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Analysis of Li Metal Anode by Machine Learning Potential
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Genming LAI1, Junyu JIAO1, Yao JIANG2, Jiaxin ZHENG1, 2, Chuying OUYANG2
Journal of the Chinese Ceramic Society | 2023, 51(2) : 469 - 475
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Journal of the Chinese Ceramic Society | 2023, 51(2): 469-475
• Review •
Analysis of Li Metal Anode by Machine Learning Potential
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Genming LAI1, Junyu JIAO1, Yao JIANG2, Jiaxin ZHENG1, 2, Chuying OUYANG2
Affiliations
  • 1.School of Advanced Materials, Peking University, Shenzhen Graduate School, Shenzhen 518055, Guangdong, China
  • 2.Fujian science & technology innovation laboratory for energy devices of China (21C-LAB), Ningde 352100, Fujian, China

    • LAI Genming (1998-), male, Doctoral candidate. E-mail:

About Author:

LAI Genming (1998-), male, Doctoral candidate. E-mail:

Published: 2023-02-20 doi: 10.14062/j.issn.0454-5648.20220793
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Li metal is regarded as an ideal anode for the next-generation secondary batteries. However, the growth of Li-dendrite results in a low coulomb efficiency, thus restricting the commercial application of Li secondary batteries. The mechanism of Li deposition and growth in an atomic scale is still unclear, and there are different opinions about the origin of Li dendrite. Recent work has dealt with the application of machine learning in computational materials science. This review represented the applications of machine learning potential for the study of Li metal anode.

lithium metal anode  /  machine learning  /  molecular dynamics  /  simulation
赖根明, 焦君宇, 蒋耀, 郑家新, 欧阳楚英. 机器学习原子势在锂金属负极中的应用. 硅酸盐学报, 2023 , 51 (2) : 469 -475 . DOI: 10.14062/j.issn.0454-5648.20220793
Genming LAI, Junyu JIAO, Yao JIANG, Jiaxin ZHENG, Chuying OUYANG. Analysis of Li Metal Anode by Machine Learning Potential[J]. Journal of the Chinese Ceramic Society, 2023 , 51 (2) : 469 -475 . DOI: 10.14062/j.issn.0454-5648.20220793
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Year 2023 volume 51 Issue 2
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Article Info
doi: 10.14062/j.issn.0454-5648.20220793
  • Receive Date：2022-09-26
  • Online Date：2026-10-20
  • Published：2023-02-20
Article Data
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History
  • Received：2022-09-26
  • Revised：2022-10-24
Funding
Affiliations
    1.School of Advanced Materials, Peking University, Shenzhen Graduate School, Shenzhen 518055, Guangdong, China
    2.Fujian science & technology innovation laboratory for energy devices of China (21C-LAB), Ningde 352100, Fujian, China

Corresponding:

ZHENG Jiaxin (1985-), male, Ph.D., Associate Professor. E-mail:
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Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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