A data-driven interpretation of the stability of organic molecular crystals

Due to the subtle balance of molecular interactions, predicting the stability of molecular crystals is a non-trivial scientific problem. Physically-motivated machine learning models can not only “rediscover” the maxims of crystal engineering, but also guide crystal design.