Machine learning for membrane design and discovery
作者机构:Department of Chemical EngineeringTsinghua University100084BeijingChina School of Materials Science&EngineeringTsinghua University100084BeijingChina Department of Chemical and Biomolecular EngineeringNational University of SingaporeSingapore117576Singapore
出 版 物:《Green Energy & Environment》 (绿色能源与环境(英文版))
年 卷 期:2024年第9卷第1期
页 面:54-70页
核心收录:
学科分类:12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 081104[工学-模式识别与智能系统] 0805[工学-材料科学与工程(可授工学、理学学位)] 0703[理学-化学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术(可授工学、理学学位)]
基 金:This work is supported by the National Key R&D Program of China(No.2022ZD0117501) the Singapore RIE2020 Advanced Manufacturing and Engineering Programmatic Grant by the Agency for Science,Technology and Research(A*STAR)under grant no.A1898b0043 Tsinghua University Initiative Scientific Research Program and Low Carbon En-ergy Research Funding Initiative by A*STAR under grant number A-8000182-00-00
主 题:Machine learning Membranes AI for Membrane Data-driven Design
摘 要:Membrane technologies are becoming increasingly versatile and helpful today for sustainable *** Learning(ML),an essential branch of artificial intelligence(AI),has substantially impacted the research and development norm of new materials for energy and *** review provides an overview and perspectives on ML methodologies and their applications in membrane design and dis-covery.A brief overview of membrane technologies isfirst provided with the current bottlenecks and potential *** an appli-cations-based perspective of AI-aided membrane design and discovery,we further show how ML strategies are applied to the membrane discovery cycle(including membrane material design,membrane application,membrane process design,and knowledge extraction),in various membrane systems,ranging from gas,liquid,and fuel cell separation ***,the best practices of integrating ML methods and specific application targets in membrane design and discovery are presented with an ideal paradigm *** challenges to be addressed and prospects of AI applications in membrane discovery are also highlighted in the end.