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Langmuir 2006, 22, 4574-4582
Roles of the Textural and Surface Chemical Properties of Activated Carbon in the Adsorption of Acid Blue Dye M. Valix,*,† W. H. Cheung,†,§ and G. McKay‡ Department of Chemical Engineering, UniVersity of Sydney, NSW 2006, Australia, and Department of Chemical Engineering, Hong Kong UniVersity of Science and Technology, Clear Water Bay, Kowloon, Hong Kong ReceiVed June 26, 2005. In Final Form: March 14, 2006 This study has demonstrated the use of empirical modeling in resolving the effects of individual carbon properties on acid blue dye adsorption. Acid blue dye adsorption tests were conducted on activated carbons prepared from bagasse by physical (CO2) and chemical (ZnCl2, MgCl2 and CaCl2) techniques. Empirical models based on the carbon textural (surface area and pore size) properties and the surface chemistry inferred from heteroatom (C,H, N, and S) concentration and carbon surface pH were used to resolve the effects of individual carbon properties on acid blue dye adsorption. This form of analysis was conducted to optimize carbon preparation properties, forming the foundation for tailormaking adsorbents from bagasse suitable for acid dye adsorption. A series of statistical analyses (partial F-tests to establish the parameter significance) measured variants including the mean square error, r2 and adjusted r2, normality, and randomness of residuals, and formed the basis for testing the adequacy of these models. The empirical models suggest that a combination of suitable pore structure and distinct basic surface chemistry generated by sulfur- and nitrogen-based groups, which were also elucidated by Fourier transform infrared spectroscopy, is necessary to promote acid dye adsorption.
Introduction Synthetic organic dyes present hazards and environmental problems. Dye effluents are aesthetic pollutants that contain chemicals that exhibit toxic effects toward microbial populations and can be toxic and or/carcinogenic to organisms and mammals.1 Activated carbon is perhaps the most widely used adsorbent for the removal of dyes.2 Although adsorbents are used abundantly throughout the water and wastewater treatment industries, carbon adsorption remains an expensive process. This is associated with the high cost of producing activated carbons.3 Over recent years, this has attracted considerable research into low-cost alternative materials for the production of activated carbon from agricultural wastes for dye removal, such as apricot stones,3 bamboo,4 and plum kernels.5 Despite significant research in the production of activated carbons for dye adsorption, there appear to be no systematic methods in manufacturing adsorbents that would optimize the adsorption of particular effluents. This has largely been associated with inadequate understanding of the roles of the chemical and physical properties of activated carbon in dye adsorption. This study aims to use empirical modeling of dye adsorption capacities as a function of carbon properties as a basis for decoupling the effects of individual carbon characteristics to adsorption. Recent works reported 6,7 established the modeling * Corresponding author. Tel: +61 2 9351 4995. Fax: +61 2 9351 2854. E-mail:
[email protected]. † University of Sydney. ‡ Hong Kong University of Science and Technology. § Present address: Department of Chemical Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong. (1) Reife, A. EnVironmetal Chemistry of Dyes and Pigments; John Wiley and Sons: Mississauga, ON, Canada, 1995; Vol. 8. (2) Allen, S. J. Types of adsorbent materials. In Use of Adsorbents for the RemoVal of Pollutants from Wastewaters; CRC: Boca Raton, FL, 1996. (3) Khalil, L. B.; Girgis, B. S. Adsorpt. Sci. Technol. 1998, 16, 405-414. (4) Wu, F. C.; Tseng, R. L.; Juang, R. S. J. EnViron. Sci. Health, Part A: Toxic/Hazard. Subst. EnViron. Eng. 1999, 34, 1753-1775. (5) Wu, F. C.; Tseng, R. L.; Juang, R. S. J. Hazard. Mater. 1999, 69, 287-302.
strategy in tailor-making activated carbon for the recovery of gold from thiourea and cyanide complexes. The present study used this previous technique as a basis for developing activated carbons that would be suitable for removing Acid Blue 80 (AB80) dye from wastewater. In this study, a series of activated carbons were generated from sugar cane bagasse by physical and chemical activation. Bagasse is the fibrous fraction that remains after the sugar milling of sugar cane plants. Approximately 11 million tons of bagasse or greater and an equivalent quantity of cane field trash are produced in Australia annually. The conversion of bagasse to activated carbon represents an opportunity to convert this under utilized byproduct to a value-added material. Experimental Section Preparation of the Activated Carbons. Bagasse was activated in this study using two techniques: physical and chemical activation. The physical activation of bagasse in this study involved a two-step process: (1) carbonization of bagasse through the use of a dehydrating agent, sulfuric acid, followed by (2) gasification with carbon dioxide at 900 °C to develop the extended surface area and porous structure of chars. In the carbonization step, concentrated sulfuric acid was added to bagasse in a 3:4 ratio (by weight). The blend was packed into a Pyrex reactor and heated to 160 °C for 2 h with air. Air was metered into the reactor at the rate of 120 dm3/s. The resulting carbon was cooled and washed with water until it became acid free and was then dried at 110 °C. Gasification of the carbonized chars was conducted using various concentrations of carbon dioxide including 10, 50, and 100% (v/v) at a fixed temperature of 900 °C. The gasification conditions used in the preparation of the adsorbents are reported in Table 1. The process of chemical activation involves two steps: the first involves the chemical impregnation of the sugar cane fiber with the appropriate activating agent, followed by thermal degradation. The chemical activating agents, which included ZnCl2, MgCl2, and CaCl2, were dissolved in water and then added to the sugar cane fiber (bagasse) using the proportions and conditions (6) Syna, N.; Valix, M. Miner. Eng. 2003, 16, 511-518. (7) Syna, N.; Valix, M. Miner. Eng. 2003, 16, 421-427.
