过程工程学报 ›› 2021, Vol. 21 ›› Issue (7): 794-806.DOI: 10.12034/j.issn.1009-606X.220204
张智霖1(), 丁磊1,2(), 周强1, 余剑1, 郭昌进1, 张德伟2,3
收稿日期:
2020-06-28
修回日期:
2020-09-01
出版日期:
2021-07-28
发布日期:
2021-07-27
通讯作者:
丁磊 zhangzhilin1211@163.com;dinglei1978@163.com
作者简介:
张智霖(1996-),男,安徽省马鞍山市人,硕士研究生,市政工程专业,E-mail: zhangzhilin1211@163.com基金资助:
Zhilin ZHANG1(), Lei DING1,2(), Qiang ZHOU1, Jian YU1, Changjin GUO1, Dewei ZHANG2,3
Received:
2020-06-28
Revised:
2020-09-01
Online:
2021-07-28
Published:
2021-07-27
Contact:
Lei DING zhangzhilin1211@163.com;dinglei1978@163.com
摘要:
以木薯酒精厂生产过程中产生的脱水污泥为原料,采用响应曲面法 Box-Behnken模型优化了木薯酒精污泥基活性炭的制备工艺,同时对最优成品进行一系列表征分析,并将其应用于没食子酸废水的处理研究。活性炭的最优制备条件为活化温度489℃,浸渍时间14 h,活化时间51 min,氯化锌浓度21.53%,该条件下样品的碘吸附值达521.64 mg/g。表征分析显示其表面布有众多孔壁较薄、大小不一的孔洞,金属含量较小,BET比表面积达441.86 m2/g,平均孔径为2.50 nm,拥有丰富的微孔结构,表面富有较多的含氧官能团。考察了活性炭投加量、pH、接触时间、溶液温度对样品去除水中没食子酸的影响。结果表明,样品能够高效去除没食子酸,且随着投加量的增加和pH值降低,没食子酸的去除率呈增长趋势。木薯酒精污泥基活性炭对没食子酸的吸附符合pseudo second-order动力学模型和Freundlich等温模型,最大吸附量为126.72 mg/g。扩散机理显示除颗粒内扩散外也包含液膜扩散过程。热力学分析表明该吸附反应是自发进行的吸热且熵增的过程。本研究将为制备高性能污泥活性炭并应用于高浓度天然有机物废水处理提供理论基础。
中图分类号:
张智霖, 丁磊, 周强, 余剑, 郭昌进, 张德伟. 响应曲面法优化木薯酒精污泥基活性炭制备及对没食子酸的吸附性能[J]. 过程工程学报, 2021, 21(7): 794-806.
Zhilin ZHANG, Lei DING, Qiang ZHOU, Jian YU, Changjin GUO, Dewei ZHANG. Optimization of preparation of cassava alcohol sludge-based activated carbon by response surface methodology and its adsorption properties for gallic acid[J]. The Chinese Journal of Process Engineering, 2021, 21(7): 794-806.
Factor | Code | Level | ||
---|---|---|---|---|
-1 | 0 | 1 | ||
Activation temperature/℃ | A | 400 | 500 | 600 |
Impregnation time/h | B | 6 | 12 | 18 |
Activation time/min | C | 30 | 60 | 90 |
Zinc chloride concentration/% | D | 10 | 20 | 30 |
表1 Box-Behnken实验设计的自变量水平和编码值
Table 1 Independent variable levels and codified values for the Box-Behnken experimental design
Factor | Code | Level | ||
---|---|---|---|---|
-1 | 0 | 1 | ||
Activation temperature/℃ | A | 400 | 500 | 600 |
Impregnation time/h | B | 6 | 12 | 18 |
Activation time/min | C | 30 | 60 | 90 |
Zinc chloride concentration/% | D | 10 | 20 | 30 |
Run | Activation temperature/℃, A | Impregnation time/min, B | Activation time/min, C | Zinc chloride concentration/%, D | Iodine values, R/(mg/g) | |
---|---|---|---|---|---|---|
Experiment | Predict | |||||
1 | 500 | 12 | 90 | 10 | 490.21 | 490.45 |
2 | 500 | 6 | 60 | 30 | 503.17 | 503.89 |
3 | 500 | 12 | 60 | 20 | 525.24 | 521.49 |
4 | 500 | 6 | 90 | 20 | 506.38 | 503.06 |
5 | 500 | 12 | 90 | 30 | 447.16 | 456.53 |
6 | 400 | 18 | 60 | 20 | 493.57 | 490.82 |
