pymatgen.analysis.defects.thermodynamics module

class DefectPhaseDiagram(entries, vbm, band_gap, filter_compatible=True)[source]

Bases: monty.json.MSONable

This is similar to a PhaseDiagram object in pymatgen, but has ability to do quick analysis of defect formation energies when fed DefectEntry objects

uses many of the capabilities from PyCDT’s DefectsAnalyzer class…

This class is able to get:
  1. stability of charge states for a given defect,
  2. list of all formation ens

c) transition levels in the gap d)

Parameters:dentries ([DefectEntry]) – A list of DefectEntry objects
all_stable_entries

List all stable entries (defect+charge) in the DefectPhaseDiagram

all_unstable_entries

List all unstable entries (defect+charge) in the DefectPhaseDiagram

defect_concentrations(chemical_potentials, temperature=300, fermi_level=0.0)[source]

Give list of all concentrations at specified efermi in the DefectPhaseDiagram :param chemical_potentials = {Element: number} is dictionary of chemical potentials to provide formation energies for :param temperature = temperature to produce concentrations from: :param fermi_level: (float) is fermi level relative to valence band maximum

Default efermi = 0 = VBM energy
Returns:list of dictionaries of defect concentrations
defect_types

List types of defects existing in the DefectPhaseDiagram

find_stable_charges()[source]

Sets the stable charges and transition states for a series of defect entries. This function uses scipy’s HalfspaceInterection to oncstruct the polygons corresponding to defect stability as a function of the Fermi-level. The Halfspace Intersection constructs N-dimensional hyperplanes, in this case N=2, based on the equation of defect formation energy with considering chemical potentials:

E_form = E_0^{Corrected} + Q_{defect}*(E_{VBM} + E_{Fermi})

Extra hyperplanes are constructed to bound this space so that the algorithm can actually find enclosed region.

This code was modeled after the Halfspace Intersection code for the Pourbaix Diagram

solve_for_fermi_energy(temperature, chemical_potentials, bulk_dos)[source]

Solve for the Fermi energy self-consistently as a function of T and p_O2 Observations are Defect concentrations, electron and hole conc :param bulk_dos: bulk system dos (pymatgen Dos object) :param gap: Can be used to specify experimental gap.

Will be useful if the self consistent Fermi level is > DFT gap
Returns:Fermi energy
suggest_charges(tolerance=0.1)[source]

Suggest possible charges for defects to computee based on proximity of known transitions from entires to VBM and CBM

Parameters:tolerance (float) – tolerance with respect to the VBM and CBM to ` continue to compute new charges