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Elastic

Elastic constants recipes for MLIPs.

elastic_tensor_flow 

elastic_tensor_flow(
    atoms: Atoms,
    pre_relax: bool = True,
    run_static: bool = False,
    deform_kwargs: dict[str, Any] | None = None,
    job_params: dict[str, dict[str, Any]] | None = None,
    job_decorators: (
        dict[str, Callable | None] | None
    ) = None,
) -> ElasticSchema

Workflow consisting of:

  1. Bulk structure relaxation (if pre_relax is True)

  2. Bulk structure static calculation (if run_static is True)

  3. Deformed structures generation

  4. Deformed structures relaxations

  5. Deformed structures statics (if run_static is True)

  6. Elastic tensor calculation

Parameters:

  • atoms (Atoms) –

    Atoms object

  • pre_relax (bool, default: True ) –

    Whether to run a relaxation on the structure before deformation (true)

  • run_static (bool, default: False ) –

    Whether to run static calculations after any relaxations on the undeformed or deformed structures

  • deform_kwargs (dict[str, Any] | None, default: None ) –

    Additional keyword arguments to pass to quacc.atoms.deformation.make_deformations_from_bulk

  • job_params (dict[str, dict[str, Any]] | None, default: None ) –

    Custom parameters to pass to each Job in the Flow. This is a dictionary where the keys are the names of the jobs and the values are dictionaries of parameters.

  • job_decorators (dict[str, Callable | None] | None, default: None ) –

    Custom decorators to apply to each Job in the Flow. This is a dictionary where the keys are the names of the jobs and the values are decorators.

Returns:

  • ElasticSchema –

    See the return type-hint for the data structure.

Source code in quacc/recipes/mlip/elastic.py 
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@flow
def elastic_tensor_flow(
    atoms: Atoms,
    pre_relax: bool = True,
    run_static: bool = False,
    deform_kwargs: dict[str, Any] | None = None,
    job_params: dict[str, dict[str, Any]] | None = None,
    job_decorators: dict[str, Callable | None] | None = None,
) -> ElasticSchema:
    """
    Workflow consisting of:

    1. Bulk structure relaxation (if pre_relax is True)
        - name: "relax_job"
        - job: [quacc.recipes.emt.core.relax_job][]

    2. Bulk structure static calculation (if run_static is True)
        - name: "static_job"
        - job: [quacc.recipes.emt.core.static_job][]

    3. Deformed structures generation

    4. Deformed structures relaxations
        - name: "relax_job"
        - job: [quacc.recipes.emt.core.relax_job][]

    5. Deformed structures statics (if run_static is True)
        - name: "static_job"
        - job: [quacc.recipes.emt.core.static_job][]

    6. Elastic tensor calculation

    Parameters
    ----------
    atoms
        Atoms object
    pre_relax
        Whether to run a relaxation on the structure before deformation (true)
    run_static
        Whether to run static calculations after any relaxations on the undeformed or deformed structures
    deform_kwargs
        Additional keyword arguments to pass to [quacc.atoms.deformation.make_deformations_from_bulk][]
    job_params
        Custom parameters to pass to each Job in the Flow. This is a dictionary where
        the keys are the names of the jobs and the values are dictionaries of parameters.
    job_decorators
        Custom decorators to apply to each Job in the Flow. This is a dictionary where
        the keys are the names of the jobs and the values are decorators.

    Returns
    -------
    ElasticSchema
        See the return type-hint for the data structure.
    """
    relax_job_, static_job_ = customize_funcs(
        ["relax_job", "static_job"],
        [relax_job, static_job],
        param_swaps=job_params,
        decorators=job_decorators,
    )  # type: ignore

    return elastic_tensor_flow_(
        atoms=atoms,
        relax_job=relax_job_,
        static_job=static_job_,
        pre_relax=pre_relax,
        run_static=run_static,
        deform_kwargs=deform_kwargs,
    )