10.1021/la051711j CCC: $33.50 © 2006 American Chemical Society Published on Web 04/11/2006
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Table 1. Gasification Conditions of Physically Activated Carbon from Bagasse
Table 2. Manufacturing Conditions for Chemically Activated Sugar Cane Fibers
carbon adsorbent
PCO2 (v/v %)
period of activation (hours)
activating agent
sample code
I.R. (g/g)
I.t. (h)
C.T. (°C)
C.t. (h)
CA-1 CA-2 CA-3 CA-4 CA-5 CA-6 CB-1 CB-2 CB-3 CB-4 CB-5 CC-1 CC-2 CC-3 CC-4 CC-5 CC-6
10 10 10 10 10 10 50 50 50 50 100 100 100 100 100 100 100
1 3 5 7 10 15 1 5 7 10 15 1 3 5 7 10 15
ZnCl2
Zn-1 Zn-2 Zn-3 Ca-1 Ca-2 Ca-3 Ca-4 Mg-1 Mg-2 Mg-3 Mg-4
0.4 0.4 1 1 1 2 2 5 5 2 2
8 24 8 8 24 8 24 8 24 8 24
500 500 500 500 500 500 500 500 500 500 500
2 2 2 2 2 2 2 2 2 2 2
reported in Table 2. The manufacturing conditions, including the impregnation ratio (I.R., wt/wt %), impregnation time (I.t., hr), carbonization temperature (C.T., °C), and carbonization period (C.t., hr) are reported in Table 2. These mixtures were well blended and dried at 110 °C. Thermal degradation of these chemically impregnated fibers was conducted in a furnace at 500 °C under nitrogen for 2 h. The sample names, for example CA-1 and Zn-1, are related directly to their manufacturing conditions in Tables 1 and 2. Physical and Chemical Characterization of the Activated Carbons. Textural characteristics of the carbon were determined by N2 adsorption at 77 K in a Quantachrome Autosorb 1-CLP. The particle size analysis of the activated carbons was conducted using a Malvern Mastersizer S. The 50% passing (D50), or the size representing 50% of the cumulative particle size distribution, is from 190 to 235 µm. Surface and chemical properties of the carbon were established from the ash content, and the carbon pH values of the prepared activated carbons were determined according to ASTM tests D2866-94 and D3838-80, respectively (ASTM, 1996). Chemical characterization also included carbon, hydrogen, nitrogen, and sulfur analyses of the activated bagasse, which were conducted using an Elementar Vario EL III CHNOS elemental analyzer. The oxygen contents of the carbons were estimated by the difference between the C, H, N, S and the ash content of the carbon. The surface functional groups of the activated carbon, prepared from bagasse by physical techniques, were studied by Fourier transform infrared (FTIR) spectroscopy (Bruker IFS66v). The FTIR spectra were recorded under vacuum from 4000 and 400 cm-1. Dye Adsorption. The adsorbate used in this experiment was AB80 (CI ) 61585, FW ) 678.68 mol/g) from CIBA. The estimated molecular dimension is 16.5 × 6.26 Å. Its formula is:
Adsorption was carried out at room temperature using a fixed loading
CaCl2
MgCl2
Table 3. The Heteroatom Concentrations of Physically Activated Bagasse carbon adsorbent
S wt %
N wt %
H wt %
O wt %
CA-1 CA-2 CA-3 CA-4 CA-5 CA-6 CB-1 CB-2 CB-3 CB-4 CB-5 CC-1 CC-2 CC-3 CC-4 CC-5 CC-6
0.003 0.033 0.087 0.066 0.046 0.093 0.026 0.056 0.055 0.137 0.174 0.035 0.125 0.132 0.228 0.229 0.218
0.18 0.17 0.16 0.17 0.15 0.18 0.19 0.17 0.15 0.22 0.21 0.17 0.18 0.21 0.25 0.2 0.24
1.1 1.2 1.4 1.4 1.2 1.8 1.1 1.4 1.4 1.7 1.1 1.2 1.6 1.9 1.5 0.34 0.77
9.7 9.9 5.1 5.1 15.5 10.5 14.5 10.8 15.5 15.0 9.7 9.4 13.6 10.5 4.7 4.4 14.1
ratio of 10 mg of carbon in 10 mL of dye solution. Various dye concentrations from 20 to 330 ppm were shaken with the carbon for a period of three weeks. Residual dye concentrations were measured using a UV/vis spectrophotometer at a λmax of 626 nm. All experiments were carried out in duplicate.