7 | 400 | 12 | 30 | 20 | 454.21 | 465.91 |
8 | 500 | 18 | 90 | 20 | 472.93 | 478.86 |
9 | 500 | 18 | 30 | 20 | 515.08 | 516.46 |
10 | 400 | 12 | 60 | 10 | 470.93 | 468.77 |
11 | 500 | 12 | 60 | 20 | 515.63 | 521.49 |
12 | 500 | 18 | 60 | 30 | 502.18 | 493.55 |
13 | 500 | 6 | 60 | 10 | 480.93 | 491.19 |
14 | 600 | 18 | 60 | 20 | 458.98 | 462.14 |
15 | 400 | 6 | 60 | 20 | 492.63 | 489.8 |
16 | 500 | 6 | 30 | 20 | 502.60 | 494.74 |
17 | 500 | 12 | 30 | 30 | 508.62 | 508.69 |
18 | 600 | 12 | 60 | 30 | 445.74 | 445.95 |
19 | 400 | 12 | 90 | 20 | 484.65 | 482.49 |
20 | 500 | 18 | 60 | 10 | 498.15 | 499.05 |
21 | 600 | 12 | 90 | 20 | 434.93 | 424.85 |
22 | 600 | 12 | 30 | 20 | 466.93 | 470.71 |
23 | 600 | 12 | 60 | 10 | 447.05 | 446.89 |
24 | 500 | 12 | 30 | 10 | 476.64 | 467.57 |
25 | 400 | 12 | 60 | 30 | 478.70 | 476.91 |
26 | 500 | 12 | 60 | 20 | 518.76 | 521.49 |
27 | 600 | 6 | 60 | 20 | 462.58 | 465.64 |
28 | 500 | 12 | 60 | 20 | 527.47 | 521.49 |
29 | 500 | 12 | 60 | 20 | 520.36 | 521.49 |
表2 Box-Behnken实验设计结果与实验及预测值
Table 2 Experimental Box-Behnken design matrix and measured and predicted results
Run | Activation temperature/℃, A | Impregnation time/min, B | Activation time/min, C | Zinc chloride concentration/%, D | Iodine values, R/(mg/g) | |
---|---|---|---|---|---|---|
Experiment | Predict | |||||
1 | 500 | 12 | 90 | 10 | 490.21 | 490.45 |
2 | 500 | 6 | 60 | 30 | 503.17 | 503.89 |
3 | 500 | 12 | 60 | 20 | 525.24 | 521.49 |
4 | 500 | 6 | 90 | 20 | 506.38 | 503.06 |
5 | 500 | 12 | 90 | 30 | 447.16 | 456.53 |
6 | 400 | 18 | 60 | 20 | 493.57 | 490.82 |
7 | 400 | 12 | 30 | 20 | 454.21 | 465.91 |
8 | 500 | 18 | 90 | 20 | 472.93 | 478.86 |
9 | 500 | 18 | 30 | 20 | 515.08 | 516.46 |
10 | 400 | 12 | 60 | 10 | 470.93 | 468.77 |
11 | 500 | 12 | 60 | 20 | 515.63 | 521.49 |
12 | 500 | 18 | 60 | 30 | 502.18 | 493.55 |
13 | 500 | 6 | 60 | 10 | 480.93 | 491.19 |
14 | 600 | 18 | 60 | 20 | 458.98 | 462.14 |
15 | 400 | 6 | 60 | 20 | 492.63 | 489.8 |
16 | 500 | 6 | 30 | 20 | 502.60 | 494.74 |
17 | 500 | 12 | 30 | 30 | 508.62 | 508.69 |
18 | 600 | 12 | 60 | 30 | 445.74 | 445.95 |
19 | 400 | 12 | 90 | 20 | 484.65 | 482.49 |
20 | 500 | 18 | 60 | 10 | 498.15 | 499.05 |
21 | 600 | 12 | 90 | 20 | 434.93 | 424.85 |
22 | 600 | 12 | 30 | 20 | 466.93 | 470.71 |
23 | 600 | 12 | 60 | 10 | 447.05 | 446.89 |
24 | 500 | 12 | 30 | 10 | 476.64 | 467.57 |
25 | 400 | 12 | 60 | 30 | 478.70 | 476.91 |
26 | 500 | 12 | 60 | 20 | 518.76 | 521.49 |
27 | 600 | 6 | 60 | 20 | 462.58 | 465.64 |
28 | 500 | 12 | 60 | 20 | 527.47 | 521.49 |
