atomistics.workflows.quasiharmonic.get_thermal_properties_for_quasi_harmonic_approximation#
- atomistics.workflows.quasiharmonic.get_thermal_properties_for_quasi_harmonic_approximation(eng_internal_dict: dict, task_dict: dict, qh_dict: dict, fit_type: str, fit_order: int, t_min: float = 1.0, t_max: float = 1500.0, t_step: float = 50.0, temperatures: ndarray | None = None, cutoff_frequency: float | None = None, pretend_real: bool = False, band_indices: ndarray | None = None, is_projection: bool = False, quantum_mechanical: bool = True, output_keys: tuple[str, ...] = ('temperatures', 'volumes', 'free_energy', 'entropy', 'heat_capacity')) dict[source]#
Returns thermal properties at constant volume in the given temperature range. Can only be called after job successfully ran.
- Parameters:
eng_internal_dict (dict) – Dictionary of internal energies for different strains.
task_dict (dict) – task dictionary with the structures
qh_dict (dict) – quasi_harmonic dictionary containing the phonon_dict and the repeat_vector
fit_type (str) – Type of fitting for energy-volume curve.
fit_order (int) – Order of fitting for energy-volume curve.
t_min (float, optional) – Minimum sample temperature. Defaults to 1.0.
t_max (float, optional) – Maximum sample temperature. Defaults to 1500.0.
t_step (float, optional) – Temperature sample interval. Defaults to 50.0.
temperatures (np.ndarray, optional) – Custom array of temperature samples. If given, t_min, t_max, t_step are ignored.
cutoff_frequency (float, optional) – Cutoff frequency. Defaults to None.
pretend_real (bool, optional) – Whether to pretend real. Defaults to False.
band_indices (np.ndarray, optional) – Array of band indices. Defaults to None.
is_projection (bool, optional) – Whether it is a projection. Defaults to False.
quantum_mechanical (bool, optional) – Whether to use quantum mechanical approach. Defaults to True.
output_keys (tuple[str], optional) – Output keys. Defaults to OutputThermodynamic.keys().
- Returns:
Thermal properties as returned by Phonopy.
- Return type:
dict