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摘要
简要介绍了材料研究领域常用的机器学习算法,探讨了通过数据挖掘技术进行材料研究的方法流程,回顾了机器学习技术在多孔碳、沸石和金属有机骨架3类重要吸附材料研究中的典型案例,最后对这一技术在气体吸附材料研发中的应用前景进行了展望。
Abstract
Machine learning techniques,which have rapidly developed in recent years,are increasingly applied to assist in discovery of gas adsorption materials.The machine learning algorithms commonly used in the field of materials research are introduced,and the process for materials research through data mining techniques is explored.Typical cases of machine learning techniques in the research of three types of important adsorbent materials are reviewed,including porous carbon,zeolite and metal-organic framework.An outlook on the application of this technique in the R&D of gas adsorbent materials is provided.
关键词
气体吸附材料
/
金属有机骨架
/
沸石
/
多孔碳
/
机器学习
Key words
material for gas adsorption
/
metal-organic framework
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zeolite
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porous carbon
/
machine learning
Author summay
机器学习技术在气体吸附多孔材料研究中的应用进展[J].
, 2022, 42(4): 17-22 DOI:10.16606/j.cnki.issn0253-4320.2022.04.004