29 | 500 | 12 | 60 | 20 | 520.36 | 521.49 |
Std. Dev. | Mean | C.V./% | PRESS | R2 | Adj R2 | Pred R2 | Adeq precision |
---|---|---|---|---|---|---|---|
7.81 | 486.29 | 1.61 | 4529.62 | 0.96 | 0.91 | 0.77 | 17.20 |
表3 回归模型方程的标准差和R2分析结果
Table 3 Standard deviation and R2 for the regression model equation
Std. Dev. | Mean | C.V./% | PRESS | R2 | Adj R2 | Pred R2 | Adeq precision |
---|---|---|---|---|---|---|---|
7.81 | 486.29 | 1.61 | 4529.62 | 0.96 | 0.91 | 0.77 | 17.20 |
Source | Sum of squares | Degree of freedom | Mean square | F | Prob>F |
---|---|---|---|---|---|
Model | 18880.62 | 14 | 1348.62 | 22.11 | <0.0001 |
A | 2093.10 | 1 | 2093.10 | 34.31 | <0.0001 |
B | 4.56 | 1 | 4.56 | 0.075 | 0.7885 |
C | 642.89 | 1 | 642.89 | 10.54 | 0.0059 |
D | 39.05 | 1 | 39.05 | 0.64 | 0.4370 |
AB | 5.15 | 1 | 5.15 | 0.084 | 0.7757 |
AC | 974.59 | 1 | 974.59 | 15.98 | 0.0013 |
AD | 20.59 | 1 | 20.59 | 0.34 | 0.5705 |
BC | 527.28 | 1 | 527.28 | 8.64 | 0.0108 |
BD | 82.93 | 1 | 82.93 | 1.36 | 0.2631 |
CD | 1407.71 | 1 | 1407.71 | 23.08 | 0.0003 |
A2 | 10819.05 | 1 | 10819.05 | 177.34 | < 0.0001 |
B2 | 81.88 | 1 | 81.88 | 1.34 | 0.2660 |
C2 | 2506.94 | 1 | 2506.94 | 41.09 | < 0.0001 |
D2 | 2865.11 | 1 | 2865.11 | 46.96 | < 0.0001 |
Residual | 854.08 | 14 | 61.01 | ||
Lack of fit | 761.20 | 10 | 76.12 | 3.28 | 0.1319 |
Pure error | 92.89 | 4 | 23.22 | ||
Cor total | 19734.70 | 28 |
表4 拟合模型和模型参数的方差分析统计
Table 4 ANOVA statistics for the fitted model and parameters in the model
Source | Sum of squares | Degree of freedom | Mean square | F | Prob>F |
---|---|---|---|---|---|
Model | 18880.62 | 14 | 1348.62 | 22.11 | <0.0001 |
A | 2093.10 | 1 | 2093.10 | 34.31 | <0.0001 |
B | 4.56 | 1 | 4.56 | 0.075 | 0.7885 |
C | 642.89 | 1 | 642.89 | 10.54 | 0.0059 |
D | 39.05 | 1 | 39.05 | 0.64 | 0.4370 |
AB | 5.15 | 1 | 5.15 | 0.084 | 0.7757 |
AC | 974.59 | 1 | 974.59 | 15.98 | 0.0013 |
AD | 20.59 | 1 | 20.59 | 0.34 | 0.5705 |
BC | 527.28 | 1 | 527.28 | 8.64 | 0.0108 |
BD | 82.93 | 1 | 82.93 | 1.36 | 0.2631 |
CD | 1407.71 | 1 | 1407.71 | 23.08 | 0.0003 |
A2 | 10819.05 | 1 | 10819.05 | 177.34 | < 0.0001 |
B2 | 81.88 | 1 | 81.88 | 1.34 | 0.2660 |
C2 | 2506.94 | 1 | 2506.94 | 41.09 | < 0.0001 |
D2 | 2865.11 | 1 | 2865.11 | 46.96 | < 0.0001 |
Residual | 854.08 | 14 | 61.01 | ||
Lack of fit | 761.20 | 10 | 76.12 | 3.28 | 0.1319 |
Pure error | 92.89 | 4 | 23.22 | ||
Cor total | 19734.70 | 28 |
Sample | SBET/(m2/g) | SMicro/(m2/g) | VTotal/ (cm3/g) | VMicro/(cm3/g) | Daver/nm |
---|---|---|---|---|---|
CASAC | 441.86 | 299.76 | 0.276 | 0.155 | 2.50 |
表5 CASAC的比表面积及孔结构
