Machine-learning approaches for the discovery of electrolyte materials for solid-state lithium batteries

HIGHLIGHTS

• who: Shengyi Hu and Chun Huang from the Department of Materials, Imperial College London, London , AZ, UK have published the research work: Machine-Learning Approaches for the Discovery of Electrolyte Materials for Solid-State Lithium Batteries, in the Journal: Batteries 2023, 9, 228. of /2023/
• what: The model was able to provide a screening for 20 billion ternary and quaternary lithium-containing compounds at an extremely fast speed compared with DFT calculations.
• how: This review introduces common ML techniques employed in materials discovery and an overview of ML applications in lithium SSE discovery . . .
  

   

  

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