0.886

57.8 50.1 124

R2

E (kJ/mol) 0.164 1.053 1.924

21.6 16.5 8.7

qs (mg/g)

0.999 0.864 0.857

23.8 12.8 5.79

R2

KL (L/mg)

R2

B

123.2 20.4 141.5 17.8 318 7.9 Dubinin−Radushkevich

qm (mg/g)

bT

0.988 0.956 0.999 R2 0.954 0.971 0.832 B

464 5.42 719 3.5 2915 0.86 Dubinin−Radushkevich BD (mol2/kJ2) −8

2.6 × 10 1.99 × 10−8 7.8 × 10−8

R2 0.989 0.932 0.867

E (kJ/mol)

R2

4.384 5.011 2.531

0.998 0.895 0.991

the electrostatic repulsion between the phenolate ions and negatively charged carbon surface reduces the adsorption of phenol. However, the maximum adsorption of phenol at neutral pH is due to the formation of hydrogen bonding between phenol molecules and the carbon surface having adsorbed water molecules (the reaction mechanism is discussed in section 3.2.8). Interestingly, adsorption of MB increased with an increase in pH (Figure 13b). At lower pH, the positively charged surface of carbon hinders the adsorption of cationic dye MB, while, with an increase in pH, the negatively charged surface of carbon facilitates the uptake of cationic dye MB via electrostatic attraction and/or hydrogen bonding (the reaction mechanism is discussed in section 3.2.8). 3.2.5. Effect of Coexisting Ions. The effect of different coexisting ions such as chloride, sulfate, and phosphate (corresponding sodium salt solutions) upon the adsorption of both phenol and MB was studied, and it is shown in parts a and b of Figure 14, respectively. The initial ion concentration was taken as 10 mg/L at pH 7 with a contact time of 30 min at 30 °C. Figure 14 shows that the coexisting ions adsorbed on the porous carbon to a little extent, rendering a slight decrease in

resulting in a lower kinetic energy for diminishing the adsorption process. With an increase in temperature, water adsorption on the carbon surface increases, forming a hydration layer which could inhibit the π−π interactions between phenol molecules (Figure S3a, Supporting Information) and the carbon surface.47 Therefore, enhancement of thermal energy weakens the attractive forces between phenol and adsorbent, which leads to the decrease in adsorption capacity.48 However, due to the presence of a higher number of π rings in MB (Figure S3b, Supporting Information), the hydration layer of carbon is competing with the stronger π−π interactions between MB and carbon active sites. Therefore, for MB adsorption, the % adsorption could not increase significantly with temperature. 3.2.4. Effect of pH. The effect of pH on the adsorption of phenol and methylene blue is shown in parts a and b of Figure 13, respectively. It was observed that adsorption of phenol was lower in acidic and alkaline pH, and became maximum in neutral pH (Figure 13a). At very low pH, the adsorbent (carbon) surface is positive, which could suppress its intake capacity to adsorb protonated phenol. Similarly, in alkaline pH, J



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The ΔG° value was calculated from the following equation.

the adsorption of both organic pollutants, phenol and MB. It is demonstrated that coexisting ions has a nominal effect on the adsorption of phenol and MB. 3.2.6. Adsorption Isotherm. The data of adsorption for phenol and MB were fitted with four adsorption isotherm models such as Langmuir (Figures S6 and S7, Supporting Information), Freundlich (Figures S8 and S9, Supporting Information), Temkin (Figures S10 and S11, Supporting Information), and Dubinin−Radushkevich (Figures S12 and S13, Supporting Information) varying the adsorbent dosage. The parameters obtained from the isotherm and the best fitted model were represented in Table 4. The heterogeneity factor (nF) was calculated from the slope of the Freundlich isotherm plot. All of the samples show the value of nF in between 1 and 10, which indicates the favorable adsorption for both phenol and MB.49 The well fitted isotherms for the samples were tabulated in Table 5. It is observed that CF108 and CF127

