首页|基于高通量形式下的储氢MOFs材料筛选模拟研究进展

基于高通量形式下的储氢MOFs材料筛选模拟研究进展

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氢能的储运对于氢能发展有着重大意义,近年来储氢金属有机骨架材料(MOFs)的研究显著增长.围绕储氢MOFs材料的模拟与理论计算、储氢材料数据库、储氢MOFs材料高通量结构筛选与机器学习理论设计等方面展开论述和总结,并整理和阐述计算模拟方法在储氢MOFs材料方面的研究思路与进展,为促进储氢MOFs材料的快速应用提供理论依据.
Research progress on hydrogen storage MOFs materials based on high-throughput screening and simulation
Hydrogen storage and transport is of great significance to the development of hydrogen energy,and the research on metal-organic frameworks(MOFs)for hydrogen storage has grown significantly in recent years.The paper discusses and summarises the simulation and theoretical calculation of MOFs materials for hydrogen storage,database of hydrogen storage materials,high-throughput structure screening of MOFs materials for hydrogen storage and theoretical design of machine learning,etc.The paper also collates and elaborates the research ideas and progress of computational simulation methods in MOFs materials for hydrogen storage,which provides theoretical basis for promoting the rapid application of MOFs materials for hydrogen storage.

energy storage technologyhydrogen energyhydrogen storage MOFs materialmolecular simu-lationhigh throughput computing technologymachine learning

吕瑞琪、徐向亚、李蔚、刘东兵

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中石化(北京)化工研究院有限公司 催化科学研究所,北京 100013

储能技术 氢能 储氢MOFs材料 分子模拟 高通量计算技术 机器学习

中国石油化工股份有限公司北京化工研究院院控项目

G6001-21-ZS-0224

2024

工业催化
西北化工研究院

工业催化

CSTPCD
影响因子:0.504
ISSN:1008-1143
年,卷(期):2024.32(9)
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