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Steam activation of Eupatorium adenophorum for the production of porous carbon and hydrogen rich fuel gas
Journal of Analytical and Applied Pyrolysis 110 (2014) 113–121
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Steam activation of Eupatorium adenophorum for the production of porous carbon and hydrogen rich fuel gas Zhaoqiang Zheng a,b,c , Hongying Xia a,b,c,∗ , C. Srinivasakannan d , Jinhui Peng a,b,c , Libo Zhang a,b,c a
Yunnan Provincial Key Laboratory of Intensification Metallurgy, Kunming 650093, Yunnan, China Key Laboratory of Unconventional Metallurgy, Ministry of Education, Kunming University of Science and Technology, Kunming 650093, Yunnan, China c Faculty of Metallurgical and Energy Engineering, Kunming University of Science and Technology, Kunming 650093, China d Chemical Engineering Program, The petroleum Institute, PO Box 2533, Abu Dhabi, United Arab Emirates b
a r t i c l e
i n f o
Article history: Received 16 March 2014 Accepted 16 August 2014 Available online 27 August 2014 Keywords: Eupatorium adenophorum Activated carbon Hydrogen rich fuel gas Response surface methodology
a b s t r a c t Eupatorium adenophorum was converted into a high-quality activated carbon (EAAC) and hydrogen rich fuel gas via steam activation. The process variables including activation temperature, activation duration and steam flow rate on the adsorption capability and activated carbon yield were identified. Additionally the surface characteristics of EAAC were characterized by nitrogen adsorption isotherms, FTIR and SEM. The operating variables were optimized utilizing the response surface methodology and were identified to be an activation temperature of 950 ◦ C, an activation duration of 60 min and a steam flow rate of 1.2 ml/min with a iodine adsorption capacity of 1031 mg/g and yield of 25%. The key parameters that characterize quality of the porous carbon such as the BET surface area, total pore volume and average pore diameter were estimated to be 1357 m2 /g, 1.1 ml/g and 3.31 nm, respectively. The heating value of fuel gases evolved during the process of activation at optimized process conditions were estimated to be 10.27 MJ/m3 , with the major components being H2 and CO. A high heating value well augurs its utility as a heat source for the whole process which would significantly alter the commercial manufacturing economy. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Activated carbons (AC) are important kinds of porous carbon material with abundantly developed pore structure having high surface area and thermo stability. They are widely used in different industries, for separation and purification of gas and aqueous media [1–3], as catalyst supports [4] and for waste water treatment applications [5,6]. The selection of an appropriate precursor plays an important role in deciding the characteristics of the AC as well as the economics of the manufacturing plant. To identify new precursors that are cheap, accessible and available in large quantity has been a perennial challenge in commercial manufacture for economic benefits [7]. Towards which, different biomass based feedstock such as rice bran, coconut shell and waste materials were used as the raw materials since they are sustainable sources having high fixed carbon content [8–10].
∗ Corresponding author at: Kunming University of Science and Technology, Faculty of Metallurgical and Energy Engineering, Kunming 650093, China. E-mail addresses: [email protected], [email protected] (H. Xia). http://dx.doi.org/10.1016/j.jaap.2014.08.007 0165-2370/© 2014 Elsevier B.V. All rights reserved.
Eupatorium adenophorum is a kind of global exotic weed originated from Mexico, and has spread extensively in many countries around the world such as America, Australia and the countries in Southeast Asia due to its strong ability to adapt to different environmental conditions [11]. Since 1940s, Eupatorium adenophorum has spread extensively in south and western of China. Lots of the farm lands, pasture fields and forests have been destroyed causing huge economic losses. This has drawn the attention of the society and many methods have been developed to control it, such as manual, chemical and biological control, however with no tangible progress in controlling it. In 2003, the Chinese ministry of environmental protection released a list of “The First Batch of Exotic Invasive Species” and Eupatorium adenophorum was rated the first [12,13]. According to the published literatures, Eupatorium adenophorum can be used as bio-pesticide [14], organic fertilizer and feedstuff, feedstock for production of marsh gas [15]. Although, Eupatorium adenophorum can be utilized as a biomass resource to prepare the AC, the relevant literature is very limited. The attempts pertaining to preparation of EAAC has been limited to Xia et al. and Wu et al. [16,17]. Activated carbons have been traditionally produced by the partial gasification of the char either with steam or CO2 or a
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combination of both. The gasification reaction results in removal of most reactive carbon atoms and simultaneously produce a wide range of pores (predominantly micropores), resulting in porous activated carbon. Physical activation is essentially a two-step process, where the carbonization of a carbonaceous material forms the first step, while the second step involves the activation of the resulting char at elevated temperature in presence of suitable oxidizing gases such as carbon dioxide, steam, air or their mixtures. Physical activation is widely adopted industrially for commercial production owing to the simplicity of process and the ability to produce AC with well developed micro porosity and desirable physical characteristics such as the good physical strength. During the activation process, the exhaust gases will certainly be produced by the oxidizing gases, which were discharged into the atmosphere causing environmental concerns. Referring to exhaust gas in the process of preparation of AC is space although the exhaust gas is a rich resource of hydrogen. The objective of present work is to assess the effect of operating conditions to understand the relationship between the process variables and the desired objective function. Towards which the effects of activation temperature, activation duration and steam rate on the adsorption capacity and yield of EAAC were investigated systematically to optimize the process conditions to maximize the iodine adsorption capacity, which reflects the internal surface area. Additionally the exhaust gases under the optimized process conditions were sampled for characterization using Gas Chromatography. The AC prepared under the optimized process conditions were characterized using the nitrogen adsorption isotherm, FTIR and SEM. 2. Materials and methods 2.1. Materials Eupatorium adenophorum was obtained from Kunming, Yunnan Province of China. The raw materials were crushed to a size of 5–7 mm and washed thoroughly with deionized water, then were oven-dried at 105 ◦ C and stored in moisture free environment for utilization in the experiments. The proximate analysis of Eupatorium adenophorum is presented as follow: volatile 76.41%, ash 1.90% and fixed carbon 21.69%. The ultimate analysis of Eupatorium adenophorum represented in weight percent is as follow: carbon 52.37%, hydrogen 6.02%, oxygen 39.62%, nitrogen 1.15% and sulfur 0.84%. 2.2. Experimental methods The carbonization of raw precursors was carried out at a carbonization temperature of 500 ◦ C at the heating rate of 20 ◦ C/min in muffle furnace, for duration of 60 min, under the nitrogen flow atmosphere. The char yield is estimated to be around 35% and the proximate analysis of char (Fig. 1) was as follow: volatile 15.84%, ash 8.86% and fixed carbon 75.30%. The carbon content of the char is found to have increased significantly upon carbonization, while the volatile matter decreased. A self-made tube furnace, which was employed in the activation experiments, is shown in Fig. 2. It mainly consists of four components: the temperature control system (temperature controlled by the input electric power and measured by the thermoelement, with a measurement precision of ±0.5 ◦ C), the flow control system (controlled by the flow meter for steam and N2 ), the activation system (a known amount of the carbonized materials were placed in the platform of quartz reactor fixed in the tube furnace), and the gas analysis system (the gas was collected in the glass bottle filled with water, which was analyzed using GC of Agilent 7890A). Prior to the use of furnace, N2 was purged to displace the air at a pre-set flow rate of 150 cc/min. Subsequently, the materials were heated from the room temperature to the desired temperature. Once the
Fig. 1. The proximate analysis of precursor Eupatorium adenophorum and its chars.