Results and Discussion Properties of Activated Carbon from Bagasse. To support the modeling of dye adsorption capacities and carbon properties, a series of activated carbons were prepared from bagasse. Chemical characterization of these carbons included carbon pH, ash, and heteroatom concentrations. Physical analyses included total surface area and mean pore size. The heteroatom sulfur, nitrogen, hydrogen, and oxygen concentrations in the physically and chemically prepared activated carbons are reported in Tables 3 and 4, respectively. The total surface areas of the activated carbons from bagasse were calculated from the nitrogen adsorption by the BrunauerEmmett-Teller (BET) equation.8 The molecular area of the nitrogen adsorbate was taken as 16.2 Å2. The median pore widths (W) of the micropores (pore size < 2.0 nm) were estimated by applying the Horvath-Kawazoe (HK) method,9 which assumes slit pore shapes, to the nitrogen adsorption isotherms. Mesoporesized pores (2 nm < pore size < 50 nm) were estimated using the Kelvin equation.10 The properties of these physically and chemically activated carbons are summarized in Tables 5 and 6, respectively. (8) Brunauer, S., Emmett, P. H.; Teller, E. 1938, 60, 309-319. (9) Horvath, G.; Kawazoe, K. J. Chem. Eng. Jpn. 1983, 16, 470-475. (10) Bansal, R. P.; Donnet, J.; Stoeckli, F. ActiVe Carbon; Marcel Dekker, Inc.: New York, 1988.
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Table 4. The Heteroatom Concentrations of Chemically Activated Bagasse carbon adsorbent Mg-1 Mg-2 Mg-3 Mg-4 Ca-1 Ca-2 Ca-3 Ca-4 Zn-1 Zn-2 Zn-3 a
S wt %
N wt %
H wt %
O wt %
a
0.1 0.12 0.16 0.19 0.25 0.25 0.25 0.25 1.01 0.96 1.33
2.8 2.9 2.8 3.3 3.0 2.9 2.9 3.0 2.35 2.4 3.3
20 21 19 24 23.4 25.5 21.5 20.3 21.6 21.2 25.8
neg neg neg neg neg neg neg neg neg neg neg
neg: negligible or below 0.001 wt %.
Table 5. Physical and Chemical Properties and Acid Blue Dye Adsorption Capacities of Physically Activated Bagasse carbon adsorbent
BET TSA m2/g
carbon pH
W Å
ash wt %
qc mg/g
CA-1 CA-2 CA-3 CA-4 CA-5 CA-6 CB-1 CB-2 CB-3 CB-4 CB-5 CC-1 CC-2 CC-3 CC-4 CC-5 CC-6
482 546 565 661 890 992 516 681 894 876 1161 614 737 860 1146 1433 1165
7.7 7.1 6.1 6.4 6.4 6.6 6.1 5.9 6 6.5 6.6 6.4 7.3 6.8 7.1 7.4 7.4
5.46 4.87 4.82 5.12 5.56 6.66 4.95 4.92 5.13 6.5 10.7 4.9 4.54 6 8.32 11.6 10.7
21.6 22.9 28.8 32.9 34.2 44.4 19.6 27.7 32.3 40 46.1 46.1 28.7 34.8 44.3 61.1 46.7
15.8 20 23 22 38 57.7 17 19 43 64 160 27.5 25 40 145 358 200.4
Table 6. Physical and Chemical Properties and Acid Blue Dye Adsorption Capacities of Chemically Activated Carbon from Bagasse carbon adsorbent
BET TSA m2/g
carbon pH
W Å
ash wt %
qc mg/g
Mg-1 Mg-2 Mg-3 Mg-4 Ca-1 Ca-2 Ca-3 Ca-4 Zn-1 Zn-2 Zn-3
159 180 202 65 54 29 115 109 779 772 1353
9.1 9.1 9 8.9 6.1 6.2 6.3 6.5 6 6.1 5.7
266 327 102.6 258 118 147 163 180 2.9 3.13 3.9
55.6 52.8 42.4 40.2 24.3 27.7 26.3 30 28.5 27.6 25.3
39.7 43.8 26 39 43 33 61.8 58.9 29.8 20 33.5
Surface Chemical Characteristics. The FTIR spectra of bagasse physically activated with CO2 at 900 °C at various periods (3, 5, 10, and 15 h) are shown in Figure 1. The spectrum displayed the following bands: O-H stretching of the hydroxyl of the alcohols groups: 3430 and 3249 cm-1; CdO stretching of amide: 1631 cm-1; N-H stretching: 3442, 3249, and 3115 cm-1; NdO stretching from NO2: 1393, 1388, and 789 cm-1; SdO stretching from SO4: 1405 and 1388 cm-1; S(dO)2 stretching and CdS: 1166 cm-1; S-O-C stretching: 1082 cm-1; SdS stretching: 466 cm-1. The main functional groups in physically activated bagasse are the alcohol groups and the sulfurbased groups, although the nitrogen oxide groups also demonstrated intense peaks. The presence of the sulfur and nitrogen groups is consistent with the heteroatom analysis (H, N, S, and O) in Table 3.
