A machine-learned superionic, Li-metal-compatible, and cost-effective halide electrolyte for all-solid-state Li metal batteries
Abstract
Code of machine learning part of the submitted article "A machine-learned superionic, Li-metal-compatible, and cost-effective halide electrolyte for all-solid-state Li metal batteries".
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