From atoms to algorithms: a review of machine learning approaches to cathode material innovation in zinc-ion batteries
This review explores how ML accelerates data-driven design and synthesis of Zn-ion batteries, addressing data gaps, interpretability, and validation while emphasizing standardized datasets, explainable AI, and experiment–theory integration.
Authors
- Jenitha Moses
- Ajay Rakkesh Rajendran (ORCID: https://orcid.org/0000-0003-4975-4877)
Institutions
- SRM Institute of Science and Technology (IN)
Publication Details
- Journal
- Journal of Materials Chemistry A
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5ta04723d
- Citations
- 1
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.73