Dye Adsorption. The amount of dye adsorbed, qe (mg/g), was determined from the following equation:
qe )
(Co - Ce)V G
(1)
where Co and Ce are the initial and equilibrium liquid-phase concentrations of dye solution, respectively, V is the volume of the dye solution, and G is the weight of the activated carbon used in the adsorption tests. Adsorption was conducted using acid dye concentrations from 20 to 330 mg/dm3. The adsorption capacities, qc (mg/g), were determined from the adsorption isotherms of each carbon. These adsorption capacities are reported in Tables 5 and 6. As shown in Tables 3-6, the carbons used in this study cover a wide range of surface areas and pore structures, representing micro-, meso-, and macropores. The total surface area is from 29 to 1400 m2/g, and the mean pore size is from 5 to 330 Å. The heteroatom concentrations of sulfur, nitrogen, hydrogen, and oxygen in the prepared activated carbons are 0.010.07, 0.14-1.3, 11-30, and 5-15 mmol‚g-1, respectively, and the carbon pH values are from 5.7 to 9.1. The adsorption capacities obtained from these carbons are in the range of 15-358 mg/g. These properties suitably cover a range of carbon characteristics that could be available and would thus be appropriate for the modeling intended in this study. Adsorption Models. As suggested, there is an inherent difficulty in elucidating the roles of the chemical and physical properties of carbons in the adsorption behavior of activated carbon. This has been associated with the fact that carbon properties will all concurrently change with activation. As such, the correlation of acid dye adsorption to any individual property is complex, and direct interpretation may be misleading. This study investigates the use of empirical modeling that relates dye adsorption to carbon properties as a means of resolving the role of the individual chemical and physical carbon properties on the acid blue dye adsorption of activated carbons. Adsorption is influenced by the surface chemistry and the structural characteristics that determine the distribution of adsorption surfaces and their accessibility. The models proposed here relate the key chemical and physical characteristics of activated carbon to dye adsorption capacities in interactive power law equations. The following correlations were proposed: Model 1:
qc ) k1[TSA]R[W]β[S]δ[N]γ[H]λ[O][ash]η
(2)
Model 2:
qc ) k2[TSA]F[pH]σ[W]ω[ash]ζ
(3)
where k1 ) constant in Model 1 k2 ) constant in Model 2 [S] ) sulfur content (mmol/g) [N] ) nitrogen content (mmol/g) [H] ) hydrogen content (mmol/g) [O] ) oxygen content (mmol/g) TSA ) BET N2 total surface area (m2/g) pH ) carbon pH W ) median pore size (Å). ash ) ash content (wt %) R, β, δ, γ, λ, , η ) power constants of the parameters in Model 1. F, σ, ω, ζ ) power constants of the parameters in Model 2. The proposed models relate the surface chemistry of the carbons to the surface acidity and ash content of the carbon. The adsorption of dyes has been found to be influenced by the surface chemistry of carbon inferred from its
Role of C Properties in Acid Blue Dye Adsorption
Langmuir, Vol. 22, No. 10, 2006 4577
Figure 1. FTIR spectra of carbon activated after 3, 5, 10, and 15 h of physical activation with 100% CO2 at 900 °C.
acidity. Basic and acidic carbons are generally recognized as having positive and negative surface charges, respectively.11,12 These properties are postulated to provide the selectivity to attract (11) Van der Plas, T. The texture and surface chemistry of carbons. In Physical and Chemical Aspects of Adsorbents and Catalysts; Academic Press: London, 1970. (12) Mattson, J. S.; Mark, H. B. ActiVated Carbon: Surface Chemistry and Adsorption from Solution; Marcel Dekker: New York, 1971.
anionic and cationic dyes to the surface of carbons. The acidity can be measured by acid/base titration13 to provide the pH required to give a zero net charge, by mass titration,14 or by measurement of the corresponding pH imparted by the carbon adsorbent in the (13) Takashi, K.; Tagaya, T.; Higatshitsuji, K.; Kittaka, S. Electrical Phenomena at Interfaces; Marcel Dekker: New York, 1984. (14) Noh, J. S.; Schwarz, J. A. Carbon 1990, 28, 675-682.
