OXtal-CSP/OXtal_train_data

OXtal is an all-atom diffusion model for molecular crystal structure prediction (CSP). OXtal achieves orders-of-magnitude improvements over prior ab initio machine learning CSP methods, while remaining orders of magnitude cheaper than traditional quantum-chemical approaches. Specifically, OXtal recovers experimental crystal structures for both rigid and flexible molecules as well as co-crystals with conformer RMSD₁ < 0.5 Å and attains over 80% packing similarity rate, demonstrating its ability to model both thermodynamic and kinetic regularities of molecular crystallization.

This dataset contains the list of CCDC ids used to train OXtal and defer to the official CCDC CSD database for actual crystal structure retreival.