Crystallization processes are underpinned by an interplay between thermodynamics and kinetics, leading to complex energy landscapes spanned by polymorphs and metastable intermediates that are challenging to identify and characterize. In this Review, the authors highlight how recent progress in computational methods, and their augmentation with machine learning, have advanced our ability to predict crystal structures and simulate crystal nucleation.
- Caroline Desgranges
- Jerome Delhommelle
