Analysis of Artificial Microstructure of Li-ion Battery Electrode Using Persistent Homology and Machine Learning

Kanji MIYAZAKI; Yoichi TAKAGISHI; Tatsuya YAMAUE

doi:10.5796/electrochemistry.25-00120

Electrochemistry

Online ISSN : 2186-2451
Print ISSN : 1344-3542
ISSN-L : 1344-3542

This article has now been updated. Please use the final version.

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Analysis of Artificial Microstructure of Li-ion Battery Electrode Using Persistent Homology and Machine Learning

Kanji MIYAZAKI, Yoichi TAKAGISHI, Tatsuya YAMAUE

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Keywords: Li-ion Battery, Persistent Homology, Machine Learning, Material Design

JOURNAL OPEN ACCESS Advance online publication

Article ID: 25-00120

DOI https://doi.org/10.5796/electrochemistry.25-00120

A newer version of this article is available.

The final version of this article is now available: Vol. 93 (2025), No. 11 pp. 117006-117006

UNCORRECTED PROOF： October 31, 2025
ACCEPTED MANUSCRIPT： October 16, 2025

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This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License (CC BY-NC-SA, https://creativecommons.org/licenses/by-nc-sa/4.0/), which permits non-commercial reuse, distribution, and reproduction in any medium by share-alike, provided the original work is properly cited. For permission for commercial reuse, please email to the corresponding author. [DOI: 10.5796/electrochemistry.25-00120].
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