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ts

Transition state recipes for the NewtonNet code.

IRCSchema

Bases: OptSchema

freq_job instance-attribute 

freq_job: FreqSchema | None

QuasiIRCSchema

Bases: OptSchema

freq_job instance-attribute 

freq_job: FreqSchema | None

irc_job instance-attribute 

irc_job: IRCSchema

TSSchema

Bases: OptSchema

freq_job instance-attribute 

freq_job: FreqSchema | None

irc_job 

irc_job(
    atoms: Atoms,
    direction: Literal["forward", "reverse"] = "forward",
    run_freq: bool = True,
    freq_job_kwargs: dict[str, Any] | None = None,
    opt_params: OptParams | None = None,
    **calc_kwargs
) -> IRCSchema

Perform an intrinsic reaction coordinate (IRC) job using the given atoms object.

Parameters:

  • atoms (Atoms) –

    The atoms object representing the system.

  • direction (Literal['forward', 'reverse'], default: 'forward' ) –

    The direction of the IRC calculation ("forward" or "reverse").

  • run_freq (bool, default: True ) –

    Whether to run the frequency analysis.

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

    Keyword arguments to use for the quacc.recipes.newtonnet.ts.freq_job

  • opt_params (OptParams | None, default: None ) –

    Dictionary of custom kwargs for the optimization process. For a list of available keys, refer to quacc.runners.ase.run_opt.

  • **calc_kwargs –

    Custom kwargs for the NewtonNet calculator. Set a value to quacc.Remove to remove a pre-existing key entirely. For a list of available keys, refer to the newtonnet.utils.ase_interface.MLAseCalculator calculator.

Returns:

  • IRCSchema –

    A dictionary containing the IRC summary and thermodynamic summary. See the type-hint for the data structure.

Source code in quacc/recipes/newtonnet/ts.py 
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@job
@requires(NewtonNet, "NewtonNet must be installed. Refer to the quacc documentation.")
@requires(Sella, "Sella must be installed. Refer to the quacc documentation.")
def irc_job(
    atoms: Atoms,
    direction: Literal["forward", "reverse"] = "forward",
    run_freq: bool = True,
    freq_job_kwargs: dict[str, Any] | None = None,
    opt_params: OptParams | None = None,
    **calc_kwargs,
) -> IRCSchema:
    """
    Perform an intrinsic reaction coordinate (IRC) job using the given atoms object.

    Parameters
    ----------
    atoms
        The atoms object representing the system.
    direction
        The direction of the IRC calculation ("forward" or "reverse").
    run_freq
        Whether to run the frequency analysis.
    freq_job_kwargs
        Keyword arguments to use for the [quacc.recipes.newtonnet.ts.freq_job][]
    opt_params
        Dictionary of custom kwargs for the optimization process. For a list
        of available keys, refer to [quacc.runners.ase.run_opt][].
    **calc_kwargs
        Custom kwargs for the NewtonNet calculator. Set a value to
        `quacc.Remove` to remove a pre-existing key entirely. For a list of available
        keys, refer to the `newtonnet.utils.ase_interface.MLAseCalculator` calculator.

    Returns
    -------
    IRCSchema
        A dictionary containing the IRC summary and thermodynamic summary.
        See the type-hint for the data structure.
    """
    freq_job_kwargs = freq_job_kwargs or {}

    calc_defaults = {
        "model_path": SETTINGS.NEWTONNET_MODEL_PATH,
        "settings_path": SETTINGS.NEWTONNET_CONFIG_PATH,
    }
    opt_defaults = {
        "optimizer": IRC,
        "optimizer_kwargs": {"dx": 0.1, "eta": 1e-4, "gamma": 0.4, "keep_going": True},
        "run_kwargs": {"direction": direction},
    }

    calc_flags = recursive_dict_merge(calc_defaults, calc_kwargs)
    opt_flags = recursive_dict_merge(opt_defaults, opt_params)

    # Define calculator
    atoms.calc = NewtonNet(**calc_flags)

    # Run IRC
    with change_settings({"CHECK_CONVERGENCE": False}):
        dyn = run_opt(atoms, **opt_flags)
        opt_irc_summary = _add_stdev_and_hess(
            summarize_opt_run(
                dyn, additional_fields={"name": f"NewtonNet IRC: {direction}"}
            )
        )

    # Run frequency job
    freq_summary = (
        strip_decorator(freq_job)(opt_irc_summary["atoms"], **freq_job_kwargs)
        if run_freq
        else None
    )
    opt_irc_summary["freq_job"] = freq_summary

    return opt_irc_summary

quasi_irc_job 

quasi_irc_job(
    atoms: Atoms,
    direction: Literal["forward", "reverse"] = "forward",
    run_freq: bool = True,
    irc_job_kwargs: dict[str, Any] | None = None,
    relax_job_kwargs: dict[str, Any] | None = None,
    freq_job_kwargs: dict[str, Any] | None = None,
) -> QuasiIRCSchema

Perform a quasi-IRC job using the given atoms object. The initial IRC job by default is run with max_steps: 5.

Parameters:

Returns:

  • QuasiIRCSchema –

    A dictionary containing the IRC summary, optimization summary, and thermodynamic summary. See the type-hint for the data structure.

Source code in quacc/recipes/newtonnet/ts.py 
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@job
@requires(NewtonNet, "NewtonNet must be installed. Refer to the quacc documentation.")
@requires(Sella, "Sella must be installed. Refer to the quacc documentation.")
def quasi_irc_job(
    atoms: Atoms,
    direction: Literal["forward", "reverse"] = "forward",
    run_freq: bool = True,
    irc_job_kwargs: dict[str, Any] | None = None,
    relax_job_kwargs: dict[str, Any] | None = None,
    freq_job_kwargs: dict[str, Any] | None = None,
) -> QuasiIRCSchema:
    """
    Perform a quasi-IRC job using the given atoms object. The initial IRC job by default
    is run with `max_steps: 5`.

