easyunfold.effective_mass

easyunfold.effective_mass#

Module for obtaining effective mass

Module Contents#

Classes#

EffectiveMass

Calculate effective mass from unfolding data

Functions#

fit_effective_mass

Fit the effective masses using either a parabolic or nonparabolic fit.

fitted_band

Return fitted effective mass curve

points_with_tol

Return the indices and values of points in an array close to the value with a tolerance

locate_kpoint_segment

Locate the labels and indices of the kpoints defining a segment

Data#

eV_to_hartree

bohr_to_m

angstrom_to_bohr

TMP_DATA

API#

easyunfold.effective_mass.eV_to_hartree#

None

easyunfold.effective_mass.bohr_to_m#

None

easyunfold.effective_mass.angstrom_to_bohr#

None

easyunfold.effective_mass.TMP_DATA#

None

easyunfold.effective_mass.fit_effective_mass(distances, energies, parabolic=True)#

Fit the effective masses using either a parabolic or nonparabolic fit.

Adapted from sumo.

Args: distances (:obj:numpy.ndarray): The x-distances between k-points in reciprocal Angstroms, normalised to the band extrema. energies (:obj:numpy.ndarray): The band eigenvalues normalised to the eigenvalue of the band extrema. parabolic (:obj:bool, optional): Use a parabolic fit of the band edges. If False then nonparabolic fitting will be attempted. Defaults to True.

Returns: float: The effective mass in units of electron rest mass, :math:m_0.

easyunfold.effective_mass.fitted_band(x: numpy.ndarray, eff_mass: float) → numpy.ndarray#

Return fitted effective mass curve

easyunfold.effective_mass.points_with_tol(array, value, tol=0.0001, sign=1)#

Return the indices and values of points in an array close to the value with a tolerance

class easyunfold.effective_mass.EffectiveMass(unfold: easyunfold.unfold.UnfoldKSet, intensity_tol: float = 0.1, extrema_tol: float = 0.001, parabolic: bool = True, npoints: float = 3)#

Calculate effective mass from unfolding data

Initialization

Instantiate the object

Parameters:

  • unfold – The UnfoldKSet object that holds unfolding data.

  • intensity_tol – Intensity threshold for detecting band edges.

  • extrema_tol – Distance tolerance for detecting band edges.

  • parabolic – Perform parabolic fit or not. The default is None.

  • npoints – The number of points used for fitting.

set_nocc(nocc)#
property kpoints#

The primitive cell k-points used for unfolding.

property kpoints_labels#

The primitive cell k-points labels set for unfolding.

get_band_extrema(mode: str = 'cbm', extrema_tol: float = None, ispin=0)#

Obtain the kpoint idx of band extrema, sub indices in the set, and the band indices.

The search takes two steps. First, the kpoints at the band extrema are located by comparing the band energies with that recorded in the supplied cbm and vbm, based on the extrema_tol. Afterwards, the band indices are selected at these kpoints using the tol set.

Parameters:

  • mode – The mode to search for band extrema. Can be either ‘cbm’ (conduction band minimum) or ‘vbm’ (valence band maximum).

  • extrema_tol – The tolerance for determining the proximity of band energies to the cbm/vbm. If not provided, the default tolerance from self.extrema_detect_tol is used.

  • ispin – The spin index. Default is 0.

Returns:

A tuple of extrema locations including a list of kpoint indices, sub-indices within the set, and the band indices at each kpoint that is within the extrema_tol from the cbm/vbm.

Raises:

ValueError – If an unknown mode is provided.

_get_kpoint_distances()#

Distances between the kpoints along the path in the reciprocal space. This does not take account of the breaking of the path NOTE: the reciprocal lattice vectors includes the 2pi factor, e.g. np.linalg.inv(L).T * 2 * np.pi

_get_fitting_data(kidx: int, iband: int, direction=1, ispin=0, npoints=None)#

Get fitting data for a specific combination of kpoint and band index

Parameters:

  • kidx – The index of the kpoint

  • iband – The index of the band

  • direction – The direction of the data collection, defaults to 1

  • ispin – The index of the spin, defaults to 0

  • npoints – Override for the number of data points to collect

Returns:

The normalized kpoint distances, normalized effective energies, and the original kpoint distances and effective energies

get_effective_masses(npoints: Union[float, None] = None, ispin=0, iks=None, iband=None, mode=None)#

Obtain the effective masses based on the unfolded band structure

Parameters:

  • npoints – Number of points to use for fitting. If None, a default value is used.

  • ispin – The index of the spin channel. Default is 0.

  • iks – K-point indices used for manual override.

  • iband – Band indices used for manual override.

  • mode – Calculation mode. If None, effective masses at both conduction band minimum (cbm) and valence band maximum (vbm) will be calculated.

Returns:

A dictionary containing the effective masses for electrons and holes.

_get_effective_masses(mode: str = 'cbm', ispin: int = 0, npoints: Union[None, int] = None, iks=None, iband=None)#

Work out the effective masses based on the unfolded band structure for CBM or VBM

Parameters:

  • mode – The mode to calculate effective masses, either ‘cbm’ for conduction band minimum or ‘vbm’ for valence band maximum. Default is ‘cbm’.

  • ispin – The spin index. Default is 0.

  • npoints – The number of points to use for fitting. If None, the default number of points will be used.

  • iks – The indices of the k-points to calculate effective masses. If None, the indices will be obtained from get_band_extrema method.

  • iband – The indices of the bands to calculate effective masses. If None, the indices will be obtained from get_band_extrema method.

Returns:

A list of dictionaries containing the calculated effective masses and related information.

easyunfold.effective_mass.locate_kpoint_segment(idxk: int, label_idx: list, label_names: list, direction: int)#

Locate the labels and indices of the kpoints defining a segment

Parameters:

  • idxk – The index of the kpoint

  • label_idx – A list of indices corresponding to the labels

  • label_names – A list of label names

  • direction – The direction of the segment (1 for forward, -1 for backward)

Returns:

A tuple containing the index of the label, the label name of the starting point, and the label name of the ending point