Special Issue:
TOPICAL REVIEW — Physics research in materials genome
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TOPICAL REVIEW—Physics research in materials genome |
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Discovery and design of lithium battery materials via high-throughput modeling |
Xuelong Wang(王雪龙)1,2, Ruijuan Xiao(肖睿娟)1, Hong Li(李泓)1, Liquan Chen(陈立泉)1 |
1 Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China;
2 University of Chinese Academy of Sciences, Beijing 100049, China |
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Abstract This paper reviews the rapid progress in the field of high-throughput modeling based on the Materials Genome Initiative, and its application in the discovery and design of lithium battery materials. It offers examples of screening, optimization and design of electrodes, electrolytes, coatings, additives, etc. and the possibility of introducing the machine learning method into material design. The application of the material genome method in the development of lithium battery materials provides the possibility to speed up the upgrading of new candidates in the discovery of lots of functional materials.
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Received: 15 May 2018
Revised: 18 September 2018
Accepted manuscript online:
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Fund: Project supported by the National Natural Science Foundation of China (Grant No. 51772321), the Beijing Science and Technology Project (Grant No. D171100005517001), the National Key Research and Development Plan (Grant No. 2017YFB0701602), and the Youth Innovation Promotion Association (Grant No. 2016005). |
Corresponding Authors:
Ruijuan Xiao
E-mail: rjxiao@iphy.ac.cn
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Cite this article:
Xuelong Wang(王雪龙), Ruijuan Xiao(肖睿娟), Hong Li(李泓), Liquan Chen(陈立泉) Discovery and design of lithium battery materials via high-throughput modeling 2018 Chin. Phys. B 27 128801
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