Screening of potential candidates for solid electrolyte interphase materials for Lithium-ion battery through data-driven approach

Key Points

• Machine learning significantly enhances the design of materials for lithium-ion batteries.
• A data-driven approach allows for effective screening of solid electrolyte interphase materials.
• Predictive algorithms are integral in overcoming design challenges for battery components.
• This methodology could revolutionize material selection processes in battery technology.