How Machine Learning Has Driven the Development of Rechargeable Ion Batteries

Role: First author and project coordinator.

Contribution: Led the conceptualization and overall planning of the review; designed the analytical framework and manuscript structure; coordinated literature collection and data organization with co-authors; designed and prepared the principal figures; and took primary responsibility for scientific synthesis, manuscript writing, revision, and quality control.

This review systematically examines machine-learning workflows for rechargeable battery research, covering data acquisition and preprocessing, model development and interpretation, and applications across different battery chemistries. It further discusses emerging directions involving large language models, reinforcement learning, autonomous experimentation, and closed-loop materials discovery.

Recommended citation: Liu, H.; Li, S.; Zhu, S.; Hu, Y.; Han, X.; Shi, C.; He, F.; He, C.; Chen, B.; Zhao, N. (2025). "How Machine Learning Has Driven the Development of Rechargeable Ion Batteries." Advanced Energy Materials 15, e04095.
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