物理学报2023，Vol.72Issue(24)：23-31,9.DOI:10.7498/aps.72.20231058
高分子塌缩相变和临界吸附相变的计算机模拟和机器学习
Computer simulation and machine learning of polymer collapse and critical adsorption phase transitions
罗启睿 1沈一凡 2罗孟波2
作者信息
- 1. 杭州链坊科技有限公司,杭州 310013
- 2. 浙江大学物理学院,杭州 310027
- 折叠
摘要
Abstract
Collapse and critical adsorption of polymers are two crucial phase transitions in polymer science,both are accompanied by significant changes in polymer conformation.In this paper,Langevin dynamics and dynamic Monte Carlo methods are used to simulate the collapse and critical adsorption of polymer,respectively,and corresponding phase transition temperatures are estimated.Meanwhile,a large number of polymer conformations at different temperatures are obtained.In the machine learning method,a large number of extended random coil and collapsed spherical,desorption and adsorption conformations are used to train the neural network,so that the neural network can learn the characteristics of different states of the polymer,and it can quickly and accurately analyze the polymer conformations at different temperatures and obtain the corresponding collapse phase transition temperature and critical adsorption temperature.The results demonstrate that machine learning can correctly calculate the phase transition temperature of polymer system,which provides new ideas and methods for machine learning technology in the study of polymer phase transitions.关键词
高分子/塌缩/临界吸附/机器学习Key words
polymer/collapse/critical adsorption/machine learning引用本文复制引用
罗启睿,沈一凡,罗孟波..高分子塌缩相变和临界吸附相变的计算机模拟和机器学习[J].物理学报,2023,72(24):23-31,9.
