Sensing as the key to battery lifetime and sustainability
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DOI: 10.1038/s41893-022-00859-y
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Cited by:
- Jiang, Bo & Tao, Siyi & Wang, Xueyuan & Zhu, Jiangong & Wei, Xuezhe & Dai, Haifeng, 2023. "Mechanics-based state of charge estimation for lithium-ion pouch battery using deep learning technique," Energy, Elsevier, vol. 278(PA).
- 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 & Ravi , 2023. "Nonintrusive thermal-wave sensor for operando quantification of degradation in commercial batteries," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
- Fu Liu & Wenqing Lu & Jiaqiang Huang & Vanessa Pimenta & Steven Boles & Rezan Demir-Cakan & Jean-Marie Tarascon, 2023. "Detangling electrolyte chemical dynamics in lithium sulfur batteries by operando monitoring with optical resonance combs," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
- Wenxin Mei & Zhi Liu & Chengdong Wang & Chuang Wu & Yubin Liu & Pengjie Liu & Xudong Xia & Xiaobin Xue & Xile Han & Jinhua Sun & Gaozhi Xiao & Hwa-yaw Tam & Jacques Albert & Qingsong Wang & Tuan Guo, 2023. "Operando monitoring of thermal runaway in commercial lithium-ion cells via advanced lab-on-fiber technologies," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
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