ForceFieldNebFromImagesMaker

class atomate2.forcefields.neb.ForceFieldNebFromImagesMaker(name='Forcefield NEB from images', calculator_kwargs=<factory>, ionic_step_data=('energy', 'forces', 'magmoms', 'stress', 'mol_or_struct'), store_trajectory=StoreTrajectoryOption.NO, tags=None, neb_kwargs=<factory>, fix_symmetry=False, symprec=0.01, steps=500, relax_kwargs=<factory>, optimizer_kwargs=<factory>, traj_file=None, traj_file_fmt='ase', traj_interval=1, neb_doc_kwargs=<factory>, force_field_name=MLFF.Forcefield, calculator_meta=None, task_document_kwargs=<factory>)

Bases: ForceFieldMixin, AseNebFromImagesMaker

Run NEB with an ML forcefield using ASE.

Parameters:

• name (str)

• calculator_kwargs (dict[str, Any])

• ionic_step_data (tuple[str, ...] | None)

• store_trajectory (StoreTrajectoryOption)

• tags (list[str] | None)

• neb_kwargs (dict)

• fix_symmetry (bool)

• symprec (float | None)

• steps (int)

• relax_kwargs (dict)

• optimizer_kwargs (dict)

• traj_file (str | None)

• traj_file_fmt (Literal['pmg', 'ase', 'xdatcar'])

• traj_interval (int)

• neb_doc_kwargs (dict)

• force_field_name (str | MLFF | dict)

• calculator_meta (str | MLFF | dict | None)

• task_document_kwargs (dict[str, Any])

make(images, prev_dir=None)

Perform NEB with MLFFs on a set of images.

Parameters:

• images (list of pymatgen .Structure) – Structures to perform NEB on.

• prev_dir (str or Path or None) – A previous calculation directory to copy output files from. Unused, just added to match the method signature of other makers.

Return type:

NebResult