Revealing EDL-Driven Reduction Mechanisms in Binary, Ternary, and Quaternary Fluorinated Electrolytes via an Integrated MD-DFT-ML Framework

Key Points

• This research aims to investigate the mechanisms behind SEI formation in various fluorinated electrolytes using an integrated approach.
• Utilized molecular dynamics simulations to analyze EDL structure and dynamics.
• Employed density functional theory for electronic structure calculations.
• Incorporated machine learning techniques to enhance predictive capabilities.
• Identified significant differences in EDL structure between the bulk and interface, affecting SEI formation.
• Demonstrated that varying electrolyte composition alters reduction pathways and properties of SEI.
• Established a framework that improves prediction accuracy of SEI dynamics and stability.