A machine-learned superionic, Li-metal-compatible, and cost-effective halide electrolyte for all-solid-state Li metal batteries

Zenodo (CERN European Organization for Nuclear Research) 2026 Open access

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Authors: Haoyu Yin
DOI: 10.5281/zenodo.18394285
Cited by: 0

Abstract

The data and source code of the machine learning part in the article.

Fields of Study & Subjects

Advanced Battery Materials and Technologies Machine Learning in Materials Science Advancements in Battery Materials

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
27 January 2026