precursors reached the desired temperature the N2 flow was terminated and replaced by steam into the reactor at the desired flow rate for desired activation duration. The completion of activation process was marked by termination of the steam supply and starting of N2 flow until the EAAC were cooled to the room temperature, which were then dried at 105 ◦ C and stored for further characterization. The iodine adsorption capacity is represented as iodine number, is an important parameter widely used to characterize micro porous material. Iodine number was tested for the EAAC according to the National Standard Testing Methods of PR China (GB/T12496.8-1999) [18], while the yield of EAAC was defined as the weight of activated carbon per weight of carbonized materials utilized for activation. The specific surface areas of EAAC produced by the optimum conditions as well as the carbonized char were determined by the BET method using nitrogen as the adsorbate at 77 K utilizing the commonly used Autosorb instrument. Prior to the measurements, the samples were out gassed at 300 ◦ C under nitrogen for at least 12 h. Nitrogen adsorption isotherms of EAAC and char were tested over a relative pressure (P/P0 ) range from 10−7 to 1. The total pore volumes were estimated to be the equivalent liquid volume of the adsorbate (N2 ) at a relative pressure of 0.99. The BET surface area of the sample was calculated by the Brunauer–Emmett–Teller (BET) equation. The pore size distribution was analyzed by using the Non-local Density Functional Theory (NLDFT). Scanning electron microscopy (SEM, Philips XL30ESEM-TMP) analysis was carried out to assess the surface microstructures. The Fourier transform infrared spectroscopy (FTIR) was applied to qualitatively identify the chemical function groups present in the EAAC. FTIR spectra were operating in the range of 4000–400 cm−1 by using AVATAR 330 (Thermo Nicolet CO., USA) Spectrophotometer. The samples of the transmission spectra were prepared by mixing up with KBr crystals at a ratio of 1:100 (samples/KBr) and pressed into a pellet. The gases were analyzed in an Agilent 7890A gas chromatograph fitted with a TCD detector, the TCD was calibrated with the standard gas mixture at fixed intervals. The carrier gas (He) flow rate was 40 ml/min, while the oven temperature was set at 50 ◦ C. The injector and detector temperature were 100 and 180 ◦ C, respectively. The heating values (HV) of the gases were determined based on the composition of gases by the HV of individual components [19]. 2.3. Experimental design RSM was utilized to optimize the activation process as it is a popular statistical tool for modeling and analysis of multi parameter processes. The central composite design (CCD) was employed
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Fig. 2. The modified diagram for the preparation equipment.
Table 1 Independent variables and their levels for central composite design.
Table 3 Analysis of credibility of the model.
Independent variables
Symbol Coded variable levels −1.68179 −1
0
+1
+1.68179
Activation temperature Activation duration Steam flow rate (ml/min)
X1
865.91
900
950
1000
1034.09
X2
34.77
45
60
75
85.23
X3
0.80
1.00
1.3
1.60
1.80
to design the activation experiments [20]. The effects of three independent variables, X1 (activation temperature), X2 (activation duration), X3 (steam flow rate), at five levels were investigated (Table 1). The iodine number and yield of EAAC were taken as the two responses of the designed experiments. A total of 20 experiments consisting of 8 factorial points, 6 axial points and 6 replicates at the central points were employed. The experimental design matrix is provided in Table 2. The experimental data were analyzed using the Design Expert software version 7.1.5 (Stat-Ease Inc., Minneapilis, USA). Optimization of activation conditions for Eupatorium adenophorum was obtained using the software’s numerical and graphical optimization functions.
Source
Std. Dev.
R2
Adj R2
Pred R2
Adeq Precosopm
Iodine number Yeild
14.02 3.56
0.9763 0.9692
0.9550 0.9416
0.8246 0.7641
18.23 21.16
the parameters such as activation temperature, activation duration and steam flow rate. The EAAC are characterized for iodine number, yield and results are listed as well in Table 2. 3.1. Statistical analysis The relationship between the responses (Y1 , Y2 ) and three independent variables (X1 , X2 , X3 ) were established using an appropriate regression model, utilizing the software. For iodine number and yield, the two-factor interaction model was selected as suggested by the software. Experimental runs performed at the center point of all the variables (15–20 runs) were utilized to determine the experimental error. The final empirical models in terms of coded factors (excluding the insignificant terms) for iodine number (Y1 ) and yield (Y2 ) are shown in Eqs. (1) and (2), respectively: Y1 = +1044.49 + 21.19X1 + 15.49X1 + 11.31X3 − 45.76X12 − 42.76X22 − 43.11X32
3. Results and discussion Table 2 shows the experimental conditions adopted for preparation of EAAC as generated by the Design Expert software covering Table 2 Experimental design matrix and results by microwave heating with steam. Run
X1 (◦ C)
X2 (min)
X3 (ml/min)
Y1 (mg/g)
Y2 (%)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
900.00 1000.00 900.00 1000.00 900.00 1000.00 900.00 1000.00 865.91 1034.09 950.00 950.00 950.00 950.00 950.00 950.00 950.00 950.00 950.00 950.00
45.00 45.00 75.00 75.00 45.00 45.00 75.00 75.00 60.00 60.00 34.77 85.23 60.00 60.00 60.00 60.00 60.00 60.00 60.00 60.00
1.00 1.00 1.00 1.00 1.60 1.60 1.60 1.60 1.30 1.30 1.30 1.30 0.80 1.84 1.30 1.30 1.30 1.30 1.30 1.30
855 895 917 952 890 932 919 977 875 943 912 923 900 933 1040 1048 1050 1043 1042 1046
55.50 46.35 33.46 23.64 43.51 31.33 19.72 13.25 52.08 20.45 47.61 18.32 38.77 17.75 23.43 23.50 23.54 23.17 23.62 23.19
Y2 = +23.4 − 6.65X1 − 9.95X2 − 6.31X3 + 2.82X12 + 1.65X22
(1)
(2)
The results obtained from the analysis of variance (ANOVA) were also carried out to prove the validity of the model. Validating the model adequacy is an import part of the data analysis, since it would lead to poor or misleading results if it is an inadequate fit. The analysis of credibility of the model for iodine number and yield was shown Table 3.The quality of model developed was always evaluated using the correlation coefficient (R2 ), which were 0.9763 for Eq. (1) and 0.9348 for Eq. (2), respectively. Both the R2 values were of high proximity to unity, indicating the suitability of the model equation, evidencing good agreement between experimental data and the prediction using the model [21]. For iodine number the Pred R2 of 0.8246 is reasonable agreement with the Adj R2 of 0.9550 (The difference between Pred R2 and Adj R2 within 0.2 is reasonable). Adequate precision measures the signal to noise ratio was observed to be 18.23 for the present experiments, much higher than the desirable ratio greater than 4. For yield the Pred R2 , Adj R2 and Adequate precision were 0.7641, 0.9416 and 21.16. With the above validations in support of the model, it was utilized to navigate the design space to identify the optimum conditions. The ANOVA for the quadratic model of iodine number is presented in Table 4. The model F-value of 45.79 implied the model is
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Table 4 Analysis of variance for the iodine number. Source
Sum of squares
Degree of freedom
Mean square
F-value
Pb > F
Model X1 X2 X3 X1 X2 X1 X3 X2 X3 X1 2 X2 2 X3 2
81036.57 6131.01 3275.43 1747.84 15.13 78.13 253.12 30183.16 26349.27 26786.81
9 1 1 1 1 1 1 1 1 1
9004.06 6131.01 3275.43 1747.84 15.13 78.13 253.12 30183.16 26349.27 26786.81
45.79 31.18 16.66 8.89 0.077 0.40 1.29 153.51 134.01 136.23
<0.0001 0.0002 0.0022 0.0138 0.7872 0.5426 0.2830 <0.0001 <0.0001 <0.0001
Fig. 3. Predicted vs. experimental iodine number of EAAC.
significant. There was only a 0.01% chance that a “Model F-Value” of this large could occur due to noise. Values of “Prob > F” less than 0.05 indicated that the model terms are significant. In this case X1 , X2 , X3 and the interaction terms (X1 2 , X2 2 , X3 2 ) were found to be significant model terms based on the low ‘p’ values. Values greater than 0.1 indicates the model terms were not significant. The ANOVA result of quadratic model corresponding to yield is shown in Table 5. A model F-value of 35.01 and P > F of <0.0001 indicated the suitability of model. In this case, X1 , X2 , X3 along with the interaction parameters (X1 2 , X2 2 ) were found to be significant. In conclusion, the ANOVA results showed that the model was appropriateness to be utilized within the range of the variables covered in the present work.
