Machine learning-based design of electrocatalytic materials towards high-energy lithium||sulfur batteries development

Machine learning-based design of electrocatalytic materials towards high-energy lithium||sulfur batteries development

Abstract The practical development of Li | |S batteries is hindered by the slow kinetics of polysulfides conversion reactions during cycling. To circumvent this limitation, researchers suggested the use of transition metal-based electrocatalytic materials in the sulfur-based positive electrode. Howe...

Full description

Saved in:
Bibliographic Details
Main Authors: Zhiyuan Han, An Chen, Zejian Li, Mengtian Zhang, Zhilong Wang, Lixue Yang, Runhua Gao, Yeyang Jia, Guanjun Ji, Zhoujie Lao, Xiao Xiao, Kehao Tao, Jing Gao, Wei Lv, Tianshuai Wang, Jinjin Li, Guangmin Zhou
Format: Article
Language:English
Published: Nature Portfolio 2024-09-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-024-52550-9
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41467-024-52550-9

Similar Items