Enabling accurate modelling of materials for solid electrolyte interphase in lithium-ion batteries using effective machine learning interatomic potentials

Key Points

• Accurate modeling of the solid electrolyte interphase improves understanding of lithium-ion battery performance.
• The study emphasizes challenges posed by the complex structure of the solid electrolyte interphase.
• Utilizing machine learning interatomic potentials can enhance the precision of structural and dynamic property predictions.
• These advancements may lead to more efficient lithium-ion battery technologies and better energy storage solutions.