Monte Carlo simulation of sequential structure control of AN-MA-IA aqueous copolymerization by different operation modes

作     者：Tong Qin Zhenhao Xi Ling Zhao Weikang Yuan Tong Qin;Zhenhao Xi;Ling Zhao;Weikang Yuan

作者机构：State Key Laboratory of Chemical EngineeringEast China University of Science and TechnologyShanghai 200237China College of Chemistry and Chemical EngineeringXinjiang UniversityUrumqi 830046China 

出 版 物：《Chinese Journal of Chemical Engineering》 (中国化学工程学报（英文版）)

年 卷 期：2022年第35卷第6期

页      面：231-242页

核心收录：

学科分类：08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 080502[工学-材料学] 

基　　金：The authors gratefully acknowledge the supports from the National Natural Science Foundation of China(21878256,21978089) the National Key Research and Development Program of China(2016YFB0302701) the Fundamental Research Funds for the Central Universities(22221818010) Programe of Introducing Talents of Discipline to Universities(B20031) 

主　　题：Polyacrylonitrile Monte Carlo simulation Machine learning Genetic algorithms Sequence structure Operation method 

摘      要：The regulation of polyacrylonitrile(PAN)copolymer composition and sequence structure is the precondition for producing high-quality carbon fiber high *** this work,the sequential structure control of acrylonitrile(AN),methyl acrylate(MA)and itaconic acid(IA)aqueous copolymerization was investigated by Monte Carlo(MC)*** parameters used in Monte Carlo were optimized via machine learning(ML)and genetic algorithms(GA)using the experimental data from batch *** results reveal that it is difficult to control the aqueous copolymerization to obtain PAN copolymer with uniform sequence structure by batch polymerization with one-time *** contrary,it is found that the PAN copolymer with uniform composition and sequence structure can be obtained by adjusting IA feeding quantity in each reactor of a train of five ***,the results obtained in this work can provide valuable information for the understanding and optimization of AN copolymerization process to obtain high-quality PAN copolymer precursor.