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Authors
He, Yvxin
Deng, Zhongwei https://orcid.org/0000-0002-5834-1583
Chen, Jue
Li, Weihan https://orcid.org/0000-0002-2916-3968
Zhou, Jingjing
Xiang, Fei
Hu, Xiaosong
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Funding
Funding for this research was provided by:
Sichuan Province Science and Technology Support Program
National Natural Science Foundation of China
China Postdoctoral Science Foundation
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This article is maintained by: Elsevier
Article Title: State-of-health estimation for fast-charging lithium-ion batteries based on a short charge curve using graph convolutional and long short-term memory networks
Journal Title: Journal of Energy Chemistry
CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.jechem.2024.06.024
Content Type: article
Copyright: © 2024 Science Press and Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by ELSEVIER B.V. and Science Press. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