the figure, the experimental data were evenly distributed on the both sides of the model prediction, indicating the suitability of the model in capturing the correlation between the process and response variables. Based on the F values (Table 4), activation temperature showed the highest of F Value (31.18) indicating it to be the most significant parameters as compared to activation duration and steam flow rate, with the F Value of 16.66 and 8.89, respectively. Three-dimensional response surfaces were created to show the relationships between the independent variables on iodine number as shown in Fig. 4a–c. In all the plots the third variable was maintained at the center point. As can be seen, an increase in the activation temperature activation duration steam flow rate, an increase in the iodine number could be evidenced, indicating the formation of pores due to the gasification reaction of steam with the carbon. The increase in the iodine number sustains until an optimal combinations of the parameter beyond which it was found to decrease. It is well established that the gasification reactions beyond an optimal conditions would contribute to reduction in the surface area due to pore enlargement and pore merger. Hence it is important to identify the optimal process conditions to maximize the surface area. It is well known that the adsorption depends on the pore structure. It is reported that the pore diameter should be at least 1.7 times of the molecular widest dimension in order to be good adsorption site to capture a molecule [23]. The iodine molecule is strongly adsorbed due to its smaller size of 0.27 nm permitting its penetration into micropores under the size of 1 nm [24]. The development of porosity was associated with gasification according to the reaction between the steam and carbon. The extent of the reaction would increase with an increase in the activation temperature, activation duration and steam flow rate. The increase in porosity is expected to be directly proportional to the increase in the carbon conversion. The increase in the micropores can be assessed based on the increase in the iodine adsorption capacity of the carbon. A reduction beyond optimum levels could be due to the higher extent of steam-carbon reaction contributing to pore merger as observed at high temperatures. A similar tendency has been reported in the preparation of AC from Jatropha hull [25], wood sawdust [26] and biodiesel industry solid residue [27]. Table 6 lists the comparison of maximum iodine number of various AC derived from different precursors reported in the literature. As can be seen, the EAAC prepared in the present work has relatively high iodine number as compared with the values reported in literature.
3.3. Yield of EAAC 3.2. Iodine number of EAAC Fig. 3 shows the comparison of predicted versus the experimental data for iodine number of EAAC. Experimental values were the measured response data for a particular run while the predicted values were evaluated using the model Eq. (1) [22]. As seen in Table 5 Analysis of variance for the yield. Source
Sum of squares
Degree of freedom
Mean square
F-value
Pb > F
Model X1 X2 X3 X1 X2 X1 X3 X2 X3 X1 2 X2 2 X3 2
2956.98 603.90 1351.94 544.57 3.18 0.013 1.04 306.77 171.24 44.49
9 1 1 1 1 1 1 1 1 1
328.55 603.90 1351.94 544.57 3.18 0.013 1.04 306.77 171.24 44.49
35.01 64.36 144.07 58.03 0.34 0.001 0.11 32.69 18.25 4.74
<0.0001 <0.0001 <0.0001 <0.0001 0.5736 0.9713 0.7465 0.0002 0.0016 0.0545
The yield of EAAC is an important parameter, which is affected by the activation process and the activation conditions. The model prediction against the actual experimental data on the yield of EAAC is shown in Fig. 5. As can be seen, the experimental data are evenly distributed on the both sides of the model prediction. Based on the F values (Table 5), X2 was found to have the highest of F value of 144.07, implying its significant effect on yield as compared to X1 and X3 . Table 2 compiles the yield of EAAC for each experiment. Three-dimensional response surfaces plot of yield with respect to the activation temperature and activation duration is shown in Fig. 6a–c. From the figures, the yield of EAAC is found to decrease with the increase in all the three parameters, the results indicate the minimum of yield corresponds to the maximum of the three parameters. As can be seen from Fig. 6a and c, the activation duration was found to play the most important role in the yield of EAAC. Moreover, an increase in any of the three parameters effectively contributes to an increase in the extent of C-Steam reaction, contributing to the reduction in the yield of EAAC.
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Fig. 4. Three-dimensional response surface plot of iodine number: effect of activation duration and activation temperature (a), effect of steam flow rate and activation temperature (b), effect of steam flow rate and activation duration (c).
Table 6 Comparison iodine adsorption of AC prepared from different biomass. Precursors
Activating agent
Activation duration (min)
Iodine adsorption (mg/g)
Activation temperature(◦ C)
Reference
Eupatorium adenophorum Rice bran Paper mill sewage sludge Olive-waste cakes
Steam Steam Steam H3 PO4
60 90 40 120
1050 220 180 583
950 850 850 450
Present study [28] [29] [30]
3.4. Process optimization Industrial production of AC augur a high iodine number and yield as both of which contribute to improve the economics of commercial manufacture. However, both the response variables the iodine adsorption capacity (Y1 ) and yield (Y2 ) respond opposite to
each other, demanding identification of an optimum combination of the parameters that maximize the iodine number and the yield of carbon. The optimized goals of these two responses were selected to maximize with the ranges of 855–1050 mg/g, 13.25–55.50%, respectively. The optimum condition was identified by invoking the optimization tool available with the Design Expert Software. The optimized process conditions along with the validation of the optimized process conditions are presented in Table 7. In order to authenticate the identified optimized experimental conditions, three repeat runs were conducted and the average of the three runs is posted in Table 7. The proximity in iodine number and the yield between the repeat runs and the optimized conditions validate the success of the optimization process. 3.5. Characterizations of pore structure
Fig. 5. Predicted vs. experimental yield of EAAC.
Nitrogen adsorption is a standard procedure for determination of porosity of the carbonaceous adsorbents. The nitrogen adsorption isotherm of char and EAAC under the optimum condition was estimated using the Autosorb instrument at 77 K is shown Fig. 7. The shape of the isotherm pertains to adsorption isotherm type II under the IUPAC classification [31]. Fig. 7 compares the nitrogen adsorption capacity of the char with respect to the EAAC. As can
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Fig. 6. Three-dimensional response surface plot of yield: effect of activation duration and activation temperature (a), effect of steam flow rate and activation temperature (b), effect of steam flow rate and activation duration (c).
Table 7 Validation of process optimization. Activation temperature, X1 (◦ C)
Activation duration, X2 (min)
Steam dioxide flow, X3 (ml/min)
Iodine number (mg/g)
Yield(%)
Predicted
Experimental
Predicted
Experimental
950.00
60.00
1.2
1036
1031
25.69
25
Adsorption Volume (mg/g)
500
Char EAAC
400
300
200
100
0 0.0
0.2
0.4
0.6
0.8
Relative Pressure (P/P0) Fig. 7. Nitrogen adsorption isotherm of the EAAC and char.
