Machine Learning Enabled Graph Analysis of Particulate Composites: Application to Solid-State Battery Cathodes

Zebin Li, Shimao Deng, Yijin Liu, Jia-Mian Hu

Open source

DOI: 10.1021/acsenergylett.5c04258
Published: 2026-05-14
Container: ACS Energy Letters
Publisher: American Chemical Society (ACS)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1021/acsenergylett.5c04258,
  title = {Machine Learning Enabled Graph Analysis of Particulate Composites: Application to Solid-State Battery Cathodes},
  author = {Zebin Li and Shimao Deng and Yijin Liu and Jia-Mian Hu},
  year = {2026},
  journal = {ACS Energy Letters},
  doi = {10.1021/acsenergylett.5c04258},
  url = {https://doi.org/10.1021/acsenergylett.5c04258}
}

RIS

TY  - JOUR
TI  - Machine Learning Enabled Graph Analysis of Particulate Composites: Application to Solid-State Battery Cathodes
AU  - Zebin Li
AU  - Shimao Deng
AU  - Yijin Liu
AU  - Jia-Mian Hu
PY  - 2026
JO  - ACS Energy Letters
DO  - 10.1021/acsenergylett.5c04258
UR  - https://doi.org/10.1021/acsenergylett.5c04258
ER  -

APA

Li, Z., Deng, S., Liu, Y., & Hu, J. (2026). Machine Learning Enabled Graph Analysis of Particulate Composites: Application to Solid-State Battery Cathodes. ACS Energy Letters. https://doi.org/10.1021/acsenergylett.5c04258

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crossref · retrieved 2026-11-10T18:15:00.689Z