    Parameters
    ----------
    atoms
        The atoms object representing the system
    direction
        The direction of the IRC calculation
    run_freq
        Whether to run the frequency analysis
    irc_job_kwargs
        Keyword arguments to use for the [quacc.recipes.newtonnet.ts.irc_job][]
    relax_job_kwargs
        Keyword arguments to use for the [quacc.recipes.newtonnet.core.relax_job][]
    freq_job_kwargs
        Keyword arguments to use for the [quacc.recipes.newtonnet.ts.freq_job][]

    Returns
    -------
    QuasiIRCSchema
        A dictionary containing the IRC summary, optimization summary, and
        thermodynamic summary.
        See the type-hint for the data structure.
    """
    relax_job_kwargs = relax_job_kwargs or {}
    freq_job_kwargs = freq_job_kwargs or {}

    irc_job_defaults = {"max_steps": 5}
    irc_job_kwargs = recursive_dict_merge(irc_job_defaults, irc_job_kwargs)

    # Run IRC
    irc_summary = strip_decorator(irc_job)(
        atoms, direction=direction, run_freq=False, **irc_job_kwargs
    )

    # Run opt
    relax_summary = strip_decorator(relax_job)(irc_summary["atoms"], **relax_job_kwargs)

    # Run frequency
    freq_summary = (
        strip_decorator(freq_job)(relax_summary["atoms"], **freq_job_kwargs)
        if run_freq
        else None
    )
    relax_summary["freq_job"] = freq_summary
    relax_summary["irc_job"] = irc_summary

    return relax_summary

ts_job 

ts_job(
    atoms: Atoms,
    use_custom_hessian: bool = False,
    run_freq: bool = True,
    freq_job_kwargs: dict[str, Any] | None = None,
    opt_params: OptParams | None = None,
    **calc_kwargs
) -> TSSchema

Perform a transition state (TS) job using the given atoms object.

Parameters:

  • atoms (Atoms) –

    The atoms object representing the system.

  • use_custom_hessian (bool, default: False ) –

    Whether to use a custom Hessian matrix.

  • run_freq (bool, default: True ) –

    Whether to run the frequency job.

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

    Keyword arguments to use for the quacc.recipes.newtonnet.ts.freq_job

  • opt_params (OptParams | None, default: None ) –

    Dictionary of custom kwargs for the optimization process. For a list of available keys, refer to quacc.runners.ase.run_opt.

  • **calc_kwargs –

    Dictionary of custom kwargs for the NewtonNet calculator. Set a value to quacc.Remove to remove a pre-existing key entirely. For a list of available keys, refer to the newtonnet.utils.ase_interface.MLAseCalculator calculator.

Returns:

  • TSSchema –

    Dictionary of results. See the type-hint for the data structure.

Source code in quacc/recipes/newtonnet/ts.py 
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@job
@requires(NewtonNet, "NewtonNet must be installed. Refer to the quacc documentation.")
@requires(Sella, "Sella must be installed. Refer to the quacc documentation.")
def ts_job(
    atoms: Atoms,
    use_custom_hessian: bool = False,
    run_freq: bool = True,
    freq_job_kwargs: dict[str, Any] | None = None,
    opt_params: OptParams | None = None,
    **calc_kwargs,
) -> TSSchema:
    """
    Perform a transition state (TS) job using the given atoms object.

    Parameters
    ----------
    atoms
        The atoms object representing the system.
    use_custom_hessian
        Whether to use a custom Hessian matrix.
    run_freq
        Whether to run the frequency job.
    freq_job_kwargs
        Keyword arguments to use for the [quacc.recipes.newtonnet.ts.freq_job][]
    opt_params
        Dictionary of custom kwargs for the optimization process. For a list
        of available keys, refer to [quacc.runners.ase.run_opt][].
    **calc_kwargs
        Dictionary of custom kwargs for the NewtonNet calculator. Set a value to
        `quacc.Remove` to remove a pre-existing key entirely. For a list of available
        keys, refer to the `newtonnet.utils.ase_interface.MLAseCalculator` calculator.

    Returns
    -------
    TSSchema
        Dictionary of results. See the type-hint for the data structure.
    """
    freq_job_kwargs = freq_job_kwargs or {}

    calc_defaults = {
        "model_path": SETTINGS.NEWTONNET_MODEL_PATH,
        "settings_path": SETTINGS.NEWTONNET_CONFIG_PATH,
        "hess_method": "autograd",
    }
    opt_defaults = {
        "optimizer": Sella,
        "optimizer_kwargs": (
            {"diag_every_n": 0, "order": 1} if use_custom_hessian else {"order": 1}
        ),
    }

    calc_flags = recursive_dict_merge(calc_defaults, calc_kwargs)
    opt_flags = recursive_dict_merge(opt_defaults, opt_params)

    atoms.calc = NewtonNet(**calc_flags)

    if use_custom_hessian:
        opt_flags["optimizer_kwargs"]["hessian_function"] = _get_hessian

    ml_calculator = NewtonNet(**calc_flags)
    atoms.calc = ml_calculator

    # Run the TS optimization
    dyn = run_opt(atoms, **opt_flags)
    opt_ts_summary = _add_stdev_and_hess(
        summarize_opt_run(dyn, additional_fields={"name": "NewtonNet TS"})
    )

    # Run a frequency calculation
    freq_summary = (
        strip_decorator(freq_job)(opt_ts_summary["atoms"], **freq_job_kwargs)
        if run_freq
        else None
    )
    opt_ts_summary["freq_job"] = freq_summary

    return opt_ts_summary