1.0
be seen, the nitrogen adsorption isotherm of EAAC is exceedingly higher than that of char, clearly indicating the higher amount of pores in EAAC. A continued increase in the nitrogen adsorption capacity beyond a p/p0 value of 0.1, are typical for mesoporous material, which is exhibited by the char as well as the EAAC. This type of isotherm indicates an indefinite multi-layer formation after completion of the monolayer and is found in adsorbents with a wide distribution of pore sizes. Near to the first point of inflexion a monolayer is completed, following with adsorption in successive layers. Microporous materials don’t exhibit an increase in adsorption capacity beyond a p/p0 value of 0.1. The cumulative pore volume plots shown in Fig. 8, while Fig. 9 shows the pore size distribution, both of which substantiate the amount of pores in the mesoporous range, with the average pore diameter estimated to be 3.31 nm. In general steam activation process is known to produce highly microporous material contradicting to the results of the present work. Generation of mesopores are generally attributed to excess burnout or the carbon-steam reaction rendering pore wall thining and eventually pore merger. Although the sample corresponds to the optimized process conditions that maximize the surface area and the yield, the proportion of pore volumes in the mesoporous range are contradicting to the earlier reports related
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0.60
Char EAAC
3
Adsorption Volume (cm /g)
0.75
0.45
0.30
0.15
0.00 0
5
10
15
20
25
30
35
40 Fig. 10. FTIR of EAAC.
Pore width (nm) Fig. 8. Cumulative pore volume distribution chart for EAAC and char. Table 8 Pore structural parameters of EAAC vs. chars. Properties Pore volume Average pore diameter Micropore volume Mesopore volume BET Surface area
ml/g nm % % m2 /g
EAAC
Chars
1.1 3.31 34 66 1357
0.23 3.6 27.1 72.9 260
to other biomass. High proportion of mesopores with high surface area would render this product highly suitable for removal of high molecular weight compounds from liquid phase. The pore structural parameters are summarized in Table 8. A comparison of the quality of EAAC with the char exhibits a significant increase in the pore volume, the micropore volume and the surface area attributed to the activation process. 3.6. Function groups of EAAC To characterize surface groups on EAAC, Fourier transform infrared (FTIR) transmission spectra were obtained, as shown in
3.7. SEM analysis of microstructure The microscopic structure of the char (before activation) and the EAAC are shown in Fig. 11. Fig. 11a shows the SEM microstructure of char while Fig. 11b shows the SEM microstructure of EAAC. It can be seen that the surface of precursor was devoid of any tangible pores, while the surface of EAAC (Fig. 11b) has large number of pores of irregular and heterogeneous morphology, which attests a significant development of pore structure. A comparison of the microstructure of EAAC with the char indicates that the activation process plays an important role contributing to pore-formation. 3.8. Activation gases
0.06
Reports on the gaseous byproducts generated during the activation process are seldom reported in literature. Owing to its importance the gases generated during the activation were collected and were analysed for its composition and heating value. Analyses of the gaseous products were mainly composed of CO2 , C2 H2 , H2 , O2 , N2 , CH4 , CO, and the H2 + CO are the main components. Table 9 shows the composition of the gases released in the activation. The high proportion of H2 and CO and the low C2 H2 and CH4 contents can be attributed to the set of gasification reactions shown below,
EAAC
0.05
0.04
dV (ml/g)
Fig. 10. As we can see from Fig. 10, few functional groups were detected, around the wide peak, which located at 3340.48 cm−1 is assigned to O H stretching vibration. The band at 1602.71 cm−1 indicate that there may be exist carbonyl (C O) functional group. The telescopic vibration at 1436.45 cm−1 may be attributed to CH2 stretching vibration. The band at around 1045.18 cm−1 is typically attributed to C O stretching vibration. Finally, the band caused by C H out-of-plane bending vibrations band is located at 876.71 cm−1 . From the band assignment, the chemical structure of the EAAC surface was relatively combined with different OH, CO and CH bonds.
0.03
0.02
0.01
C + H2 O → CO + H2
(1)
C + CO2 → 2CO
(2)
0.00 0
5
10
15
20
25
30
Pore width (nm) Fig. 9. Pore size distribution chart for EAAC.
35
40
Table 9 Composition (vol %) of the activation gases. Composition
CO2
C2 H2
H2
O2
N2
CH4
CO
vol%
0.9
0.1
70.5
0.3
1.6
3.3
23.3
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Fig. 11. SEM images of char (a) and EAAC (b).
(−CH2 −) + H2 O → CO + 2H2
(3)
CO + 3H2 → CH4 + H2 O
(4)
Reaction (1) was the main reaction contributing to the gas rich in hydrogen and carbon monoxide. The reactions are endothermic requiring high energy inputs to promote the reaction. The HV of the gases were determined based on the composition of the gases and the individual HV of their components which estimated to be 10.27 MJ/m3 . A heating value as high as 10.27 MJ/m3 is good enough to run through the turbine to generate power. These gases could be utilized to run the steam generator in the process of AC manufacture which would contribute to reducing the operating expenses of the manufacturing process. Also the mixture of CO and H2 commonly known as the syngas could be utilized to convert into variety of other useful fuels and chemicals through subsequent chemical conversions. 4. Conclusions Eupatorium adenophorum, a harmful biomass is utilized for preparing AC with steam activation having well developed pore structure and favorable functional groups. The key parameters that characterize quality of the porous carbon such as the BET surface area and average pore diameter were estimated to be 1357 m2 /g and 3.31 nm, respectively. The high pore volume and the larger pore diameter render the AC with high proportion of mesopores suitable for liquid phase adsorption. High surface area mesoporous carbons are highly favored for liquid phase application. Additionally the high proportion of H2 to CO generated during the activation process with a HV of 10.27 MJ/m3 could be contributed to improving the commercial manufacturing economics. Acknowledgement The authors would like to express their gratitude to the Specialized Research Fund for the Doctoral Program of Higher Education of China (no. 20115314120014), the Kunming University of Science and Technology Personnel Training Fund (no. KKSY201252077) and the Yunnan Provincial Science and Technology Innovation Talents Scheme-Technological Leading Talent (no.2013HA002) for financial support. References [1] Y. Li, Q. Du, T. Liu, Y. Qi, P. Zhang, Z. Wang, Y. Xia, Preparation of activated carbon from Enteromorpha prolifera and its use on cationic red X-GRL removal, Appl. Surf. Sci. 257 (2011) 10621–10627.
