Fully printable integrated multifunctional sensor arrays for intelligent lithium-ion batteries

Nuo Sun, Qinlang Rong, Jie Wu, Liting Huang, Stefano Passerini, Hong Li, Hailong Wang, Jing Chen, YongAn Huang (), Zhimeng Liu, Linyu Hu, Kang Xu (), Yuanjing Lin () and Xin He ()
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Nuo Sun: Sichuan University
Qinlang Rong: Sichuan University
Jie Wu: Sichuan University
Liting Huang: Southern University of Science and Technology
Stefano Passerini: Karlsruhe Institute of Technology (KIT)/Helmholtz Institute Ulm (HIU)
Hong Li: Chinese Academy of Sciences
Hailong Wang: Sichuan University
Jing Chen: Sichuan University
YongAn Huang: Huazhong University of Science and Technology
Zhimeng Liu: Sichuan University
Linyu Hu: Southern University of Science and Technology
Kang Xu: SES AI Corp
Yuanjing Lin: Southern University of Science and Technology
Xin He: Sichuan University

Nature Communications, 2025, vol. 16, issue 1, 1-17

Abstract: Abstract Monitoring battery health states and predicting potential hazards are crucial technologies for ensuring the safe operation of battery packs. Current battery risk control often lacks indicators and timeliness for the accidents due to complexity in convoluted and distinct electrochemical behaviors of diverse cell chemistries. Here, we enable lithium-ion batteries with intelligence by integrating a conformal array of multifunctional sensors into the packing foil. Fully printed sensing arrays are prepared by nano-fabricating process with sensing inks, provide advantages with minimized weight increase (49 mg), strong resilience against multi-dimensional disturbances, and long-term stability as integrated system. Operando thermal, mechanical, and chemical features serve as quantitative indicators of degradation across various issues, including over-dis/charging, low-temperature/high-rates Li-plating, internal-short circuit, breakage or thermal abuse, ensuring safety with a lead time. Additionally, sensors for flammable gases and electrolyte leakage directly trigger alarms upon real-time analysis, efficiently providing warnings in complex situations. As important advance in intelligent energy storage management, this platform can be applied universally to various battery-types or pack-levels.

Date: 2025
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DOI: 10.1038/s41467-025-62657-2

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