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bulk solution.15 Boehm16 suggested that the surface acidity is a contribution of various acidic and basic functional groups, which can be titrated with HCl, NaOH, NaHCO3, and Na2CO3. It has been suggested that a similar relationship exists between elemental or heteroatom sites and carbon acidity. Hydrogen, oxygen, sulfur and nitrogen are elements found on the surfaces of activated carbons. Their presence is found to affect the surface acidity and thus the adsorption properties of activated carbon.10,17-21 Zhang22 recently reported that sulfur and nitrogen contribute to the alkalinity of carbons, whereas oxygen and hydrogen contribute to the acidity of the carbon surface. However, with the exception of this work and that conducted in oxygen,17,21,23,24 little has been done to elucidate the individual and/or complementary effects of nitrogen, hydrogen, and sulfur heteroatoms on the surface of activated carbons. This study investigates the use of heteroatom concentrations and measured carbon pH to infer the surface chemistry of the carbon. The proposed models take into account these different methods of relating the surface acidity of carbons. Model 1 relates the surface acidity to the heteroatom concentrations, and Model 2 uses the measured carbon pH directly. Both models, as shown, also related the dye adsorption capacities to structural parameters including pore size and the carbon total surface area. The median pore widths (W) of the micropores were estimated by applying the HK method,9 and the mesoporesized pores were estimated using the Kelvin equation.10 Predicted adsorption capacities according to Models 1 and 2 are correlated to experimental capacities in Figures 2 and 3, respectively. These correlations form the basis for the statistical analysis for the adequacy of the proposed models. Error Analysis. Error functions were defined to determine the significance of each parameter in Models 1 and 2, and their values were determined to establish the fit of the models to the experimental data. The sum of squared total (SST), sum of squares for regression (SSR), and sum of squared errors (SSE) were computed from the number of carbons tested (n) as follows:25
Figure 2. Correlation of observed and predicted AB80 dye adsorption according to Model 1.
n
SST )
(qmeasured - qmean)2 ∑ i)1
SSR )
(qpredicted - qmean)2 ∑ i)1
(4)
n
(5)
n
SSE )
(qmeasured - qpredicted)2 ∑ i)1
(6)
where qmeasured is the experimental adsorption capacity, qpredicted is the predicted adsorption capacity, and q mean is the mean (15) American Society for Testing and Materials. Refractories, Carbon and Graphite Products, ActiVated Carbon AdVanced Ceramics; Annual Book of ASTM Standards; ASTM: Philadelphia, PA, 1996. (16) Boehm, H. P. AdVances in Catalysis; Academic Press: New York, 1966. (17) Otake, Y.; Jenkins, R. G. Carbon 1993, 31, 109-121. (18) Benaldi, H.; Bandosz, T. J.; Jagiello, J.; Schwarz, J. A.; Rouzaud, J. N.; Legras, D.; Beguin, F. Carbon 2000, 38, 669-674. (19) Sidgwick, N. V.; Millar, I. T.; Springhall, H. D. In The Organic Chemistry of Nitrogen; Clarendon Press: Oxford, 1966. (20) Toles, C. A.; Marshall, W. E.; Johns, M. M. Carbon 1999, 37, 12071214. (21) Barton, S. S.; Evans, M. J. B.; Halliop, E.; MacDonald, J. A. F. Carbon 1997, 35, 1361-1366. (22) Zhang, K. Ph.D. Thesis, The University of Sydney, 2004. (23) Lopez-Ramon, M. V.; Stoeckli, F.; Moreno-Castilla, C.; Carrasco-Marin, F. Carbon 1999, 37, 1215-1221. (24) Jankowska, H.; Neffe, S.; Swiatkowski, A. Electrochim. Acta 1981, 26, 1861-1866. (25) Alwan, L. C. Statistical Process Analysis; McGraw-Hill Higher Education: New York, 2000.
Figure 3. Correlation of observed and predicted AB80 dye adsorption according to Model 2.
experimental adsorption capacity. The mean square error (MSE), or the variance of the random errors between the fitted model and the observed data, was measured from the following equation:25
MSE ) se2 )
SSE degree of freedom
(7)
The parameters of Models 1 and 2 were determined using the solver “add-in” function of the Microsoft Excel spreadsheet program by minimizing the SSE. These parameters are shown in Table 7. Parameter Significance Tests. The significance of the independent variables used in each model was established using a partial F-test. The error sum of the squares of the full model is SSE1, and that of the reduced model containing k predictors
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Langmuir, Vol. 22, No. 10, 2006 4579
Table 7. Parameters of AB80 Adsorption Models 1 and 2 Model 1
Model 2
parameters
values
parameters
values
k1 R β δ γ λ η
19.5 0.59 0.82 0.27 1.2 -0.48 -0.127 0.096
k2 r s w z
1.33 × 10-5 1.54 -0.38 0.5 1.29
Table 8. Statistical Significance of Model Parameters parameters
degree of freedom
SSE
R(M1/M2)
full TSA W N H O S ash constant (k1)
20 1 1 1 1 1 1 1 1
Model 1 1316 3447 9844 5149 6811 1772 10916 1324 2074
full TSA W pH ash constant (k2)
24 1 1 1 1 1
