Discovery and design of lithium battery materials via high-throughput modeling

被引：2

作者：

Wang, Xuelong ^{[1
,2
]}

Xiao, Ruijuan ^{[1
]}

Li, Hong ^{[1
]}

Chen, Liquan ^{[1
]}

机构：

[1] Chinese Acad Sci, Inst Phys, Beijing 100190, Peoples R China

[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China

来源：

CHINESE PHYSICS B | 2018年 / 27卷 / 12期

基金：

中国国家自然科学基金;

关键词：

Materials Genome Initiative; lithium battery materials; high-throughput simulations; material design; COMBINATORIAL APPROACH; SOLID ELECTROLYTES; ION CONDUCTORS; OPTIMIZATION; CHALLENGES; ELECTRODES; VOLTAGE; PROJECT; OXIDES;

D O I：

10.1088/1674-1056/27/12/128801

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

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.

引用

页数：8

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