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MLIP-Compatible Recipes

Several popular datasets used to train machine-learned interatomic potentials (MLIPs) were built from large collections of DFT calculations run with a specific, fixed set of computational settings. To let users generate additional data that is consistent with one of these datasets (e.g. to extend a dataset or build an internally-consistent benchmark without introducing methodological drift), quacc ships a set of recipes that reproduce those settings.

Note

While these recipes aim to reproduce the settings of each dataset, you should still manually confirm that the resulting calculator settings are consistent with the source dataset for good measure.

Supported Datasets

Dataset Recipe Extra Dependencies
OC20 quacc.recipes.vasp.fairchem.oc20_static_job quacc[fairchem]
OC22 quacc.recipes.vasp.fairchem.oc22_static_job none
OC25 quacc.recipes.vasp.fairchem.oc25_static_job quacc[fairchem]
OMat24 quacc.recipes.vasp.fairchem.omat_static_job quacc[fairchem]
OMC25 quacc.recipes.vasp.fairchem.omc_static_job quacc[atomate2]
OMol25 quacc.recipes.orca.fairchem.omol_static_job quacc[fairchem]
ODAC23 quacc.recipes.vasp.fairchem.odac23_static_job none
ODAC25 quacc.recipes.vasp.fairchem.odac25_static_job none
AQCat25 quacc.recipes.vasp.aqcat.aqcat25_static_job none
MPtrj / WBM / sAlex / MatterSim quacc.recipes.vasp.mp_legacy.mp_relax_set_job none
MatPES quacc.recipes.vasp.matpes.matpes_static_job quacc[atomate2]
MP-ALOE quacc.recipes.vasp.mp_aloe.mp_aloe_static_job none

A Representative Example

from ase.build import bulk
from quacc.recipes.vasp.fairchem import omat_static_job

# Make an Atoms object of a bulk Cu structure
atoms = bulk("Cu")

# Run a static calculation with OMat24-compatible VASP settings
result = omat_static_job(atoms)
print(result)

As with all quacc recipes, you can override any of the default calculator settings by passing additional keyword arguments:

result = omat_static_job(atoms, encut=600)