Model 2 14206 37636 23430 18065 3859 13708 -497 18418 4212 37135 22929
2132 8528 3834 5495 456 9601 8.5 758
MSE
F
65.8 2132 8528 3834 5495 456 9601 8.5 758
32.4 129.6 58.3 83.5 6.9 145.9 0.1 11.5
591.9 23430 3859 -497 4212 22929
39.6 6.5 -0.84 7.1 38.7
is SSE2. The reduction in error sum of squares resulting from the fit of the additional terms in the full model was defined as26
R(M1/M2) ) SSE2 - SSE1
(8)
The F-statistics for determining the statistical significance of the chosen subset of predictor variables was estimated from the following expression:
R(M1/M2) MSR(M1/M2) p-k ) F) SSE1 MSE n-p-1
(9)
The F-statistic was used to test the null hypothesis that the variances of the reduced and full model are equal. The F-tests of each model are shown in Table 8. In Model 1, all parameters are shown to be statistically significant, with the exception of the ash content. This suggests that the ash content of the carbon is a poor predictor of dye adsorption onto activated carbons. Ash has poor structural properties, and its contribution to adsorption is often low in comparison to the carbonaceous constituent of the activated carbon.27,28 Thus, the weak correlation between the carbon ash contents and the dye adsorption is not surprising. The parameters of Model 2, with the exception of carbon pH, were also statistically significant. The lack of significance of the carbon pH in predicting dye adsorption is consistent with previous discrepancies associated with experimentally measured carbon (26) Mason, R. L.; Gunst, R. F.; Hess, J. L. Statistical Design and Analysis of Experiments; John Wiley and Sons Publications: New York, 2003. (27) Rodriguez-Reinoso, F.; Martin-Martinez, J. M.; Molina-Sabio, M. Carbon 1985, 23, 19-24. (28) Marsh, H.; Iley, M.; Berger, J.; Siemieniewska, T. Carbon 1975, 13, 103-109.
pH.18,29 Measured carbon pH is often influenced by both the surface acidity of the carbon and the soluble components in the carbon. In such a situation, where other influences apart from the actual surface acidity affect the outcome of the titration, the measured carbon pH can provide a misleading assessment of the carbon surface acidity. The analysis conducted here has shown that the use of heteroatoms, S, N, H, and O, provides a better measure of the surface acidities of the carbon that is independent of soluble inorganic impurities, which would otherwise affect titration tests. Goodness of Fit of Models. Alwan25 suggested that a parameter significance test may not be a sufficient basis to reject a model. To further analyze the suitability of the models, their fit to the experimental data was assessed. The fit of the models was established using a single statistical parameter (r2), which is also referred to as the coefficient determination, and was defined as follows:25
r2 )
SSR SST
(10)
The parameter r2 is applicable to linear models with a single variable. Both Models 1 and 2 are fitted to eight and five variables, respectively. To overcome the possible misleading representation imposed by this large number of variables, a variant called the adjusted r2 that adjusts for the number of variables (p) in the fitted model was also reported. The adjusted r2 was computed as25
adjusted r2 ) 1 -
(n - 1)SSE (n - p - 1)SST
(11)
Similarly, the MSE (see eq 7) was also corrected for the bias of a differing number of fitted dependent variables, according to the following equation:25
MSE ) se2 )
SSE (n - p - 1)
(12)
The correlation of the observed and predicted dye adsorption according to Models 1 and 2 are shown in Figures 2 and 3, respectively. The statistical measures of the fit of the two proposed models are shown in Table 9. The coefficient of determination of Model 1 is r2 ) 0.99, adjusted r2 ) 0.985, and se ) 8.1. The corresponding measures of fit of Model 2 are r2 ) 0.90, adjusted r2 ) 0.89, and se ) 24.3. These statistical parameters are consistent with the parameter significance tests and suggest the greater fit of Model 1 in comparison to Model 2. It appears that inferring the surface acidity from the heteroatom concentrations, as in Model 1, provides a better prediction of dye adsorption in comparison to measured carbon pH. The inability of the measured carbon pH to suitably predict dye adsorption is consistent with the previous reported difficulty in obtaining accurate carbon pH.18,29 Diagnostic Analysis of Fitted Model Adequacy. The statistical analysis above proved the greater fit of Model 1 to the observed adsorption values; however, these values do not imply the adequacy of the model for its intended application. This would require a basic diagnostic check of model adequacy. The randomness and normality diagnosis of the residuals from the fitted model and the observed adsorption data form the basis for judging the appropriateness of the fitted model. The residuals are considered random if 95% of the data falls within the mean (29) Apak, R.; Guclu, K.; Turgut, M. H. J. Colloid Interface Sci. 1998, 203, 122-130.
