Nonintrusive thermal-wave sensor for operando quantification of degradation in commercial batteries

Yuqiang Zeng, Fengyu Shen, Buyi Zhang, Jaeheon Lee, Divya Chalise, Qiye Zheng, Yanbao Fu, Sumanjeet Kaur, Sean D. Lubner, Vincent S. Battaglia, Bryan D. McCloskey, Michael C. Tucker and Ravi S. Prasher ()
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Yuqiang Zeng: Southern University of Science and Technology
Fengyu Shen: Lawrence Berkeley National Laboratory
Buyi Zhang: Lawrence Berkeley National Laboratory
Jaeheon Lee: Lawrence Berkeley National Laboratory
Divya Chalise: Lawrence Berkeley National Laboratory
Qiye Zheng: Lawrence Berkeley National Laboratory
Yanbao Fu: Lawrence Berkeley National Laboratory
Sumanjeet Kaur: Lawrence Berkeley National Laboratory
Sean D. Lubner: Lawrence Berkeley National Laboratory
Vincent S. Battaglia: Lawrence Berkeley National Laboratory
Bryan D. McCloskey: Lawrence Berkeley National Laboratory
Michael C. Tucker: Lawrence Berkeley National Laboratory
Ravi S. Prasher: Lawrence Berkeley National Laboratory

Nature Communications, 2023, vol. 14, issue 1, 1-9

Abstract: Abstract Monitoring real-world battery degradation is crucial for the widespread application of batteries in different scenarios. However, acquiring quantitative degradation information in operating commercial cells is challenging due to the complex, embedded, and/or qualitative nature of most existing sensing techniques. This process is essentially limited by the type of signals used for detection. Here, we report the use of effective battery thermal conductivity (keff) as a quantitative indicator of battery degradation by leveraging the strong dependence of keff on battery-structure changes. A measurement scheme based on attachable thermal-wave sensors is developed for non-embedded detection and quantitative assessment. A proof-of-concept study of battery degradation during fast charging demonstrates that the amount of lithium plating and electrolyte consumption associated with the side reactions on the graphite anode and deposited lithium can be quantitatively distinguished using our method. Therefore, this work opens the door to the quantitative evaluation of battery degradation using simple non-embedded thermal-wave sensors.

Date: 2023
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DOI: 10.1038/s41467-023-43808-9

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