文献类型：期刊文献

中文题名：Electroreduction of hexavalent chromium using a porous titanium flow-through electrode and intelligent prediction based on a back propagation neural network

作者：Xinwan Zhang[1];Guangyuan Meng[1];Jinwen Hu[1];Wanzi Xiao[1];Tong Li[2];Lehua Zhang[1,3,4];Peng Chen[1]

机构：[1]National Engineering Laboratory for Industrial Wastewater Treatment,School of Resources and Environmental Engineering,East China University of Science and Technology,Shanghai 200237,China;[2]Continuing Education Center,Bozhou University,Bozhou 236800,China;[3]State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process,East China University of Science and Technology,Shanghai 200237,China;[4]Shanghai Institute of Pollution Control and Ecological Security,Shanghai 200092,China

年份：2023

卷号：17

期号：8

起止页码：69

中文期刊名：Frontiers of Environmental Science & Engineering

外文期刊名：环境科学与工程前沿(英文)

收录：Scopus;CSCD:【CSCD2023_2024】；PubMed;

基金：supported by the National Key Research and Development Program of China(No.2019YFC0408202);the National Natural Science Foundation of China(No.21876050).

语种：英文

中文关键词：Flow-through electrode;Hexavalent chromium;Heavy metals;Neural network;Artificial intelligence

摘要：Flow-through electrodes have been demonstrated to be effective for electroreduction of Cr(VI),but shortcomings are tedious preparation and short lifetimes.Herein,porous titanium available in the market was studied as a flow-through electrode for Cr(VI)electroreduction.In addition,the intelligent prediction of electrolytic performance based on a back propagation neural network(BPNN)was developed.Voltametric studies revealed that Cr(VI)electroreduction was a diffusion-controlled process.Use of the flow-through mode achieved a high limiting diffusion current as a result of enhanced mass transfer and favorable kinetics.Electroreduction of Cr(VI)in the flow-through system was 1.95 times higher than in a parallel-plate electrode system.When the influent(initial pH 2.0 and 106 mg/L Cr(VI))was treated at 5.0 V and a flux of 51 L/(h·m2),a reduction efficiency of~99.9%was obtained without cyclic electrolysis process.Sulfate served as the supporting electrolyte and pH regulator,as reactive CrSO72?species were formed as a result of feeding HSO4?.Cr(III)was confirmed as the final product due to the sequential three-electron transport or disproportionation of the intermediate.The developed BPNN model achieved good prediction accuracy with respect to Cr(VI)electroreduction with a high correlation coefficient(R2=0.943).Additionally,the electroreduction efficiencies for various operating inputs were predicted based on the BPNN model,which demonstrates the evolutionary role of intelligent systems in future electrochemical technologies.