Table 5 Structural information of CASAC
Sample | SBET/(m2/g) | SMicro/(m2/g) | VTotal/ (cm3/g) | VMicro/(cm3/g) | Daver/nm |
---|---|---|---|---|---|
CASAC | 441.86 | 299.76 | 0.276 | 0.155 | 2.50 |
图8 (a) GA在CASAC上的吸附动力学拟合曲线及(b) CASAC吸附GA的颗粒内扩散模型
Fig.8 (a) The fitted curves of adsorption kinetics of GA on CASAC and (b) intra-particle diffusion models for GA on CASAC
Sample | Pseudo first-order model | Pseudo second-order model | Elovich model | ||||
---|---|---|---|---|---|---|---|
k1/min-1 | R2 | k2/[g/(mg·min)] | R2 | R2 | |||
CASAC | 0.127 | 0.777 | 0.005 | 0.966 | 3243.449 | 0.277 | 0.867 |
表6 GA在CASAC的吸附动力学参数
Table 6 Kinetic parameter of GA adsorption on CASAC
Sample | Pseudo first-order model | Pseudo second-order model | Elovich model | ||||
---|---|---|---|---|---|---|---|
k1/min-1 | R2 | k2/[g/(mg·min)] | R2 | R2 | |||
CASAC | 0.127 | 0.777 | 0.005 | 0.966 | 3243.449 | 0.277 | 0.867 |
Sample | Intra-particle diffusion | ||||||||
---|---|---|---|---|---|---|---|---|---|
R2 | R2 | R2 | |||||||
CASAC | 3.825 | 17.973 | 0.997 | 0.490 | 38.856 | 0.998 | 0.057 | 45.171 | 0.988 |
表7 GA在CASAC上的颗粒内扩散模型拟合参数
Table 7 Parameters of intra-particle diffusion model for GA adsorption on CASAC
Sample | Intra-particle diffusion | ||||||||
---|---|---|---|---|---|---|---|---|---|
R2 | R2 | R2 | |||||||
CASAC | 3.825 | 17.973 | 0.997 | 0.490 | 38.856 | 0.998 | 0.057 | 45.171 | 0.988 |
Sample | Temperature/K | Langmuir model | Freundlich model | ||||
---|---|---|---|---|---|---|---|
K1 | qm/(mg/g) | R2 | K2 | 1/n | R2 | ||
CASAC | 298 | 0.207 | 107.819 | 0.955 | 29.895 | 0.251 | 0.967 |
308 | 0.202 | 115.487 | 0.961 | 31.164 | 0.259 | 0.967 | |
318 | 0.242 | 117.591 | 0.961 | 34.192 | 0.247 | 0.965 |
表8 CASAC对GA的吸附等温线模型拟合参数
Table 8 Parameters of the adsorption isotherm model for GA on CASAC
Sample | Temperature/K | Langmuir model | Freundlich model | ||||
---|---|---|---|---|---|---|---|
K1 | qm/(mg/g) | R2 | K2 | 1/n | R2 | ||
CASAC | 298 | 0.207 | 107.819 | 0.955 | 29.895 | 0.251 | 0.967 |
308 | 0.202 | 115.487 | 0.961 | 31.164 | 0.259 | 0.967 | |
318 | 0.242 | 117.591 | 0.961 | 34.192 | 0.247 | 0.965 |
Sample | T/K | ΔG/(kJ/mol) | ΔH/(kJ/mol) | ΔS/[J/(mol·K)] |
---|---|---|---|---|
CASAC | 298 | -10.37 | 9.78 | 67.62 |
308 | -11.05 | |||
318 | -11.73 |
表9 吸附热力学模型参数
Table 9 Adsorption thermodynamic parameters
Sample | T/K | ΔG/(kJ/mol) | ΔH/(kJ/mol) | ΔS/[J/(mol·K)] |
---|---|---|---|---|
CASAC | 298 | -10.37 | 9.78 | 67.62 |
308 | -11.05 | |||
318 | -11.73 |
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