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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

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

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