文献类型：期刊文献

英文题名：Modeling and kinetics study of Bisphenol A (BPA) degradation over an FeOCl/SiO2 Fenton-like catalyst

作者：Yang, Xue-jing[1,2]; Xu, Xi-meng[1]; Xu, Xin-chao[1]; Xu, Jing[1]; Wang, Hua-lin[1,2]; Semiat, Raphael[3]; Han, Yi-fan[1,4]

机构：[1] State Key Laboratory of Chemical Engineering, East China University of Science and Technology [ECUST], Shanghai, 200237, China; [2] State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process, ECUST, Shanghai, 200237, China; [3] The Wolfson Department of Chemical Engineering, Technion, Israel Institute of Technology Technion City, Haifa, 32000, Israel; [4] Research Center of Heterogeneous Catalysis and Engineering Sciences, School of Chemical Engineering and Energy, Zhengzhou University, Zhengzhou, 450001, China

年份：2016

卷号：276

起止页码：85

外文期刊名：Catalysis Today

收录：EI(收录号：20162202447833)

语种：英文

外文关键词：Kinetic theory - Kinetics - Activation energy - Catalysts - Phenols - Integral equations - Iron compounds - Rate constants

摘要：A heterogeneous Fenton-like catalyst was used for the oxidation of Bisphenol A (BPA), which is a typical endocrine disruptor. A simple semi-empirical kinetic equation was developed to define the effects of experimental conditions (initial concentration of H2O2, initial concentration of BPA, temperature and the catalyst loading) on the reaction rate. The plausible pathway of the degradation process was proposed. A pseudo-first-order reaction rate expression with respect to BPA concentration was developed to fit all data for these experiments, and the equation of kobs (observed rate constant) was obtained with the apparent activation energy of 42.2 kJ/mol. In order to reduce the operational cost, the values of parameters (temperature, initial concentration of H2O2 and pH) that optimize the catalytic performance were studied by means of a response surface methodology. Finally, a plausible mechanism was proposed on the basis of kinetics and optimization studies, which illustrates the reaction process and optimization in a microscopic view. ? 2016 Elsevier B.V.