The solid-electrolyte interphase (SEI) is a crucial yet poorly understood component of lithium-ion battery performance, significantly impacting SEI stability, battery lifespan, and SEI growth over time. Formed during the first charging cycle, SEI in batteries acts as a protective barrier, but uncontrolled SEI formation can degrade the battery and reduce efficiency.

Despite its importance, studying SEI remains one of the key battery R&D challenges. Its nanoscale thickness, sensitivity to external conditions, and complex formation mechanisms make it difficult to analyze using conventional experimental techniques. As a result, SEI design has largely relied on trial and error, limiting progress in optimizing battery longevity and safety.

To advance beyond this, computational modeling for SEI, particularly through quantum chemistry, molecular dynamics, and beyond, is helping researchers explore its structure and behavior at the atomic level. Additionally, machine learning in batteries is emerging as a powerful tool to predict SEI evolution and accelerate the discovery of next-gen battery materials.

As solid-state batteries, sodium-ion batteries, and potassium-ion batteries gain attention as alternatives to lithium-ion technology, understanding SEI behavior across different chemistries will be critical.

The future of battery R&D hinges on overcoming these challenges—how far are we from a breakthrough? Dive in to discover the latest advancements in SEI research.