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

Tong Qin; Zhenhao Xi; Ling Zhao; Weikang Yuan

Your Location：

Home >

Browse articles >

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

Updated：2026-01-06

- Monte Carlo simulation of sequential structure control of AN-MA-IA aqueous copolymerization by different operation modes
- Monte Carlo simulation of sequential structure control of AN-MA-IA aqueous copolymerization by different operation modes
- 中国化学工程学报（英文版） 2022年46卷第6期页码：231-242
- Affiliations：
  
  1. State Key Laboratory of Chemical Engineering, East China University of Science and Technology,Shanghai,China,200237
  2. College of Chemistry and Chemical Engineering, Xinjiang University,Urumqi,China,830046
- Author bio：
- Funds：
- DOI：
  中图分类号：
- 纸质出版：2022
- Accepted：
Scan QR Code
Tong Qin, Zhenhao Xi, Ling Zhao, 等. Monte Carlo simulation of sequential structure control of AN-MA-IA aqueous copolymerization by different operation modes[J]. 中国化学工程学报（英文版）, 2022,46(6):231-242.

Tong Qin, Zhenhao Xi, Ling Zhao, Weikang Yuan. Monte Carlo simulation of sequential structure control of AN-MA-IA aqueous copolymerization by different operation modes[J]. Chinese Journal of Chemical Engineering, 2022, 46(6): 231-242.
Tong Qin, Zhenhao Xi, Ling Zhao, 等. Monte Carlo simulation of sequential structure control of AN-MA-IA aqueous copolymerization by different operation modes[J]. 中国化学工程学报（英文版）, 2022,46(6):231-242. DOI：

Tong Qin, Zhenhao Xi, Ling Zhao, Weikang Yuan. Monte Carlo simulation of sequential structure control of AN-MA-IA aqueous copolymerization by different operation modes[J]. Chinese Journal of Chemical Engineering, 2022, 46(6): 231-242. DOI：

摘要

Abstract

The regulation of polyacrylonitrile (PAN) copolymer composition and sequence structure is the precondition for producing high-quality carbon fiber high quality. In this work

the sequential structure control of acrylonitrile (AN)

methyl acrylate (MA) and itaconic acid (IA) aqueous copolymerization was investigated by Monte Carlo (MC) simulation. The parameters used in Monte Carlo were optimized

via

machine learning (ML) and genetic algorithms (GA) using the experimental data from batch copolymerization. The 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 feeding. By 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 CSTRs. Hopefully

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.

关键词

Keywords

references

浏览量

Downloads

CSCD

文章被引用时，请邮件提醒。

Submit

工具集

关联资源

Prediction of methane storage in covalent organic frameworks using big-data-mining approach

Optimization of chemical looping hydrogen generation process via Aspen Plus—Machine learning integration

Research on the prediction model of effective thermal conductivity of marine natural gas hydrate reservoirs based on machine learning

Dew-point corrosion process in the atmospheric tower: Integration of electrochemical analysis and interpretable machine learning

Data scarcity solutions in microreactor modeling co-driven by generic mechanisms and data generation