Decoding Lithium Metal Battery Degradation with Symmetric‐Cell Artificial Intelligence Diagnostics (SAID)
Abstract
Abstract While the underlying crosstalk effect between cathode and anode complicates the understanding of lithium metal degradation utilizing asymmetric (full)‐cell data, employing a symmetric cell configuration enables isolation of contributions from specific electrodes. In this study, a symmetric‐cell artificial intelligence diagnostics (SAID) is devised to decipher lithium metal anode degradation. Leveraging easily accessible, early‐cycle lithium | lithium symmetric‐cell data, SAID is demonstrated to accurately predict the elbow points (indicators of polarization acceleration) with a test mean absolute percentage error of 13.3%. More importantly, SAID reveals the persistent role of an initial‐nucleation‐related fingerprint in determining long‐term cell polarization, which is validated through experiments and extended to full cells across different electrolytes. This approach, therefore, not only offers valuable insights into battery design but also exhibits great potential in uncovering hidden chemical correlations and advancing the field of energy storage in general.
Article Details
Authors (10)
Bo‐Bo Zou
Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu Sichuan 611731 China
Kun‐Yu Liu
Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu Sichuan 611731 China
Yu Yan
Xin‐He Liu
Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu Sichuan 611731 China
Hong‐Li Long
Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu Sichuan 611731 China
Meng‐Yu Li
Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu Sichuan 611731 China
Hao‐Bo Zhang
Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu Sichuan 611731 China
Kai‐Xi You
Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu Sichuan 611731 China
Mi Chen
Xinyan Liu
Institute of Fundamental and Frontier Science