pymatgen.analysis.defects.corrections module

class BandEdgeShiftingCorrection

Bases: pymatgen.analysis.defects.core.DefectCorrection

A class for BandEdgeShiftingCorrection class. Largely adapted from PyCDT code

Requires some parameters in the DefectEntry to properly function:

hybrid_cbm

CBM of HYBRID bulk calculation

hybrid_vbm

VBM of HYBRID bulk calculation

cbm

CBM of bulk calculation (or band structure calculation of bulk); calculated on same level of theory as the eigenvalues list (ex. GGA defects -> need GGA cbm

vbm

VBM of bulk calculation (or band structure calculation of bulk); calculated on same level of theory as the eigenvalues list (ex. GGA defects -> need GGA vbm

num_hole_vbm

number of free holes that were found in valence band for the defect calculation calculated in the metadata of the BandFilling Correction

num_elec_cbm

number of free electrons that were found in the conduction band for the defect calculation calculated in the metadata of the BandFilling Correction

get_correction(entry)

Gets the BandEdge correction for a defect entry

class BandFillingCorrection(resolution=0.01)

Bases: pymatgen.analysis.defects.core.DefectCorrection

A class for BandFillingCorrection class. Largely adapted from PyCDT code

Requires some parameters in the DefectEntry to properly function:

eigenvalues

dictionary of defect eigenvalues, as stored in a Vasprun

kpoint_weights

kpoint weights corresponding to the dictionary of eigenvalues

potalign

potential alignment for the defect calculation Only applies to non-zero charge, When using potential alignment Correction (freysoldt or kumagai), need to divide by -q

cbm

CBM of bulk calculation (or band structure calculation of bulk); calculated on same level of theory as the eigenvalues list (ex. GGA defects -> need GGA cbm

vbm

VBM of bulk calculation (or band structure calculation of bulk); calculated on same level of theory as the eigenvalues list (ex. GGA defects -> need GGA vbm

Initializes the Bandfilling correction

Parameters:resolution (float) – energy resolution to maintain for gap states

get_correction(entry)

Gets the BandFilling correction for a defect entry

perform_bandfill_corr(eigenvalues, kpoint_weights, potalign, vbm, cbm)

This calculates the band filling correction based on excess of electrons/holes in CB/VB…

Note that the total free holes and electrons may also be used for a “shallow donor/acceptor”

correction with specified band shifts: +num_elec_cbm * Delta E_CBM (or -num_hole_vbm * Delta E_VBM) [this is done in the LevelShiftingCorrection class]

class FreysoldtCorrection(dielectric_const, q_model=None, energy_cutoff=520, madetol=0.0001, axis=None)

Bases: pymatgen.analysis.defects.core.DefectCorrection

A class for FreysoldtCorrection class. Largely adapated from PyCDT code

Initializes the Freysoldt Correction :param dielectric_const: Dielectric constant for the structure :type dielectric_const: float or 3x3 matrix :param q_mode: instantiated QModel object or None. Uses default parameters to instantiate QModel if None supplied :type q_mode: QModel :param energy_cutoff: Maximum energy in eV in recipripcol space to perform integration for potential correction :type energy_cutoff: int :param madeltol: Convergence criteria for the Madelung energy for potential correction :type madeltol: float :param axis: Axis to calculate correction. Averages over all three if not supplied. :type axis: int

get_correction(entry)

Gets the Freysoldt correction for a defect entry :param entry: defect entry to compute Freysoldt correction on.

Requires following parameters in the DefectEntry to exist:

axis_grid (3 x NGX where NGX is the length of the NGX grid in the x,y and z axis directions. Same length as planar average lists):

A list of 3 numpy arrays which contain the cartesian axis values (in angstroms) that correspond to each planar avg potential supplied.

bulk_planar_averages (3 x NGX where NGX is the length of the NGX grid in the x,y and z axis directions.):

A list of 3 numpy arrays which contain the planar averaged electrostatic potential for the bulk supercell.

defect_planar_averages (3 x NGX where NGX is the length of the NGX grid in the x,y and z axis directions.):

A list of 3 numpy arrays which contain the planar averaged electrostatic potential for the defective supercell.

scaling_matrix (3 x 1 matrix): scaling matrix required to convert the

entry.defect.bulk_structure object into the lattice which is used by the bulk_planar_average and defect_planar_average

perform_es_corr(lattice, q, step=0.0001)

Peform Electrostatic Freysoldt Correction

perform_pot_corr(axis_grid, pureavg, defavg, lattice, q, defect_position, axis, madetol=0.0001, widthsample=1.0)

For performing planar averaging potential alignment

title is for name of plot, if you dont want a plot then leave it as None widthsample is the width (in Angstroms) of the region in between defects where the potential alignment correction is averaged

plot(axis, title=None, saved=False)

Plots the planar average electrostatic potential against the Long range and short range models from Freysoldt