Exploring solvation structure and transport behavior for rational design of advanced electrolytes for next generation of lithium batteries.

This article reviews recent advancements in electrolyte design strategies for lithium-ion and lithium metal batteries, emphasizing the critical role of understanding electrolyte solvation structures to improve battery performance across applications such as high capacity, high voltage, fast charging, wide temperature range, and safety. It discusses experimental techniques (e.g., NMR, Raman, SAXS/SANS, XAS) and computational methods (e.g., molecular dynamics, density functional theory, machine learning) used to characterize and model electrolyte behavior at molecular and atomic scales. The review highlights the integration of artificial intelligence and high-throughput autonomous experimentation to accelerate electrolyte discovery and optimization, while underscoring the need for combined experimental and computational approaches to elucidate the complex structure–property–performance relationships. Finally, it advocates for multi-component electrolyte formulations and advanced in situ/operando characterization to guide the design of safer, more efficient electrolytes tailored to diverse battery applications.