ΔG° = −RT ln Kd

The values of ΔG°, ΔH°, and ΔS° are shown in Table 6. The negative value of ΔH° indicated that the adsorption process is exothermic. The positive ΔS° values indicate the increase in the randomness at the solid/liquid interface during the adsorption process.50 ΔG° values are different for different temperatures. The negative ΔG° value for all of the samples at different temperatures signifies the feasible and spontaneous adsorption.51 For the adsorption of phenol, −ΔG° values decreased with temperature, and thus, spontaneity of phenol adsorption decreases (S20, Supporting Information, Figure 12). However, for MB adsorption, with an increase in temperature, adsorption capacity is increased, as revealed by the increased −ΔG° value, indicating the spontaneity of the adsorption process (S21, Supporting Information, Figure 12).52,53 It is to be noted from the thermodynamic parameters that the order of adsorption efficiency for phenol and MB followed as CF108 > CF127 > CL64. 3.2.7. Selective Adsorption. The adsorption capacity of the samples was carried out in the presence of both phenol and MB. Figure 15 shows (a) UV−vis spectra for the adsorption of both phenol and MB and (b) the bar chart indicating % adsorption and selective adsorption of phenol and MB for different samples. It was observed that CF108 and CF127 showed comparable adsorption of phenol and MB (concentration of phenol and MB 10−5 M), while CL64 indicates a higher selectivity for the adsorption of phenol. Due to the presence of a higher microporosity with respect to mesoporosity and a smaller pore size of the sample CL64, it exhibits lower selectivity for the adsorption of bulky MB compared to phenol adsorption. On the other hand, the samples CF108 and CF127 reveal comparable adsorption for both phenol and MB due to the presence of a large abundance of mesoporosity and larger pore size. To study the effective selectivity of the samples, the higher concentration of phenol and MB, i.e., 2.5 × 10−5 M, was taken for the adsorption study (Figure 15). It was observed that 16% MB and 31% phenol were adsorbed by CL64 and 32% MB and 50% phenol were adsorbed by CF127, while, for CF108, 85% MB and 72% phenol were adsorbed. It suggests that, at a high concentration of the pollutants, phenol is adsorbed more effectively than MB for CL64 and CF127, while CF108 renders nearly the same adsorption for phenol and MB. The regeneration of the samples was carried out by washing the pollutant adsorbed samples with distilled water several

Table 5. Matching of Isotherms for the Samples of Different Adsorbed Pollutants sample ID

pollutant adsorbed

isotherm matched

CF108

phenol MB phenol MB phenol MB

Temkin Temkin Freundlich Freundlich Temkin/Langmuir Langmuir

CF127 CL64

followed Temkin and Freundlich isotherm models for both pollutants, respectively. However, CL64 followed both Temkin and Langmuir isotherms for adsorption of phenol, whereas the Langmuir isotherm model was well fitted for the adsorption of MB. The adsorption study with different initial concentrations of the pollutants was also carried out, and data were fitted with different isotherm models (Figures S14−S19, Supporting Information) and data were tabulated in Table S2, Supporting Information. The distribution coefficient (Kd) is an important factor for determination of the thermodynamic parameters such as ΔG° (the change in free energy), ΔH° (the change in enthalpy), and ΔS° (the change in entropy). ΔH° and ΔS° (Figures S20 and S21, Supporting Information) values were obtained from the slope and intercept of the plot of ln Kd versus 1/T (eq 20).

Kd = qe /Ce

(19)

ln Kd = ΔS°/R − ΔH °/RT

(20)

(21)

Table 6. Thermodynamic Parameters of Phenol and MB Adsorption on Porous Carbon Nanosphere Samples at Different Temperatures phenol adsorption sample ID

ΔH° (J/mol)

ΔS° (J/mol/K)

CF108

−73001.9

208.76

CF127

−48029.9

129.86

CL64

−4652

5.59

MB adsorption ΔG° (kJ/mol) −9.746 −5.545 −3.491 −8.879 −5.365 −5.276 −2.911 −3.004 −2.678

at at at at at at at at at

30 50 60 30 50 60 30 50 60 K

K K K K K K K K K

ΔH° (J/mol)

ΔS° (J/mol/K)

ΔG° (kJ/mol)

−60619

236.19

−51022

192.6

−10.702 at 30 K −16.505 at 50 K −17.441 at 60 K −7.62 at 30 K −10.29 at 50 K −13.779 at 60 K −2.299 at 30 K −3.70 at 50 K −4.169 at 60 K

−16969

63.68



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Figure 15. (a, c) UV−vis spectra for the adsorption of both phenol and MB and (b, d) the bar chart indicating % adsorption and selective adsorption of phenol and MB for different samples.

Figure 16. Maximum adsorption capacity values (qm) for the adsorption of phenol (a, b, and c) and MB (d, e, and f) on the samples CF108, CF127, and CL64, respectively, in five consecutive cycles.

