Active Learning Guided Optimization of Multi‐Component Electrolytes for Fast‐Charging Lithium‐Ion Batteries

Abstract With the rapid development of electric vehicles and portable electronics, there is an urgent demand for lithium‐ion batteries (LIBs) with excellent fast‐charging performance, which heavily depends on electrolyte solvation environment and its derived anode/cathode interphases. However, the complex electrochemical nature of LIBs (dynamic component‐interphase interactions, sensitive performance‐response to component adjustments) makes traditional trial‐and‐error optimization of multi‐component electrolytes inefficient. Herein, an active learning strategy has been successfully employed to optimize multi‐component electrolyte formulas by coordinating key component proportions, targeting fast‐charging capability improvement for LIBs with commercial graphite anodes and NCM811 cathodes. As a result, a well‐optimized formula is screened out after only two iterations. The balanced solvation environment rich in contact ion pairs (CIPs) and the fine‐tuned additives synergistically optimize Li + interfacial transport behaviors and effectively improve the fast‐charging performance. The pouch battery could retain over 90% capacity at 4C charging rate, while the coin battery achieves a long cycle life of 600 cycles. This work offers a reference for adjusting multi‐component electrolyte formulas to enhance the fast‐charging performance of LIBs.