现代应用物理2025，Vol.16Issue(4)：26-36,11.DOI:10.12061/j.issn.2095-6223.202501012
机器学习在高分子气体分离膜研制中的应用进展
Application of Machine Learning in the Development of Polymer Gas Separation Membranes
摘要
Abstract
This paper summarizes the research progress on the application of machine learning in the development of polymer gas separation membranes.Representative algorithms including support vector machines,decision trees,random forests and deep learning,are introduced.The general process for applying machine learning to materials research is outlined,and the primary methods for dataset construction and material properties are summarized.The advancements in machine learning for screening polymer gas separation membrane materials,analyzing structure-performance relationships,and predicting performance,are highlighted.Finally,future research directions are discussed,focusing on machine learning-assisted investigations of gas transfer mechanisms and inverse design of membrane structures.关键词
机器学习/深度学习/高分子/气体分离膜/构效分析Key words
machine learning/deep learning/polymer/gas separation membrane/structure-performance analysis分类
通用工业技术引用本文复制引用
安少杭,马梦瑶,盛毓强,陈占营,刘蜀疆,常印忠,李奇,王世联..机器学习在高分子气体分离膜研制中的应用进展[J].现代应用物理,2025,16(4):26-36,11.基金项目
国家自然科学基金资助项目(12205126) （12205126）