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Table 9. Statistical Analysis of the Fit of Adsorption Models source of variation
degree of freedom
sum of squares
mean squares
regression error total
7 20 27
144335 1316 145651
20619 65.8 5394
regression error total
3 24 27
140268 14206 154474
46756 592 5721
F-statistics
p-value
r2
adjusted r2
Model 1 8.1
313.4
0.000
0.99
0.985
Model 2 24.3
79
0.000
0.9
0.896
se
Table 10. Diagnosis of Normality and Randomness of Residuals Obtained from Observed and Fitted Adsorption Data According to Model 2
interval around observed adsorption data
percentage of predicted adsorption data falling within the given interval (%)
expected percentage given normality (%)
(1 standard deviation (2 standard deviation (3 standard deviation
74 96.4 100
68.27 95.45 99.73
residual ( 2 × the standard deviation. The standard deviation (STD) of the residuals was calculated from25
STD )
[
n
]
(robserved - rmean)2 ∑ i)1 n
0.5
(13)
The robserved is the difference between the observed and the predicted dye adsorption capacity, and rmean is the population average of the residuals. The test for normality of the residuals is based on a comparison with three intervals. It anticipated that 68.27, 95.45, and 99.73% of the observed residuals will fall within the (1, (2, (3 standard deviation of the mean residuals.25 A comparison of the percentage of observed residuals that fall within the given range with that expected given the normality is shown in Table 10. These data were calculated based on a mean residual of 0.07 and a standard deviation of 7.6. The residuals appear compatible with the normality check as shown by results in Table 10. The randomness check that requires 95% of the residuals to fall within the interval of the mean (2 standard deviation is also satisfied by the results in Table 10. In summary, the residuals are consistent with both the randomness and normality, implying the adequacy of the fitted Model 1. The proposed correlation of the carbon properties in Model 1 adequately describes the dye adsorption behavior on activated carbons prepared from bagasse. Mechanism of Adsorption and Surface Chemistry. Model 1 was modified by excluding the ash content parameter and was used to predict the influence of individual carbon properties on AB80 adsorption. Figure 4 shows the effect of the mean pore size and total surface area on the adsorption of AB80. The adsorption, as shown, is promoted in carbons exhibiting wide pores and high surface areas. Restriction of dye adsorption onto constricted pores would be anticipated for large molecular structures such as dyes. The effect of the surface chemistry, in particular, the effect of the heteroatom concentrations in dye adsorption, is shown in Figures 5-8. Figures 5 and 6 show that the presence of sulfur and nitrogen promotes acid dye adsorption. AB80 ionizes in solution to form the negatively charged colored component or anions and positively charged Na+ cations. The alkalinity of
Figure 4. Predicted AB80 dye adsorption as a function of the mean pore sizes (W) and total surface areas: (b) TSA ) 100 m2/g; (0) TSA ) 500 m2/g; (2) TSA ) 1000 m2/g; (3) TSA ) 1500 m2/g. Constant parameters: [S] ) 0.01 mmol‚g-1; [N] ) 0.14 mmol‚g-1; [H] ) 11 mmol‚g-1; [O] ) 15 mmol‚g-1.
Figure 5. Effect of the carbon sulfur contents on the predicted AB80 dye adsorption as a function of the mean pore sizes (W): (b) [S] ) 0.01 mmol‚g-1; (0) [S] ) 0.02 mmol‚g-1; (2) [S] ) 0.05 mmol‚g-1; (3) [S] ) 0.07 mmol‚g-1. Constant parameters: TSA ) 1000 m2‚g-1; [N] ) 0.2 mmol‚g-1; [H] ) 11 mmol‚g-1; [O] ) 15 mmol‚g-1.
carbon surfaces in bulk solutions are used to categorize activated carbons into type H and L.30 The sulfur-based functional groups established by FTIR (see Figure 1) are used to demonstrate the
Role of C Properties in Acid Blue Dye Adsorption
Langmuir, Vol. 22, No. 10, 2006 4581
Figure 6. Effect of the carbon nitrogen contents on the predicted AB80 dye adsorption as a function of the mean pore sizes (W): (b) [N] ) 0.14 mmol‚g-1; (0) [N] ) 0.2 mmol‚g-1; (2) [N] ) 0.3 mmol‚g-1; (3) [N] ) 0.4 mmol‚g-1; ([) [N] ) 0.5 mmol‚g-1. Constant parameters: TSA ) 1000 m2‚g-1; [S] ) 0.07 mmol‚g-1; [H] ) 11 mmol‚g-1; [O] ) 15 mmol‚g-1.
Figure 8. Effect of the carbon hydrogen contents on the predicted AB80 dye adsorption as a function of mean pore sizes (W): (b) [H] ) 10 mmol‚g-1; (0) [H] ) 15 mmol‚g-1; (2) [H] ) 20 mmol‚g-1; (3) [H] ) 25 mmol‚g-1; ([) [H] ) 30 mmol‚g-1. Constant parameters: TSA ) 1000 m2‚g-1; [S] ) 0.07 mmol‚g-1; [N] ) 0.2 mmol‚g-1; [O] ) 5 mmol‚g-1.
charge on the carbon based on eq 14 can now attract the negatively charged AB80 ion, as follows:
Acid Dyeδ- Naδ+ f Acid Dyeδ- + δNa+
(16)
C ) Sδ+ + Acid Dyeδ- f C ) S: ‚‚‚ Acid Dye (17)
Figure 7. Effect of the carbon oxygen contents on the predicted AB80 dye adsorption as a function of the mean pore sizes (W): (b) [O] ) 5 mmol‚g-1; (0) [O] ) 10 mmol‚g-1; (2) [O] ) 15 mmol‚g-1; (3) [O] ) 20 mmol‚g-1. Constant parameters: TSA ) 1000 m2‚g-1; [S] ) 0.07 mmol‚g-1; [N] ) 0.2 mmol‚g-1; [H] ) 11 mmol‚g-1.
