[1]张宾朋,韩秀丽,方书起,等.响应面法优化脱硅稻壳基活性炭对恩诺沙星的吸附[J].郑州大学学报(工学版),2018,39(06):64-68.[doi:10.13705/j.issn.1671-6833.2017.06.030]
 Zhang Binpeng,Han Xiuli,Fang Shuqi,et al.Response Surface Methodology for Optimization of Enrofloxacin Adsorption Using Activated Carbon Derived from the Residue of Desilicated Rice Husk[J].Journal of Zhengzhou University (Engineering Science),2018,39(06):64-68.[doi:10.13705/j.issn.1671-6833.2017.06.030]
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响应面法优化脱硅稻壳基活性炭对恩诺沙星的吸附()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
39
期数:
2018年06期
页码:
64-68
栏目:
出版日期:
2018-10-24

文章信息/Info

Title:
Response Surface Methodology for Optimization of Enrofloxacin Adsorption Using Activated Carbon Derived from the Residue of Desilicated Rice Husk
作者:
张宾朋韩秀丽方书起常春
郑州大学化工与能源学院,河南郑州,450001
Author(s):
Zhengzhou university institute of chemical industry and energy, henan zhengzhou, 450001

关键词:
恩诺沙星活性炭响应面法吸附机理稻壳
Keywords:
DOI:
10.13705/j.issn.1671-6833.2017.06.030
文献标志码:
A
摘要:
以脱硅稻壳残渣(DRH)为原料制备活性炭(AC),并用其处理含抗生素恩诺沙星(ENR)的废水.采用响应面分析方法(RSM)中的中心设计模型(CCD)优化吸附过程中的条件(吸附时间,吸附剂量,ENR浓度,pH).最终得到吸附恩诺沙星的最佳条件是:吸附时间355.3 min,吸附剂量0.40 g·L-1,ENR浓度350 mg·L-1,pH 7.69,预测的最大吸附量是429.4 mg·g-1.吸附平衡数据符合Langmuir和Koble-Corrigan热力学模型,温度为298 K时的最大单层吸附量为444.2 mg·g-1.研究表明,脱硅稻壳基活性炭基于成本低和吸附量大的特点,是处理含恩诺沙星废水的理想材料.
Abstract:
Activated carbon (AC) prepared from residue of desilicated rice husk (DRH) was investigated for the removal of antibiotic enrofloxacin (ENR) from aqueous solution. The operating variables including contact time, adsorbent dosage, ENR concentration and solution pH were optimized using central composite design (CCD) under response surface methodology (RSM) approach. The better conditions for ENR adsorption were found out to be 355.3 min contact time, 0.40·g L-1 adsorbent dosage, 350.0 mg·L-1 ENR concentration, pH 7.69 with predicted adsorption uptake of 429.4 mg·g-1. The experimental equilibrium data agreed well with the Langmuir adsorption model and Koble-Corrigan model. The maximum monolayer adsorption capacity of AC was found to be 444.2 mg·g-1 at 298K. This study indicated that AC based on DRH was a promising candidate because of the lower cost and larger adsorption capacity for the removal of ENR from aqueous solution.

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更新日期/Last Update: 2018-10-26