Data–Knowledge‐Dual‐Driven Electrolyte Design for Fast‐Charging Lithium Ion Batteries
Yi Yang, Nan Yao, Yuchen Gao, Xiang Chen, Yuxin Huang, Shuo Zhang, Han‐Bing Zhu, Lei Xu, Yuxing Yao, Shi-Jie Yang, Zheng Liao, Zeheng Li, Xue‐Fei Wen, Peng Wu, Tinglu Song, Jin‐Hao Yao, Jiang‐Kui Hu, Chong Yan, Jia‐Qi Huang, Xue‐Qiang Zhang
Abstract
Abstract Electric vehicles (EVs) starve for minutes‐level fast‐charging lithium‐ion batteries (LIBs), while the heat gathering at high‐rate charging and torridity conditions has detrimental effects on electrolytes, triggering rapid battery degradation and even safety hazards. However, the current research on high‐temperature fast‐charging (HTFC) electrolytes is very lacking. We revolutionized the conventional paradigm of developing HTFC electrolytes integrating with high‐throughput calculation, machine‐learning techniques, and experimental verifications to establish a data–knowledge‐dual‐driven approach. Ethyl trimethylacetate was efficiently screened out based on the approach and enabled batteries to work under high temperatures with distinctly restricted side reactions. A stable and highly safe fast‐charging (15‐min charging to 80% capacity) cycling without Li plating was achieved over 4100 cycles at 45 °C based on 181 Wh kg −1 pouch cells, demonstrating the state‐of‐the‐art in this field.