[2] C. Nieto-Delgado, M. Terrones, J.R. Rangel-Mendez, Development of highly microporous activated carbon from the alcoholic beverage industry organic by-products, Biomass Bioenergy 35 (2011) 103–112. [3] A. Ahmadpour, D.D. Do, The preparation of active carbons from coal by chemical and physical activation, Carbon 34 (1996) 471–479. [4] H.L. Mudoga, H. Yucel, N.S. Kincal, Decolorization of sugar syrups using commercial and sugar beet pulp based activated carbons, Bioresour. Technol. 99 (2008) 3528–3533. [5] B.H. Hameed, A.L. Ahmad, K.N.A. Latiff, Adsorption of basic dye (methylene blue) onto activated carbon prepared from rattan sawdust, Dyes Pigm. 75 (2007) 143–149. [6] M. Hejazifar, S. Azizian, H. Sarikhani, Q. Li, D. Zhao, Microwave assisted preparation of efficient activated carbon from grapevine rhytidome for the removal of methyl violet from aqueous solution, J. Anal. Appl. Pyrolysis 92 (2011) 258–266. [7] R. Baccar, J. Bouzid, M. Feki, A. Montiel, Preparation of activated carbon from Tunisian olive-waste cakes and its application for adsorption of heavy metal ions, J. Hazard. Mater. 162 (2009) 1522–1529. [8] R.M. Suzuki, A.D. Andrade, J.C. Sousa, M.C. Rollemberg, Preparation and characterization of activated carbon from rice bran, Bioresour. Technol. 98 (2007) 1985–1991. [9] W. Su, L. Zhou, Y. Zhou, Preparation of microporous activated carbon from raw coconut shell by two-step procedure, Chin. J. Chem. Eng. 14 (2006) 266–269. [10] J.M. Dias, M. Alvim-Ferraz, M.F. Almeida, J. Rivera-Utrilla, Waste materials for activated carbon preparation and its use in aqueous-phase treatment: a review, J. Environ. Manage. 85 (2007) 833–846. [11] W. Sang, L. Zhu, J.C. Axmacher, Invasion pattern of Eupatorium adenophorum Spreng in southern China, Biol. Invasions 12 (2010) 1721–1730. [12] P. Weyerstahl, H. Marschall, I. Seelmann, V.K. Kaul, Constituents of the flower essential oil of Ageratina adenophora (Spreng.) K. et R. from India, Flavour Fragance J. 12 (1997) 387–396. [13] S. Guo, W. Li, L. Zhang, J. Peng, H. Xia, S. Zhang, Kinetics and equilibrium adsorption study of lead(II) onto the low cost adsorbent—Eupatorium adenophorum spreng, Process Saf. Environ. 87 (2009) 343–351. [14] A. Sahoo, B. Singh, O.P. Sharma, Evaluation of feeding value of Eupatorium adenophorum in combination with mulberry leaves, Livest. Sci. 136 (2011) 175–183. [15] S.P.M. Madan, An alternative resource for biogas production, Energy Sources 22 (2000) 713–721. [16] H. Xia, J. Peng, L. Zhang, S. Zhang, Study on the preparation of activated carbon from Eupatorium adenophorum spreng by microwave radiation, Ion Exch. Adsorpt. 24 (2008) 16–24. [17] C. Wu, Y. Qin, J. Zhang, W. Wu, H. Xu, Preparation for activated carbon from the stem of Eupatorium adenophorum spreng by microwave radiation, J. Fujian Agric. For. Univ. 38 (2009) 428–430. [18] Z. Zhang, J. Peng, W. Qu, L. Zhang, Z. Zhang, W. Li, R. Wan, Regeneration of high-performance activated carbon from spent catalyst: optimization using response surface methodology, J. Taiwan Inst. Chem. Eng. 40 (2009) 541–548. [19] A. Dominguez, J.A. Menéndez, Y. Fernandez, J.J. Pis, J.M. Nabais, P.J.M. Carrott, M.M. Carrott, Conventional and microwave induced pyrolysis of coffee hulls for the production of a hydrogen rich fuel gas, J. Anal. Appl. Pyrolysis 79 (2007) 128–135. [20] R. Azargohar, A.K. Dalai, Production of activated carbon from Luscar char: experimental and modelling studies, Microporous Mesoporous Mater. 85 (2005) 219–225. [21] N. Novak, A. Majcen Le Marechal, M. Bogataj, Determination of cost optimal operating conditions for decoloration and mineralization of CI Reactive Blue 268 by UV/H2 O2 process, Chem. Eng. J. 151 (2009) 209–219. [22] B.K. Körbahti, M.A. Rauf, Response surface methodology (RSM) analysis of photo induced decoloration of Toludine Blue, Chem. Eng. J. 136 (2008) 25–30.
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Steam activation of Eupatorium adenophorum for the production of porous carbon and hydrogen rich fuel gas Zhaoqiang Zheng a,b,c , Hongying Xia a,b,c,∗ , C. Srinivasakannan d , Jinhui Peng a,b,c , Libo Zhang a,b,c a
Yunnan Provincial Key Laboratory of Intensification Metallurgy, Kunming 650093, Yunnan, China Key Laboratory of Unconventional Metallurgy, Ministry of Education, Kunming University of Science and Technology, Kunming 650093, Yunnan, China c Faculty of Metallurgical and Energy Engineering, Kunming University of Science and Technology, Kunming 650093, China d Chemical Engineering Program, The petroleum Institute, PO Box 2533, Abu Dhabi, United Arab Emirates b
a r t i c l e
i n f o
Article history: Received 16 March 2014 Accepted 16 August 2014 Available online 27 August 2014 Keywords: Eupatorium adenophorum Activated carbon Hydrogen rich fuel gas Response surface methodology
a b s t r a c t Eupatorium adenophorum was converted into a high-quality activated carbon (EAAC) and hydrogen rich fuel gas via steam activation. The process variables including activation temperature, activation duration and steam flow rate on the adsorption capability and activated carbon yield were identified. Additionally the surface characteristics of EAAC were characterized by nitrogen adsorption isotherms, FTIR and SEM. The operating variables were optimized utilizing the response surface methodology and were identified to be an activation temperature of 950 ◦ C, an activation duration of 60 min and a steam flow rate of 1.2 ml/min with a iodine adsorption capacity of 1031 mg/g and yield of 25%. The key parameters that characterize quality of the porous carbon such as the BET surface area, total pore volume and average pore diameter were estimated to be 1357 m2 /g, 1.1 ml/g and 3.31 nm, respectively. The heating value of fuel gases evolved during the process of activation at optimized process conditions were estimated to be 10.27 MJ/m3 , with the major components being H2 and CO. A high heating value well augurs its utility as a heat source for the whole process which would significantly alter the commercial manufacturing economy. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Activated carbons (AC) are important kinds of porous carbon material with abundantly developed pore structure having high surface area and thermo stability. They are widely used in different industries, for separation and purification of gas and aqueous media [1–3], as catalyst supports [4] and for waste water treatment applications [5,6]. The selection of an appropriate precursor plays an important role in deciding the characteristics of the AC as well as the economics of the manufacturing plant. To identify new precursors that are cheap, accessible and available in large quantity has been a perennial challenge in commercial manufacture for economic benefits [7]. Towards which, different biomass based feedstock such as rice bran, coconut shell and waste materials were used as the raw materials since they are sustainable sources having high fixed carbon content [8–10].
∗ Corresponding author at: Kunming University of Science and Technology, Faculty of Metallurgical and Energy Engineering, Kunming 650093, China. E-mail addresses: [email protected], [email protected] (H. Xia). http://dx.doi.org/10.1016/j.jaap.2014.08.007 0165-2370/© 2014 Elsevier B.V. All rights reserved.
Eupatorium adenophorum is a kind of global exotic weed originated from Mexico, and has spread extensively in many countries around the world such as America, Australia and the countries in Southeast Asia due to its strong ability to adapt to different environmental conditions [11]. Since 1940s, Eupatorium adenophorum has spread extensively in south and western of China. Lots of the farm lands, pasture fields and forests have been destroyed causing huge economic losses. This has drawn the attention of the society and many methods have been developed to control it, such as manual, chemical and biological control, however with no tangible progress in controlling it. In 2003, the Chinese ministry of environmental protection released a list of “The First Batch of Exotic Invasive Species” and Eupatorium adenophorum was rated the first [12,13]. According to the published literatures, Eupatorium adenophorum can be used as bio-pesticide [14], organic fertilizer and feedstuff, feedstock for production of marsh gas [15]. Although, Eupatorium adenophorum can be utilized as a biomass resource to prepare the AC, the relevant literature is very limited. The attempts pertaining to preparation of EAAC has been limited to Xia et al. and Wu et al. [16,17]. Activated carbons have been traditionally produced by the partial gasification of the char either with steam or CO2 or a
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combination of both. The gasification reaction results in removal of most reactive carbon atoms and simultaneously produce a wide range of pores (predominantly micropores), resulting in porous activated carbon. Physical activation is essentially a two-step process, where the carbonization of a carbonaceous material forms the first step, while the second step involves the activation of the resulting char at elevated temperature in presence of suitable oxidizing gases such as carbon dioxide, steam, air or their mixtures. Physical activation is widely adopted industrially for commercial production owing to the simplicity of process and the ability to produce AC with well developed micro porosity and desirable physical characteristics such as the good physical strength. During the activation process, the exhaust gases will certainly be produced by the oxidizing gases, which were discharged into the atmosphere causing environmental concerns. Referring to exhaust gas in the process of preparation of AC is space although the exhaust gas is a rich resource of hydrogen. The objective of present work is to assess the effect of operating conditions to understand the relationship between the process variables and the desired objective function. Towards which the effects of activation temperature, activation duration and steam rate on the adsorption capacity and yield of EAAC were investigated systematically to optimize the process conditions to maximize the iodine adsorption capacity, which reflects the internal surface area. Additionally the exhaust gases under the optimized process conditions were sampled for characterization using Gas Chromatography. The AC prepared under the optimized process conditions were characterized using the nitrogen adsorption isotherm, FTIR and SEM. 2. Materials and methods 2.1. Materials Eupatorium adenophorum was obtained from Kunming, Yunnan Province of China. The raw materials were crushed to a size of 5–7 mm and washed thoroughly with deionized water, then were oven-dried at 105 ◦ C and stored in moisture free environment for utilization in the experiments. The proximate analysis of Eupatorium adenophorum is presented as follow: volatile 76.41%, ash 1.90% and fixed carbon 21.69%. The ultimate analysis of Eupatorium adenophorum represented in weight percent is as follow: carbon 52.37%, hydrogen 6.02%, oxygen 39.62%, nitrogen 1.15% and sulfur 0.84%. 2.2. Experimental methods The carbonization of raw precursors was carried out at a carbonization temperature of 500 ◦ C at the heating rate of 20 ◦ C/min in muffle furnace, for duration of 60 min, under the nitrogen flow atmosphere. The char yield is estimated to be around 35% and the proximate analysis of char (Fig. 1) was as follow: volatile 15.84%, ash 8.86% and fixed carbon 75.30%. The carbon content of the char is found to have increased significantly upon carbonization, while the volatile matter decreased. A self-made tube furnace, which was employed in the activation experiments, is shown in Fig. 2. It mainly consists of four components: the temperature control system (temperature controlled by the input electric power and measured by the thermoelement, with a measurement precision of ±0.5 ◦ C), the flow control system (controlled by the flow meter for steam and N2 ), the activation system (a known amount of the carbonized materials were placed in the platform of quartz reactor fixed in the tube furnace), and the gas analysis system (the gas was collected in the glass bottle filled with water, which was analyzed using GC of Agilent 7890A). Prior to the use of furnace, N2 was purged to displace the air at a pre-set flow rate of 150 cc/min. Subsequently, the materials were heated from the room temperature to the desired temperature. Once the
Fig. 1. The proximate analysis of precursor Eupatorium adenophorum and its chars.
