AI reactivity predictor considers both molecular and electronic properties
Machine-learning model tested on electrochemical systems
Scientists in South Korea have devised a machine-learning model that can predict the chemical reactivity of organic materials. The model can screen for stability and compatibility across a wide stretch of chemical space, and the team demonstrated its efficacy by using it to select stable electrolytes for a lithium–oxygen battery.