pymatgen.analysis.defects.dilute_solution_model module

check_input(def_list)[source]
compute_defect_density(structure, e0, vac_defs, antisite_defs, T=800, trial_chem_pot=None, plot_style='highcharts')[source]

Wrapper for the dilute_solution_model. The computed plot data is prepared based on plot_style.

Parameters:
  • structure – pymatgen.core.structure.Structure object representing the primitive or unitcell of the crystal.
  • e0 – The total energy of the undefected system. This is E0 from VASP calculation.
  • vac_defs – List of vacancy defect parameters in the dictionary format. The keys of the dict associated with each vacancy defect are 1) site_index, 2) site_specie, 3) site_multiplicity, and 4) energy. 1-3 can be obtained from pymatgen.analysis.defects.point_defects.Vacancy class. Site index is expected to start with 1 (fortran index).
  • antisite_defs – List of antisite defect parameters in the dictionary format. The keys of the dict associated with each antisite defect are 1) site_index, 2) site_specie, 3) site_multiplicity, 4) substitution_specie, and 5) energy. 1-3 can be obtained from pymatgen.analysis.defects.point_defects.Vacancy class.
  • T – Temperature in Kelvin
  • trial_chem_pot (optional) – Trial chemical potentials to speedup the plot generation. Format is {el1:mu1,…}
  • plot_style (string) – Allowed options are 1) highcharts (default) 2) gnuplot
Returns:

The plot data is generated and returned in asked format.

dilute_solution_model(structure, e0, vac_defs, antisite_defs, T, trial_chem_pot=None, generate='plot')[source]

Compute the defect densities using dilute solution model.

Parameters:
  • structure – pymatgen.core.structure.Structure object representing the primitive or unitcell of the crystal.
  • e0 – The total energy of the undefected system. This is E0 from VASP calculation.
  • vac_defs – List of vacancy defect parameters in the dictionary format. The keys of the dict associated with each vacancy defect are 1) site_index, 2) site_specie, 3) site_multiplicity, and 4) energy. 1-3 can be obtained from pymatgen.analysis.defects.point_defects.Vacancy class. Site index is expected to start with 1 (fortran index).
  • antisite_defs – List of antisite defect parameters in the dictionary format. The keys of the dict associated with each antisite defect are 1) site_index, 2) site_specie, 3) site_multiplicity, 4) substitution_specie, and 5) energy. 1-3 can be obtained from pymatgen.analysis.defects.point_defects.Vacancy class.
  • T – Temperature in Kelvin
  • trial_chem_pot (optional) – Trial chemical potentials to speedup the plot generation. Format is {el1:mu1,…}
  • generate (string) – Options are plot or energy Chemical potentials are also returned with energy option. If energy option is not chosen, plot is generated.
Returns:

If generate=plot, the plot data is generated and returned in HighCharts format. If generate=energy, defect formation enthalpies and chemical potentials are returned.

solute_defect_density(structure, e0, vac_defs, antisite_defs, solute_defs, solute_concen=0.01, T=800, trial_chem_pot=None, plot_style='highchargs')[source]

Wrapper for the solute_site_preference_finder. The computed plot data is prepared based on plot_style.

Parameters:
  • structure – pymatgen.core.structure.Structure object representing the primitive or unitcell of the crystal.
  • e0 – The total energy of the undefected system. This is E0 from VASP calculation.
  • vac_defs – List of vacancy defect parameters in the dictionary format. The keys of the dict associated with each vacancy defect are 1) site_index, 2) site_specie, 3) site_multiplicity, and 4) energy. 1-3 can be obtained from pymatgen.analysis.defects.point_defects.Vacancy class. Site index is expected to start with 1 (fortran index).
  • antisite_defs – List of antisite defect parameters in the dictionary format. The keys of the dict associated with each antisite defect are 1) site_index, 2) site_specie, 3) site_multiplicity, 4) substitution_specie, and 5) energy. 1-3 can be obtained from pymatgen.analysis.defects.point_defects.Vacancy class.
  • solute_defs – List of solute defect parameters in the dictionary format. Similary to that of antisite defs, wtih solute specie specified in substitution_specie
  • solute_concen – Solute concentration (in fractional value)
  • T – Temperature in Kelvin
  • trial_chem_pot (optional) – Trial chemical potentials to speedup the plot generation. Format is {el1:mu1,…}
  • plot_style (string) – Allowed options are 1) highcharts (default) 2) gnuplot
Returns:

The plot data is generated and returned in asked format.

solute_site_preference_finder(structure, e0, T, vac_defs, antisite_defs, solute_defs, solute_concen=0.01, trial_chem_pot=None)[source]

Compute the solute defect densities using dilute solution model. :param structure: pymatgen.core.structure.Structure object representing the

primitive or unitcell of the crystal.
Parameters:
  • e0 – The total energy of the undefected system. This is E0 from VASP calculation.
  • T – Temperature in Kelvin
  • vac_defs – List of vacancy defect parameters in the dictionary format. The keys of the dict associated with each vacancy defect are 1) site_index, 2) site_specie, 3) site_multiplicity, and 4) energy. 1-3 can be obtained from pymatgen.analysis.defects.point_defects.Vacancy class. Site index is expected to start with 1 (fortran index).
  • antisite_defs – List of antisite defect parameters in the dictionary format. The keys of the dict associated with each antisite defect are 1) site_index, 2) site_specie, 3) site_multiplicity, 4) substitution_specie, and 5) energy. 1-3 can be obtained from pymatgen.analysis.defects.point_defects.Vacancy class.
  • solute_defs – List of solute defect parameters in the dictionary format. Similary to that of antisite defs, wtih solute specie specified in substitution_specie
  • solute_concen – Solute concentration (in fractional value)
  • trial_chem_pot – Trial chemical potentials to speedup the plot generation. Format is {el1:mu1,…}
Returns:

The data for plotting the solute defect concentration.

Return type:

plot_data