precursors reached the desired temperature the N2 flow was terminated and replaced by steam into the reactor at the desired flow rate for desired activation duration. The completion of activation process was marked by termination of the steam supply and starting of N2 flow until the EAAC were cooled to the room temperature, which were then dried at 105 ◦ C and stored for further characterization. The iodine adsorption capacity is represented as iodine number, is an important parameter widely used to characterize micro porous material. Iodine number was tested for the EAAC according to the National Standard Testing Methods of PR China (GB/T12496.8-1999) [18], while the yield of EAAC was defined as the weight of activated carbon per weight of carbonized materials utilized for activation. The specific surface areas of EAAC produced by the optimum conditions as well as the carbonized char were determined by the BET method using nitrogen as the adsorbate at 77 K utilizing the commonly used Autosorb instrument. Prior to the measurements, the samples were out gassed at 300 ◦ C under nitrogen for at least 12 h. Nitrogen adsorption isotherms of EAAC and char were tested over a relative pressure (P/P0 ) range from 10−7 to 1. The total pore volumes were estimated to be the equivalent liquid volume of the adsorbate (N2 ) at a relative pressure of 0.99. The BET surface area of the sample was calculated by the Brunauer–Emmett–Teller (BET) equation. The pore size distribution was analyzed by using the Non-local Density Functional Theory (NLDFT). Scanning electron microscopy (SEM, Philips XL30ESEM-TMP) analysis was carried out to assess the surface microstructures. The Fourier transform infrared spectroscopy (FTIR) was applied to qualitatively identify the chemical function groups present in the EAAC. FTIR spectra were operating in the range of 4000–400 cm−1 by using AVATAR 330 (Thermo Nicolet CO., USA) Spectrophotometer. The samples of the transmission spectra were prepared by mixing up with KBr crystals at a ratio of 1:100 (samples/KBr) and pressed into a pellet. The gases were analyzed in an Agilent 7890A gas chromatograph fitted with a TCD detector, the TCD was calibrated with the standard gas mixture at fixed intervals. The carrier gas (He) flow rate was 40 ml/min, while the oven temperature was set at 50 ◦ C. The injector and detector temperature were 100 and 180 ◦ C, respectively. The heating values (HV) of the gases were determined based on the composition of gases by the HV of individual components [19]. 2.3. Experimental design RSM was utilized to optimize the activation process as it is a popular statistical tool for modeling and analysis of multi parameter processes. The central composite design (CCD) was employed
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Fig. 2. The modified diagram for the preparation equipment.
Table 1 Independent variables and their levels for central composite design.
Table 3 Analysis of credibility of the model.
Independent variables
Symbol Coded variable levels −1.68179 −1
0
+1
+1.68179
Activation temperature Activation duration Steam flow rate (ml/min)
X1
865.91
900
950
1000
1034.09
X2
34.77
45
60
75
85.23
X3
0.80
1.00
1.3
1.60
1.80
to design the activation experiments [20]. The effects of three independent variables, X1 (activation temperature), X2 (activation duration), X3 (steam flow rate), at five levels were investigated (Table 1). The iodine number and yield of EAAC were taken as the two responses of the designed experiments. A total of 20 experiments consisting of 8 factorial points, 6 axial points and 6 replicates at the central points were employed. The experimental design matrix is provided in Table 2. The experimental data were analyzed using the Design Expert software version 7.1.5 (Stat-Ease Inc., Minneapilis, USA). Optimization of activation conditions for Eupatorium adenophorum was obtained using the software’s numerical and graphical optimization functions.
Source
Std. Dev.
R2
Adj R2
Pred R2
Adeq Precosopm
Iodine number Yeild
14.02 3.56
0.9763 0.9692
0.9550 0.9416
0.8246 0.7641
18.23 21.16
the parameters such as activation temperature, activation duration and steam flow rate. The EAAC are characterized for iodine number, yield and results are listed as well in Table 2. 3.1. Statistical analysis The relationship between the responses (Y1 , Y2 ) and three independent variables (X1 , X2 , X3 ) were established using an appropriate regression model, utilizing the software. For iodine number and yield, the two-factor interaction model was selected as suggested by the software. Experimental runs performed at the center point of all the variables (15–20 runs) were utilized to determine the experimental error. The final empirical models in terms of coded factors (excluding the insignificant terms) for iodine number (Y1 ) and yield (Y2 ) are shown in Eqs. (1) and (2), respectively: Y1 = +1044.49 + 21.19X1 + 15.49X1 + 11.31X3 − 45.76X12 − 42.76X22 − 43.11X32
3. Results and discussion Table 2 shows the experimental conditions adopted for preparation of EAAC as generated by the Design Expert software covering Table 2 Experimental design matrix and results by microwave heating with steam. Run
X1 (◦ C)
X2 (min)
X3 (ml/min)
Y1 (mg/g)
Y2 (%)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
900.00 1000.00 900.00 1000.00 900.00 1000.00 900.00 1000.00 865.91 1034.09 950.00 950.00 950.00 950.00 950.00 950.00 950.00 950.00 950.00 950.00
45.00 45.00 75.00 75.00 45.00 45.00 75.00 75.00 60.00 60.00 34.77 85.23 60.00 60.00 60.00 60.00 60.00 60.00 60.00 60.00
1.00 1.00 1.00 1.00 1.60 1.60 1.60 1.60 1.30 1.30 1.30 1.30 0.80 1.84 1.30 1.30 1.30 1.30 1.30 1.30
855 895 917 952 890 932 919 977 875 943 912 923 900 933 1040 1048 1050 1043 1042 1046
55.50 46.35 33.46 23.64 43.51 31.33 19.72 13.25 52.08 20.45 47.61 18.32 38.77 17.75 23.43 23.50 23.54 23.17 23.62 23.19
Y2 = +23.4 − 6.65X1 − 9.95X2 − 6.31X3 + 2.82X12 + 1.65X22
(1)
(2)
The results obtained from the analysis of variance (ANOVA) were also carried out to prove the validity of the model. Validating the model adequacy is an import part of the data analysis, since it would lead to poor or misleading results if it is an inadequate fit. The analysis of credibility of the model for iodine number and yield was shown Table 3.The quality of model developed was always evaluated using the correlation coefficient (R2 ), which were 0.9763 for Eq. (1) and 0.9348 for Eq. (2), respectively. Both the R2 values were of high proximity to unity, indicating the suitability of the model equation, evidencing good agreement between experimental data and the prediction using the model [21]. For iodine number the Pred R2 of 0.8246 is reasonable agreement with the Adj R2 of 0.9550 (The difference between Pred R2 and Adj R2 within 0.2 is reasonable). Adequate precision measures the signal to noise ratio was observed to be 18.23 for the present experiments, much higher than the desirable ratio greater than 4. For yield the Pred R2 , Adj R2 and Adequate precision were 0.7641, 0.9416 and 21.16. With the above validations in support of the model, it was utilized to navigate the design space to identify the optimum conditions. The ANOVA for the quadratic model of iodine number is presented in Table 4. The model F-value of 45.79 implied the model is
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Table 4 Analysis of variance for the iodine number. Source
Sum of squares
Degree of freedom
Mean square
F-value
Pb > F
Model X1 X2 X3 X1 X2 X1 X3 X2 X3 X1 2 X2 2 X3 2
81036.57 6131.01 3275.43 1747.84 15.13 78.13 253.12 30183.16 26349.27 26786.81
9 1 1 1 1 1 1 1 1 1
9004.06 6131.01 3275.43 1747.84 15.13 78.13 253.12 30183.16 26349.27 26786.81
45.79 31.18 16.66 8.89 0.077 0.40 1.29 153.51 134.01 136.23
<0.0001 0.0002 0.0022 0.0138 0.7872 0.5426 0.2830 <0.0001 <0.0001 <0.0001
Fig. 3. Predicted vs. experimental iodine number of EAAC.
