电解质
电池(电)
锂(药物)
对偶(语法数字)
材料科学
计算机科学
降级(电信)
离子
锂离子电池
汽车工程
工作(物理)
化学
工程类
电极
机械工程
物理
功率(物理)
电信
热力学
艺术
文学类
有机化学
物理化学
医学
内分泌学
作者
Yi Yang,Nan Yao,Yuchen Gao,Xiang Chen,Yuxin Huang,Shuo Zhang,Huilong Zhu,Lei Xu,Yuxing Yao,Shi-Jie Yang,Zheng Gen Liao,Zeheng Li,Xue‐Fei Wen,Peng Wu,Tinglu Song,Jiandong Yao,Jiang‐Kui Hu,Chong Yan,Jia‐Qi Huang,Xue‐Qiang Zhang
标识
DOI:10.1002/anie.202505212
摘要
Electric vehicles starve for minutes‐level fast‐charging lithium‐ion batteries, while the heat gathering at high‐rates charging and torridity‐condition have 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‐art in this field.
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