Artificial Intelligence Advances the Uncovering of Solid–Liquid Interfaces in Batteries

A more profound understanding of battery interfaces, characterized by multiple components and dynamic interactions, can provide a theoretical foundation for the development of next-generation energy storage systems. The rapid advancement of artificial intelligence (AI) technology is enhancing scientific paradigms, offering significant benefits for the study of complex battery interfaces. Here, we examine how AI can facilitate a deeper understanding of these intricate interfaces in batteries, promote more standardized characterization analyses, and assist in designing interface materials. The introduction of AI models may facilitate the discovery of additional mechanisms and materials. Moreover, we discuss the trade-off between interpretability and accuracy in AI models, as well as the risk of narrow cognitive perspectives among researchers. We hope this perspective will inspire and advance the technological integration of AI in battery interface research.