Machine learning-inspired battery material innovation-Reference-Cited by-同舟云学术

Machine learning-inspired battery material innovation

Published:2023 Issue:4 Volume:2 Page:449-464
ISSN:2753-1457
Container-title:Energy Advances
language:en
Short-container-title:Energy Adv.

Author:

Ng Man-Fai¹^ORCID,Sun Yongming²^ORCID,Seh Zhi Wei³^ORCID

Affiliation:

1. Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore, 138632, Republic of Singapore

2. Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China

3. Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore, 138634, Republic of Singapore

Abstract

Data-driven machine learning is a proven technique for battery material discovery and enables the development of sustainable next-generation batteries.

Funder

Agency for Science, Technology and Research

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2023/YA/D3YA00040K

Reference126 articles.

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