significant. There was only a 0.01% chance that a “Model F-Value” of this large could occur due to noise. Values of “Prob > F” less than 0.05 indicated that the model terms are significant. In this case X1 , X2 , X3 and the interaction terms (X1 2 , X2 2 , X3 2 ) were found to be significant model terms based on the low ‘p’ values. Values greater than 0.1 indicates the model terms were not significant. The ANOVA result of quadratic model corresponding to yield is shown in Table 5. A model F-value of 35.01 and P > F of <0.0001 indicated the suitability of model. In this case, X1 , X2 , X3 along with the interaction parameters (X1 2 , X2 2 ) were found to be significant. In conclusion, the ANOVA results showed that the model was appropriateness to be utilized within the range of the variables covered in the present work.
the figure, the experimental data were evenly distributed on the both sides of the model prediction, indicating the suitability of the model in capturing the correlation between the process and response variables. Based on the F values (Table 4), activation temperature showed the highest of F Value (31.18) indicating it to be the most significant parameters as compared to activation duration and steam flow rate, with the F Value of 16.66 and 8.89, respectively. Three-dimensional response surfaces were created to show the relationships between the independent variables on iodine number as shown in Fig. 4a–c. In all the plots the third variable was maintained at the center point. As can be seen, an increase in the activation temperature activation duration steam flow rate, an increase in the iodine number could be evidenced, indicating the formation of pores due to the gasification reaction of steam with the carbon. The increase in the iodine number sustains until an optimal combinations of the parameter beyond which it was found to decrease. It is well established that the gasification reactions beyond an optimal conditions would contribute to reduction in the surface area due to pore enlargement and pore merger. Hence it is important to identify the optimal process conditions to maximize the surface area. It is well known that the adsorption depends on the pore structure. It is reported that the pore diameter should be at least 1.7 times of the molecular widest dimension in order to be good adsorption site to capture a molecule [23]. The iodine molecule is strongly adsorbed due to its smaller size of 0.27 nm permitting its penetration into micropores under the size of 1 nm [24]. The development of porosity was associated with gasification according to the reaction between the steam and carbon. The extent of the reaction would increase with an increase in the activation temperature, activation duration and steam flow rate. The increase in porosity is expected to be directly proportional to the increase in the carbon conversion. The increase in the micropores can be assessed based on the increase in the iodine adsorption capacity of the carbon. A reduction beyond optimum levels could be due to the higher extent of steam-carbon reaction contributing to pore merger as observed at high temperatures. A similar tendency has been reported in the preparation of AC from Jatropha hull [25], wood sawdust [26] and biodiesel industry solid residue [27]. Table 6 lists the comparison of maximum iodine number of various AC derived from different precursors reported in the literature. As can be seen, the EAAC prepared in the present work has relatively high iodine number as compared with the values reported in literature.
3.3. Yield of EAAC 3.2. Iodine number of EAAC Fig. 3 shows the comparison of predicted versus the experimental data for iodine number of EAAC. Experimental values were the measured response data for a particular run while the predicted values were evaluated using the model Eq. (1) [22]. As seen in Table 5 Analysis of variance for the yield. Source
Sum of squares
Degree of freedom
Mean square
F-value
Pb > F
Model X1 X2 X3 X1 X2 X1 X3 X2 X3 X1 2 X2 2 X3 2
2956.98 603.90 1351.94 544.57 3.18 0.013 1.04 306.77 171.24 44.49
9 1 1 1 1 1 1 1 1 1
328.55 603.90 1351.94 544.57 3.18 0.013 1.04 306.77 171.24 44.49
35.01 64.36 144.07 58.03 0.34 0.001 0.11 32.69 18.25 4.74
<0.0001 <0.0001 <0.0001 <0.0001 0.5736 0.9713 0.7465 0.0002 0.0016 0.0545
The yield of EAAC is an important parameter, which is affected by the activation process and the activation conditions. The model prediction against the actual experimental data on the yield of EAAC is shown in Fig. 5. As can be seen, the experimental data are evenly distributed on the both sides of the model prediction. Based on the F values (Table 5), X2 was found to have the highest of F value of 144.07, implying its significant effect on yield as compared to X1 and X3 . Table 2 compiles the yield of EAAC for each experiment. Three-dimensional response surfaces plot of yield with respect to the activation temperature and activation duration is shown in Fig. 6a–c. From the figures, the yield of EAAC is found to decrease with the increase in all the three parameters, the results indicate the minimum of yield corresponds to the maximum of the three parameters. As can be seen from Fig. 6a and c, the activation duration was found to play the most important role in the yield of EAAC. Moreover, an increase in any of the three parameters effectively contributes to an increase in the extent of C-Steam reaction, contributing to the reduction in the yield of EAAC.
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Fig. 4. Three-dimensional response surface plot of iodine number: effect of activation duration and activation temperature (a), effect of steam flow rate and activation temperature (b), effect of steam flow rate and activation duration (c).
Table 6 Comparison iodine adsorption of AC prepared from different biomass. Precursors
Activating agent
Activation duration (min)
Iodine adsorption (mg/g)
Activation temperature(◦ C)
Reference
Eupatorium adenophorum Rice bran Paper mill sewage sludge Olive-waste cakes
Steam Steam Steam H3 PO4
60 90 40 120
1050 220 180 583
950 850 850 450
Present study [28] [29] [30]
3.4. Process optimization Industrial production of AC augur a high iodine number and yield as both of which contribute to improve the economics of commercial manufacture. However, both the response variables the iodine adsorption capacity (Y1 ) and yield (Y2 ) respond opposite to
each other, demanding identification of an optimum combination of the parameters that maximize the iodine number and the yield of carbon. The optimized goals of these two responses were selected to maximize with the ranges of 855–1050 mg/g, 13.25–55.50%, respectively. The optimum condition was identified by invoking the optimization tool available with the Design Expert Software. The optimized process conditions along with the validation of the optimized process conditions are presented in Table 7. In order to authenticate the identified optimized experimental conditions, three repeat runs were conducted and the average of the three runs is posted in Table 7. The proximity in iodine number and the yield between the repeat runs and the optimized conditions validate the success of the optimization process. 3.5. Characterizations of pore structure
Fig. 5. Predicted vs. experimental yield of EAAC.
