Data–Knowledge-Dual-Driven Electrolyte Design for Fast-Charging Lithium Ion Batteries

Yi Yang, Nan Yao, Yu Chen Gao, Xiang Chen*, Yu Xin Huang, Shuo Zhang, Han Bing Zhu, Lei Xu, Yu Xing Yao, Shi Jie Yang, Zheng Liao, Zeheng Li, Xue Fei Wen, Peng Wu, Ting Lu Song, Jin Hao Yao, Jiang Kui Hu, Chong Yan, Jia Qi Huang*, Qiang Zhang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article numbere202505212
JournalAngewandte Chemie - International Edition
Volume64
Issue number24
DOIs
Publication statusPublished - 10 Jun 2025

Keywords

  • Data–knowledge-dual-driven screening
  • Fast charging
  • High temperature
  • Lithium-ion batteries
  • Molecular design

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