Domain oriented universal machine learning potential enables fast exploration of chemical space of battery electrolytes

Efficient modeling of battery electrolytes is limited by the accuracy-cost trade-off. Here, authors develop a universal machine learning potential to accurately calculate transport and solvation properties across a broad chemical space.