Machine-learning-revealed statistics of the particle-carbon/binder detachment in lithium-ion battery cathodes

Machine-learning-revealed statistics of the particle-carbon/binder detachment in lithium-ion battery cathodes

Developing understanding of degradation phenomena in nickel rich cathodes is under intense investigation. Here the authors use learning-assisted statistical analysis and experiment-informed mathematical modelling to resolve the microstructure of a Ni-rich NMC composite cathode.

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Autores principales: Zhisen Jiang, Jizhou Li, Yang Yang, Linqin Mu, Chenxi Wei, Xiqian Yu, Piero Pianetta, Kejie Zhao, Peter Cloetens, Feng Lin, Yijin Liu
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Science
Q
Acceso en línea:https://doaj.org/article/d50a812eeddf43fb90c08ddfa098a381
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spelling oai:doaj.org-article:d50a812eeddf43fb90c08ddfa098a3812021-12-02T14:41:02ZMachine-learning-revealed statistics of the particle-carbon/binder detachment in lithium-ion battery cathodes10.1038/s41467-020-16233-52041-1723https://doaj.org/article/d50a812eeddf43fb90c08ddfa098a3812020-05-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-16233-5https://doaj.org/toc/2041-1723Developing understanding of degradation phenomena in nickel rich cathodes is under intense investigation. Here the authors use learning-assisted statistical analysis and experiment-informed mathematical modelling to resolve the microstructure of a Ni-rich NMC composite cathode.Zhisen JiangJizhou LiYang YangLinqin MuChenxi WeiXiqian YuPiero PianettaKejie ZhaoPeter CloetensFeng LinYijin LiuNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-9 (2020)
institution DOAJ
collection DOAJ
language EN
topic Science
Q
spellingShingle Science
Q
Zhisen Jiang
Jizhou Li
Yang Yang
Linqin Mu
Chenxi Wei
Xiqian Yu
Piero Pianetta
Kejie Zhao
Peter Cloetens
Feng Lin
Yijin Liu
Machine-learning-revealed statistics of the particle-carbon/binder detachment in lithium-ion battery cathodes
description Developing understanding of degradation phenomena in nickel rich cathodes is under intense investigation. Here the authors use learning-assisted statistical analysis and experiment-informed mathematical modelling to resolve the microstructure of a Ni-rich NMC composite cathode.
format article
author Zhisen Jiang
Jizhou Li
Yang Yang
Linqin Mu
Chenxi Wei
Xiqian Yu
Piero Pianetta
Kejie Zhao
Peter Cloetens
Feng Lin
Yijin Liu
author_facet Zhisen Jiang
Jizhou Li
Yang Yang
Linqin Mu
Chenxi Wei
Xiqian Yu
Piero Pianetta
Kejie Zhao
Peter Cloetens
Feng Lin
Yijin Liu
author_sort Zhisen Jiang
title Machine-learning-revealed statistics of the particle-carbon/binder detachment in lithium-ion battery cathodes
title_short Machine-learning-revealed statistics of the particle-carbon/binder detachment in lithium-ion battery cathodes
title_full Machine-learning-revealed statistics of the particle-carbon/binder detachment in lithium-ion battery cathodes
title_fullStr Machine-learning-revealed statistics of the particle-carbon/binder detachment in lithium-ion battery cathodes
title_full_unstemmed Machine-learning-revealed statistics of the particle-carbon/binder detachment in lithium-ion battery cathodes
title_sort machine-learning-revealed statistics of the particle-carbon/binder detachment in lithium-ion battery cathodes
publisher Nature Portfolio
publishDate 2020
url https://doaj.org/article/d50a812eeddf43fb90c08ddfa098a381
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