Nitrogen adsorption is a standard procedure for determination of porosity of the carbonaceous adsorbents. The nitrogen adsorption isotherm of char and EAAC under the optimum condition was estimated using the Autosorb instrument at 77 K is shown Fig. 7. The shape of the isotherm pertains to adsorption isotherm type II under the IUPAC classification [31]. Fig. 7 compares the nitrogen adsorption capacity of the char with respect to the EAAC. As can
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Fig. 6. Three-dimensional response surface plot of yield: effect of activation duration and activation temperature (a), effect of steam flow rate and activation temperature (b), effect of steam flow rate and activation duration (c).
Table 7 Validation of process optimization. Activation temperature, X1 (◦ C)
Activation duration, X2 (min)
Steam dioxide flow, X3 (ml/min)
Iodine number (mg/g)
Yield(%)
Predicted
Experimental
Predicted
Experimental
950.00
60.00
1.2
1036
1031
25.69
25
Adsorption Volume (mg/g)
500
Char EAAC
400
300
200
100
0 0.0
0.2
0.4
0.6
0.8
Relative Pressure (P/P0) Fig. 7. Nitrogen adsorption isotherm of the EAAC and char.
1.0
be seen, the nitrogen adsorption isotherm of EAAC is exceedingly higher than that of char, clearly indicating the higher amount of pores in EAAC. A continued increase in the nitrogen adsorption capacity beyond a p/p0 value of 0.1, are typical for mesoporous material, which is exhibited by the char as well as the EAAC. This type of isotherm indicates an indefinite multi-layer formation after completion of the monolayer and is found in adsorbents with a wide distribution of pore sizes. Near to the first point of inflexion a monolayer is completed, following with adsorption in successive layers. Microporous materials don’t exhibit an increase in adsorption capacity beyond a p/p0 value of 0.1. The cumulative pore volume plots shown in Fig. 8, while Fig. 9 shows the pore size distribution, both of which substantiate the amount of pores in the mesoporous range, with the average pore diameter estimated to be 3.31 nm. In general steam activation process is known to produce highly microporous material contradicting to the results of the present work. Generation of mesopores are generally attributed to excess burnout or the carbon-steam reaction rendering pore wall thining and eventually pore merger. Although the sample corresponds to the optimized process conditions that maximize the surface area and the yield, the proportion of pore volumes in the mesoporous range are contradicting to the earlier reports related
Z. Zheng et al. / Journal of Analytical and Applied Pyrolysis 110 (2014) 113–121
119
0.60
Char EAAC
3
Adsorption Volume (cm /g)
0.75
0.45
0.30
0.15
0.00 0
5
10
15
20
25
30
35
40 Fig. 10. FTIR of EAAC.
Pore width (nm) Fig. 8. Cumulative pore volume distribution chart for EAAC and char. Table 8 Pore structural parameters of EAAC vs. chars. Properties Pore volume Average pore diameter Micropore volume Mesopore volume BET Surface area
ml/g nm % % m2 /g
EAAC
Chars
1.1 3.31 34 66 1357
0.23 3.6 27.1 72.9 260
to other biomass. High proportion of mesopores with high surface area would render this product highly suitable for removal of high molecular weight compounds from liquid phase. The pore structural parameters are summarized in Table 8. A comparison of the quality of EAAC with the char exhibits a significant increase in the pore volume, the micropore volume and the surface area attributed to the activation process. 3.6. Function groups of EAAC To characterize surface groups on EAAC, Fourier transform infrared (FTIR) transmission spectra were obtained, as shown in
3.7. SEM analysis of microstructure The microscopic structure of the char (before activation) and the EAAC are shown in Fig. 11. Fig. 11a shows the SEM microstructure of char while Fig. 11b shows the SEM microstructure of EAAC. It can be seen that the surface of precursor was devoid of any tangible pores, while the surface of EAAC (Fig. 11b) has large number of pores of irregular and heterogeneous morphology, which attests a significant development of pore structure. A comparison of the microstructure of EAAC with the char indicates that the activation process plays an important role contributing to pore-formation. 3.8. Activation gases
0.06
Reports on the gaseous byproducts generated during the activation process are seldom reported in literature. Owing to its importance the gases generated during the activation were collected and were analysed for its composition and heating value. Analyses of the gaseous products were mainly composed of CO2 , C2 H2 , H2 , O2 , N2 , CH4 , CO, and the H2 + CO are the main components. Table 9 shows the composition of the gases released in the activation. The high proportion of H2 and CO and the low C2 H2 and CH4 contents can be attributed to the set of gasification reactions shown below,
EAAC
0.05
0.04
dV (ml/g)
Fig. 10. As we can see from Fig. 10, few functional groups were detected, around the wide peak, which located at 3340.48 cm−1 is assigned to O H stretching vibration. The band at 1602.71 cm−1 indicate that there may be exist carbonyl (C O) functional group. The telescopic vibration at 1436.45 cm−1 may be attributed to CH2 stretching vibration. The band at around 1045.18 cm−1 is typically attributed to C O stretching vibration. Finally, the band caused by C H out-of-plane bending vibrations band is located at 876.71 cm−1 . From the band assignment, the chemical structure of the EAAC surface was relatively combined with different OH, CO and CH bonds.
0.03
0.02
0.01
C + H2 O → CO + H2
(1)
C + CO2 → 2CO
(2)
0.00 0
5
10
15
20
25
30
Pore width (nm) Fig. 9. Pore size distribution chart for EAAC.
35
40
Table 9 Composition (vol %) of the activation gases. Composition
CO2
C2 H2
H2
O2
N2
CH4
CO
vol%
0.9
0.1
70.5
0.3
1.6
3.3
23.3
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Fig. 11. SEM images of char (a) and EAAC (b).
(−CH2 −) + H2 O → CO + 2H2
(3)
CO + 3H2 → CH4 + H2 O
(4)
Reaction (1) was the main reaction contributing to the gas rich in hydrogen and carbon monoxide. The reactions are endothermic requiring high energy inputs to promote the reaction. The HV of the gases were determined based on the composition of the gases and the individual HV of their components which estimated to be 10.27 MJ/m3 . A heating value as high as 10.27 MJ/m3 is good enough to run through the turbine to generate power. These gases could be utilized to run the steam generator in the process of AC manufacture which would contribute to reducing the operating expenses of the manufacturing process. Also the mixture of CO and H2 commonly known as the syngas could be utilized to convert into variety of other useful fuels and chemicals through subsequent chemical conversions. 4. Conclusions Eupatorium adenophorum, a harmful biomass is utilized for preparing AC with steam activation having well developed pore structure and favorable functional groups. The key parameters that characterize quality of the porous carbon such as the BET surface area and average pore diameter were estimated to be 1357 m2 /g and 3.31 nm, respectively. The high pore volume and the larger pore diameter render the AC with high proportion of mesopores suitable for liquid phase adsorption. High surface area mesoporous carbons are highly favored for liquid phase application. Additionally the high proportion of H2 to CO generated during the activation process with a HV of 10.27 MJ/m3 could be contributed to improving the commercial manufacturing economics. Acknowledgement The authors would like to express their gratitude to the Specialized Research Fund for the Doctoral Program of Higher Education of China (no. 20115314120014), the Kunming University of Science and Technology Personnel Training Fund (no. KKSY201252077) and the Yunnan Provincial Science and Technology Innovation Talents Scheme-Technological Leading Talent (no.2013HA002) for financial support. References [1] Y. Li, Q. Du, T. Liu, Y. Qi, P. Zhang, Z. Wang, Y. Xia, Preparation of activated carbon from Enteromorpha prolifera and its use on cationic red X-GRL removal, Appl. Surf. Sci. 257 (2011) 10621–10627.
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