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ALIGNN

Property Predictors

atomgptlab/alignn

Property Predictors¶

Single-property ALIGNN checkpoints are invoked through pretrained.py.

CLI help¶

pretrained.py -h

Example — formation energy (JARVIS-DFT)¶

pretrained.py \
  --model_name jv_formation_energy_peratom_alignn \
  --file_format poscar \
  --file_path alignn/examples/sample_data/POSCAR-JVASP-10.vasp

Available models¶

A non-exhaustive list — names match the --model_name flag:

Target	Model name
Formation energy per atom (JARVIS-DFT)	`jv_formation_energy_peratom_alignn`
Bandgap — OPT88vdW	`jv_optb88vdw_bandgap_alignn`
Bandgap — MBJ	`jv_mbj_bandgap_alignn`
Total energy per atom (JARVIS-DFT)	`jv_optb88vdw_total_energy_alignn`
Ehull	`jv_ehull_alignn`
Bulk modulus (K_v)	`jv_bulk_modulus_kv_alignn`
Shear modulus (G_v)	`jv_shear_modulus_gv_alignn`
Dielectric (εx, OPT)	`jv_epsx_alignn`
Max. piezo dielectric (DFPT)	`jv_dfpt_piezo_max_dielectric_alignn`
Spillage	`jv_spillage_alignn`
SLME	`jv_slme_alignn`
Magnetic moment	`jv_magmom_oszicar_alignn`
Raman	`jv_raman_alignn`
Superconductor T_c	`jv_supercon_tc_alignn`
Interface CBM / VBM	`intermat_cbm`, `intermat_vbm`
hMOF CO₂ adsorption	`hmof_co2_absp_alignn`

See all_models_alignn.json for the full machine-readable list.

File formats¶

Pass --file_format matching your structure file:

poscar — VASP POSCAR
cif
xyz
pdb

Using from Python¶

from ase.build import bulk
from alignn.ff.unified_calculator import (
    AlignnUnifiedCalculator, AlignnUnifiedConfig)

# Any pretrained ALIGNN 2.0 predictor(s): scalar (formation_energy_peratom,
# optb88vdw_bandgap, ...), spectra (edos, pdos, ir, raman) or tensor
# (dielectric_tensor, elastic_tensor, piezo_tensor). prop_graph is "radius"
# (default, force-field-compatible) or "knn".
cfg = AlignnUnifiedConfig(
    energy=False, forces=False, stress=False,   # property-only (no force field)
    properties=["formation_energy_peratom", "optb88vdw_bandgap"],
)
calc = AlignnUnifiedCalculator(cfg)   # models downloaded+cached, loaded once

atoms = bulk("Si", "diamond", a=5.43)
calc.calculate(atoms)                 # single forward pass
print(calc.predictions())
# {'formation_energy_peratom': 0.0026, 'optb88vdw_bandgap': 0.7725}

The pure-PyTorch ALIGNN 2.0 models are pulled from pretrained2.py (list_alignn2_models() shows the full registry). Set energy=True to also get force-field energy/forces/stress from the same calculator.

See also¶