dissociation of H or basic carbons in water in the following equation:24
C ) S+OH- + H+ f C ) S+ + H2O
(14)
The H carbon surface produces an alkaline suspension and a positive ζ potential, indicative of positively charged surface and thus demonstrating an affinity for anions. On the other hand, L or acidic carbon, which, as suggested by FTIR analysis in Figure 1, is promoted by oxygen and hydrogen groups, dissociates by
C ) O- H+ f C ) O- + H+
(15)
L carbons produce acidic suspension and negative ζ potential or negatively charged surface. Consequently, the residual positive
The affinity of AB80 onto surfaces containing sulfur and nitrogen suggest the preference of dyes for alkaline surfaces or positively charged surfaces. This is consistent with previous observations that suggest that nitrogen and sulfur impart alkalinity to the carbon surface.17,18,22 Sulfur and nitrogen compounds, in particular, oxides of sulfur and nitrogen, are known to contain unpaired electrons. It has been postulated that Lewis bases, which are electron donors, provide sites of π electron-rich regions within the basal planes of the graphitic microcrystals that act as basic sites.21,31 By the same reasoning, the presence of oxygen and hydrogen, which has previously been reported to impart acidic surfaces in activated carbons,17,21,23,24 should repel AB80 from the carbon surface but offer an attractive site for basic dyes, as represented by eq 18:
C ) Oδ- + Basic Dyeδ+ f C ) O: ‚‚‚ Basic Dye
(18)
Figures 7 and 8 show that the presence of higher concentrations and oxygen and hydrogen reduced the adsorption of acid blue dyes. These results confirm the heteroatom contribution to the surface acidity of the carbon and their relative importance in developing the surface chemistry of carbons for specific adsorption. It is apparent that the adsorption of AB80 onto the activated carbons in this study involves an electrosorption mechanism. Although larger pores promote dye adsorption, it is also apparent from Figures 5 and 6 that adequate surface chemistry will allow efficient adsorption, even in constricted pore structures. Carbon with high sulfur (0.07 mmol/g) and nitrogen (0.5 mmol/ (30) Al-Degs, Y.; Khraisheh, M. A. M.; Allen, S. J.; Ahmad, M. N. Water Res. 2000, 34, 927-935. (31) Leon, C.; Solar, J. M.; Calemma, V.; Radovic, L. R. Carbon 1992, 30, 797-811.
4582 Langmuir, Vol. 22, No. 10, 2006
g) contents is shown to promote significant dye adsorption (200350 mg/g) in microporous solids (mean pore size < 20 Å) (see Figures 5 and 6). This emphasizes the clear importance of the surface chemistry of the carbon and the selection of precursors, with chemical constituents and activation methods that will deliver adequate surface acidity in the adsorption of dyes. The molecular dimensions of the AB80, which are 16.5 × 6.26 Å, and the adsorption in microporous solids (pore size < 20 Å) suggest that AB80 adsorbs with its narrower end entering first. However higher adsorption is achieved with meso- and macroporous solids, indicating that the larger pore openings allow greater accessibility of the surface areas.
Conclusions This study has successfully demonstrated the use of empirical modeling in resolving the effects of individual carbon properties on the adsorption of AB80. A model based on the structural properties of the carbon and surface acidity inferred from heteroatom concentrations was found to adequately describe acid dye adsorption onto activated carbon. This model suggests AB80 adsorption is restricted by narrower pores. The presence of high total surface area and wider pores generally exhibited high dye adsorption capacities. The surface chemistry of the carbon was also found to affect adsorption significantly. Surface acidities that dictated the surface chemistry of the carbon were found to
Valix et al.
be influenced by their heteroatom concentrations. Sulfur and nitrogen groups, including CdS, SdS, and SdO, and NdO and NO2, imparted alkaline surfaces and thus net positive charges on the carbon surfaces that promoted the adsorption of anionic AB80 dye. The adsorption of the negatively charged dyes onto this positively charged surface is consistent with the electrosorption mechanism. Oxygen and hydrogen atoms, which contributed to the acidity of the carbons, imparted net negative surface charges that suppressed the adsorption of acid dye anions. Although wider pores allow greater accessibility and thus adsorption, this study has also shown that significant adsorption (200-350 mg/g) is also possible in microporous solids with an appropriate surface chemistry, thus emphasizing the importance of the chemical constituents of the carbon that arise from the choice of precursor and method of activation. This study has successfully demonstrated that empirical modeling of dye adsorption with carbon properties can provide valuable information that could be used as a basis for tailormaking adsorbents or selecting appropriate adsorbents for the removal of acid dyes. Acknowledgment. The authors (M.V. and W.H.C.) would like to acknowledge the financial support of the Sugar Research and Development Corporation, Australia. LA051711J
