mattersim

import torch from ase import Atoms from ase.optimize import LBFGS from mattersim.models import MatterSimModel from mattersim.calc import MatterSimCalculator # 1. Load a pre-trained MatterSim model # Using torch.hub.load handles model downloading automatically model = torch.hub.load("microsoft/mattersim", "mattersim_model_v1_0") # 2. Initialize MatterSimCalculator # Use 'cuda' if a GPU is available, otherwise 'cpu' calculator = MatterSimCalculator(model=model, device="cpu") # 3. Create an ASE Atoms object and set the calculator atoms = Atoms("H2O", positions=[[0, 0, 0], [0, 1, 0], [0.5, -0.5, 0]], cell=[10,10,10], pbc=False) atoms.set_calculator(calculator) # 4. Perform an energy minimization using an ASE optimizer print(f"Initial energy: {atoms.get_potential_energy():.4f} eV") optimizer = LBFGS(atoms) optimizer.run(fmax=0.01) # Relax until forces are below 0.01 eV/Å print(f"Final energy: {atoms.get_potential_energy():.4f} eV") print(f"Relaxed positions:\n{atoms.get_positions()}")