To confirm the adsorption of phenol and MB on a porous

times to remove the adsorbed pollutants. A recyclability test was performed with the regenerated samples for up to five cycles. It was observed that the maximum adsorption capacity (qm) for both pollutants remained almost the same up to three cycles followed by a gradual decrease of adsorption capacity for the consecutive fourth and fifth cycles (Figure 16).

carbon nanosphere, FTIR, FESEM/EDS, and N2 adsorption− desorption studies were performed on the phenol and MB adsorbed samples denoted as CF108-P, CF127-P, and CL64-P (for phenol) and CF108-M, CF127-M, and CL64-M (for MB) L



Article

Figure 17. Chemisorption mechanism of phenol and MB for different samples.

values and PEO/PPO ratio of the TBCs, the hydrophilicity of the TBCs increased in the order of L64 < F127 < F108, which rendered an increase in the pore size and pore volume of the porous carbon in the order of CL64 < CF127 < CF108. The sample CF108 shows maximum adsorption capacities of 99 and 68.49 mg/g for phenol and MB, respectively, with respect to different adsorbate concentrations, which are better than the previously reported data. From the study of thermodynamic parameters, it is revealed that the adsorption efficiency for phenol and MB followed as CF108 > CF127 > CL64 on the basis of their pore volume and pore size. Due to the presence of a higher microporosity with respect to mesoporosity and the smaller pore size of the sample CL64, it exhibits lower selectivity for the adsorption of bulky MB compared to phenol adsorption. The present study is helpful in designing the synthesis of porous carbon based materials in terms of their textural properties for the removal of multiple toxic pollutants from industrial effluents, which is important from an environmental point of view.

for the corresponding parent samples of CF108, CF127, and CL64. Figure S22, Supporting Information, shows the FTIR spectra of phenol and MB adsorbed samples along with the parent samples (before adsorption). Interestingly, after phenol adsorption for all of the samples, the peak at around 3450 cm−1 shifted to around 3420 cm−1 which is due to the O−H stretching in phenol. However, in the case of MB adsorbed samples, there is no significant change in absorption bands. The FESEM images of the samples after adsorption of phenol (Figure S23, Supporting Information) and MB (Figure S24, Supporting Information) confirmed that the morphology of the samples remains the same with the parent samples before adsorption. However, EDS of MB adsorbed samples show the presence of Cl and S (Figure S24, Supporting Information) which confirmed that MB is adsorbed in the samples. Figures S25 and S26, Supporting Information, show the BET isotherms of the phenol and MB adsorbed samples, respectively. The BET surface area data are shown in Table S3. It is noticed that, after adsorption of phenol and MB, the BET surface area decreased in all of the samples. During adsorption, some micropores could be blocked by the adsorbed pollutants which caused the reduction of surface area. The significant reduction of micropore surface area is revealed from Table S3. 3.2.8. Adsorption Mechanism. A possible mechanism for the chemisorption process is shown schematically in Figure 17. For the adsorption of phenol on the porous carbon surface, different kinds of interaction like hydrogen bonding, π−π interactions, and electron donor−acceptor complex mechanism could take place.54,55 At very low pH, the positive surface charge of carbon hinders the adsorption of protonated phenol. Similarly, in alkaline pH, the electrostatic repulsion between the phenolate ions and negatively charged carbon surface reduces the adsorption of phenol. However, π−π interactions of phenol molecules and carbon render their adsorption to a little extent at very low and high pH. However, the maximum adsorption of phenol at neutral pH is due to the formation of hydrogen bonding between phenol molecules and the carbon surface having adsorbed water molecules. For the adsorption of MB, the positive charged surface of carbon could suppress its intake capacity to adsorb a cationic dye, MB. However, with an increase in pH (pH ≥ 7), the negatively charged surface of carbon facilitates the uptake of cationic dye, MB, via electrostatic attraction and/or hydrogen bonding.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jced.7b00745. Pseudo-first-order kinetic plots for the adsorption of phenol; pseudo-first-order kinetic plots for the adsorption of MB; pseudo-second-order kinetic plots for the adsorption of phenol; pseudo-second-order kinetic plots for the adsorption of MB; structures of (a) phenol and (b) methylene blue (MB); Langmuir, Freundlich, Temkin, and Dubinin−Radushkevich isotherms for phenol and MB adsorption with different adsorbent doses; Langmuir, Freundlich, and Temkin isotherms for phenol and MB adsorption with different adsorbate concentrations; plots of ln Kd versus 1/T for phenol and MB adsorption; FTIR, FESEM, EDX, and N2 adsorption−desorption studies; parameters of the kinetic model for the adsorption of phenol and MB; parameters obtained from Langmuir, Freundlich, and Temkin using different adsorbate concentrations; surface area of porous carbon nanospheres after phenol and MB adsorption (PDF)

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Phone: +91 33 2473 3496 (Ext. 3516).

4. CONCLUSION In summary, the hierarchical porous carbon nanospheres were synthesized using a soft templating method in the presence of different TBCs (F108, F127, and L64). With increasing HLB

ORCID

Milan Kanti Naskar: 0000-0002-7447-4941 M



Article

Notes

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The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors are grateful to the Director of this institute for his kind permission to pursue this work. S.K. and I.H.C. are gratified to AcSIR and UGC, Government of India, respectively, for their fellowships.

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Hierarchical Porous Carbon Nanospheres for Efficient Removal of

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