Fixed-Cell Crystal Relaxation with SevenNet and ASE

1. Prepare an authorized periodic crystal

Linux

2. Install isolated dependencies

Linux

python -m pip install torch
python -m pip install 'sevenn @ git+https://github.com/MDIL-SNU/SevenNet.git@209339d4eb4c1717f906c4cb715629159f00f88c' ase
python -m pip freeze

3. Save the authored calculator example

Linux

"""Authored review example using documented SevenNet/ASE APIs; NOT executed.

Sources: sevenn.calculator.SevenNetCalculator, ASE IO and BFGS documentation.
Fixed-cell geometry optimization only. No MD, reference DFT, or accuracy claim.
"""
import argparse
import json
from pathlib import Path

import numpy as np
from ase.io import read, write
from ase.optimize import BFGS
from sevenn.calculator import SevenNetCalculator

parser = argparse.ArgumentParser()
parser.add_argument("input_cif")
parser.add_argument("output_directory")
args = parser.parse_args()
atoms = read(args.input_cif)
if len(atoms) == 0 or not np.isfinite(atoms.positions).all():
    raise ValueError("Empty structure or nonfinite coordinates")
if not atoms.pbc.all() or atoms.get_volume() <= 0:
    raise ValueError("This example requires a fully periodic crystal with positive cell volume")
# The pinned SevenNet implementation resolves 7net-0 to its July 2024 checkpoint.
# The calculator checks each atomic number against the loaded model type_map.
atoms.calc = SevenNetCalculator(model="7net-0", device="cpu")
energy_initial = float(atoms.get_potential_energy())
forces_initial = atoms.get_forces()
if not np.isfinite(energy_initial) or not np.isfinite(forces_initial).all():
    raise ValueError("Nonfinite initial energy or forces")
out = Path(args.output_directory)
out.mkdir(parents=True, exist_ok=False)
write(out / "initial.extxyz", atoms)
optimizer = BFGS(atoms, logfile=str(out / "optimization.log"), trajectory=str(out / "optimization.traj"))
# These are illustrative stopping settings, not upstream recommendations for all systems.
converged = bool(optimizer.run(fmax=0.05, steps=100))
energy_final = float(atoms.get_potential_energy())
forces_final = atoms.get_forces()
if not np.isfinite(energy_final) or not np.isfinite(forces_final).all():
    raise ValueError("Nonfinite final energy or forces; inspect the partial output")
write(out / "relaxed.cif", atoms)
np.savez(out / "forces.npz", initial=forces_initial, final=forces_final)
record = {"model": "7net-0", "device": "cpu", "atom_count": len(atoms),
          "elements": sorted(set(atoms.get_chemical_symbols())), "fixed_cell": True,
          "energy_initial_eV": energy_initial, "energy_final_eV": energy_final,
          "force_unit": "eV/Angstrom", "fmax_threshold_eV_per_Angstrom": 0.05,
          "max_steps": 100, "converged": converged,
          "final_max_force_eV_per_Angstrom": float(np.linalg.norm(forces_final, axis=1).max())}
(out / "results.json").write_text(json.dumps(record, indent=2) + "\n", encoding="utf-8")
print(json.dumps(record, indent=2))
if not converged:
    raise SystemExit("Optimization reached its step limit; do not describe it as converged")

4. Compute energy, forces and a bounded relaxation

Linux

python sevennet0_relax.py input.cif sevennet_review