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Identifying degradation patterns of lithium ion batteries from impedance spectroscopy using machine learning

Engineering and Technology

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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