Machine learning force fields can accelerate discovery of battery materials by accurately predicting how ions move and store in complex structures, reducing reliance on expensive experiments.
Researchers used machine learning force fields and quantum simulations to design and test a new anode material for sodium-ion batteries made from graphene with amino groups attached. The material shows promising properties: high storage capacity (~400 mAh/g), very fast ion movement, and minimal swelling—making it a strong candidate for practical battery applications.