Engineering and TechnologyNature Communications
Identifying degradation patterns of lithium ion batteries from impedance spectroscopy using machine learning
Y. Zhang, Q. Tang, et al.
Unlock the secrets of Li-ion battery health and lifespan with groundbreaking research from Yunwei Zhang, Qiaochu Tang, Yao Zhang, Jiabin Wang, Ulrich Stimming, and Alpha A. Lee. This study introduces a pioneering system that combines electrochemical impedance spectroscopy and Gaussian process machine learning, utilizing an extensive dataset of over 20,000 EIS spectra to predict battery degradation accurately.
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