Multitarget Generate Electrolyte Additive for Lithium Metal Batteries.

Journal: Advanced materials (Deerfield Beach, Fla.)
Published Date: Jun 18, 2025

Abstract

Electrolyte additives are crucial for accelerating the commercialization of lithium metal batteries (LMBs), yet designing effective additives is challenging due to the need to balance conflicting properties, such as eectrochemical performance and nonflammability. To address this challenge, a deep learning-assisted generative model is developed for multiobjective optimization of electrolyte additives. Overcoming data scarcity, the dataset is expanded using a molecular categorization derivation method, increasing single-property data points to 70 095 multiproperty data points. Coupled with an asynchronous limited decoder and adversarial regulation strategy for latent distribution, this approach achieved 100% generative efficiency for structurally complex and diverse molecules in vast chemical space. The method is validated by discovering 2,4-bis(2-fluoroethoxy) tetrafluorocyclotriphosphazene (DFEPN), a novel additive with excellent flame resistance and stable dual electrode/electrolyte interphases. In a Li||LiFePO full cell with a commercial electrolyte, DFEPN enables an order of magnitude increase in capacity retention, outperforming the state-of-the-art flame-retardant additive ethoxy(pentafluoro)cyclotriphosphazene by 33%. This study offers a pathway for developing safe and reliable lithium battery electrolytes, particularly under severe data constraints, and has broader implications for advanced battery design.

Authors

  • Xiangyang Liu
    College of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin City, 132022, China.
  • Jianchun Chu
    Key Laboratory of Thermal Fluid Science and Engineering of MOE, School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an, 710049, China.
  • Sa Xue
    Key Laboratory of Thermal Fluid Science and Engineering of MOE, School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an, 710049, China.
  • Daquan Wang
    School of Chemistry, Xi'an Jiaotong University, Xi'an, 710049, China.
  • Zhuoyang Lu
    Key Laboratory of Biomedical Information Engineering of MOE, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China.
  • Meng Zhang
    College of Software, Beihang University, Beijing, China.
  • Yongqi Liu
    Gansu University Key Laboratory for Molecular Medicine & Chinese Medicine Prevention and Treatment of Major Diseases, Gansu University of Chinese Medicine, Lanzhou, China; Key Laboratory of Dunhuang Medical and Transformation, Ministry of Education of The People's Republic of China, Gansu University of Chinese Medicine, Lanzhou, China. Electronic address: liuyongqi73@163.com.
  • Xin Xu
    State Key Laboratory of Oral Diseases, Sichuan University, Chengdu, China.
  • Yilin Zhang
    Department of Preventive Medicine, School of Public Health, Fujian Medical University; and Key Laboratory of Environment and Health, Fujian Province University, 1 North Xue-Fu Rd, Minhou, Fuzhou, 350122, Fujian Province, China.
  • Jiangang Long
    School of Life Science and Technology, Xi'an Jiaotong University, 710049 Shaanxi, China.
  • Lingjie Meng
    School of Chemistry, Xi'an Jiaotong University, Xi'an, 710049, China.
  • Jiayin Yuan
    Department of Chemistry, Stockholm University, Svante Arrheniusväg 16C, Stockholm, 106 91, Sweden.
  • Maogang He
    Key Laboratory of Thermal Fluid Science and Engineering of MOE, School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an, 710049, China.

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