Improving machine-learning models in materials science through large datasets

1. Image of the Alexandria database  state corresponding to the paper "Improving machine-learning models in materials science through large datasets".

Static pbe calculations for 1D, 2D, 3D compounds can be found in 1D_pbe.tar.gz, 2D_pbe.tar.gz, 3D_pbe.tar.gz in batches of 100k materials. The latter also contains a separate convex hull pickle with all compounds on the pbe convex hull (convex_hull_pbe_2023.12.29.json.bz2) and a list of prototypes in the database (prototypes.json.bz2). The systematic 3D calculations performed for the article Improving machine-learning models in materials science through large datasets (in the paper referred to as round 2 and 3) can be found by the location keyword in the data dictionary of each ComputedStructureEntry containing  "cgat_comp/quaternaries" (round 2) and "cgat_comp2/"  (round 3).  Round 1 (10.1002/adma.202210788) can be found under "cgat_comp/ternaries", ""cgat_comp/binaries".

Static pbesol calculations for 3D compounds can be found in 3D_ps.tar (still zip compressed) in batches of 100k materials. The folder also contains a separate convex hull pickle with all compounds on the pbesol convex hull (convex_hull_ps_2023.12.29.json.bz2). 

Static scan calculations for 3D compounds can be found in 3D_scan.tar (still zip compressed) in batches of 100k materials. The folder also contains a separate convex hull pickle with all compounds on the scan convex hull (convex_hull_scan_2023.12.29.json.bz2). 

Geometry relaxation curves for 1D and 2D and 3D compounds calculated with PBE can be found in geo_opt_1D.tar.gz, geo_opt_2D.tar.gz. and geo_opt_3D.tar. Each file in each folder contains a batch of up to 10k relaxation trajectories.

PBESOL relaxation trajectories for 3D compounds can be found in geo_opt_ps.tar

2. Crystal graph attention networks to predict the volume (volume_round_3.tar.gz) and distance to the convex hull (e_above_hull_round_3.tar.gz) trained for the paper "Improving machine-learning models in materials science through large datasets".

Can be used with the code at https://github.com/hyllios/CGAT/tree/main/CGAT.Note will predict the distance to the convex hull not normalized per atom when using the code on the github.

3. Alignn models as well as m3gnet and mace models corresponding  to the publication can be found in alexandria_v2.tar.gz

4. scripts.tar.gz Some scripts used for generating CGAT input data/ performing parallel predictions and for relaxations with m3gnet/mace force fields