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Detecting lithium plating dynamics in a solid-state battery with operando X-ray computed tomography using machine learning

Engineering and Technology

Detecting lithium plating dynamics in a solid-state battery with operando X-ray computed tomography using machine learning

Y. Huang, D. Perlmutter, et al.

Discover batternYNet, an innovative machine learning method developed by Ying Huang and colleagues for detecting lithium structures in operando X-ray micro-computed tomography datasets. This groundbreaking approach enhances the quality control of solid-state batteries and sheds light on electrode changes, promising to revolutionize Li-metal battery design.

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