doped.analysis module

Code to analyse VASP defect calculations.

These functions are built from a combination of useful modules from pymatgen, alongside substantial modification, in the efforts of making an efficient, user-friendly package for managing and analysing defect calculations, with publication-quality outputs.

class doped.analysis.DefectParser(defect_entry: DefectEntry, defect_vr: Vasprun | None = None, bulk_vr: Vasprun | None = None, skip_corrections: bool = False, error_tolerance: float = 0.05, parse_projected_eigen: bool | None = None, **kwargs)[source]

Bases: object

Create a DefectParser object, which has methods for parsing the results of defect supercell calculations.

Direct initialisation with DefectParser() is typically not recommended. Rather DefectParser.from_paths() or defect_entry_from_paths() are preferred as shown in the doped parsing tutorials.

Parameters:

defect_entry (DefectEntry) – doped DefectEntry
defect_vr (Vasprun) – pymatgen Vasprun object for the defect supercell calculation
bulk_vr (Vasprun) – pymatgen Vasprun object for the reference bulk supercell calculation
skip_corrections (bool) – Whether to skip calculation and application of finite-size charge corrections to the defect energy (not recommended in most cases). Default = False.
error_tolerance (float) – If the estimated error in the defect charge correction, based on the variance of the potential in the sampling region is greater than this value (in eV), then a warning is raised. (default: 0.05 eV)
parse_projected_eigen (bool) – Whether to parse the projected eigenvalues & orbitals from the bulk and defect calculations (so DefectEntry.get_eigenvalue_analysis() can then be used with no further parsing). Will initially try to load orbital projections from vasprun.xml(.gz) files (slightly slower but more accurate), or failing that from PROCAR(.gz) files if present in the bulk/defect directories. Parsing this data can increase total parsing time by anywhere from ~5-25%, so set to False if parsing speed is crucial. Default is None, which will attempt to load this data but with no warning if it fails (otherwise if True a warning will be printed).
**kwargs – Keyword arguments to pass to DefectParser() methods (load_FNV_data(), load_eFNV_data(), load_bulk_gap_data()) point_symmetry_from_defect_entry() or defect_from_structures, including bulk_locpot_dict, bulk_site_potentials, use_MP, mpid, api_key, symprec or oxi_state. Primarily used by DefectsParser to expedite parsing by avoiding reloading bulk data for each defect.

apply_corrections()[source]: Get defect corrections and warn if likely to be inappropriate.

Parse the defect calculation outputs in defect_path and return the DefectParser object. By default, the DefectParser.defect_entry.name attribute (later used to label defects in plots) is set to the defect_path folder name (if it is a recognised defect name), else it is set to the default doped name for that defect (using the estimated unrelaxed defect structure, for the point group and neighbour distances).

Note that the bulk and defect supercells should have the same definitions/basis sets (for site-matching and finite-size charge corrections to work appropriately).

Parameters:

defect_path (PathLike) – Path to defect supercell folder (containing at least vasprun.xml(.gz)).
bulk_path (PathLike) – Path to bulk supercell folder (containing at least vasprun.xml(.gz)). Not required if bulk_vr is provided.
bulk_vr (Vasprun) – pymatgen Vasprun object for the reference bulk supercell calculation, if already loaded (can be supplied to expedite parsing). Default is None.
bulk_procar (Procar) – easyunfold/pymatgen Procar object, for the reference bulk supercell calculation if already loaded (can be supplied to expedite parsing). Default is None.
dielectric (float or int or 3x1 matrix or 3x3 matrix) – Total dielectric constance (ionic + static contributions), in the same xyz Cartesian basis as the supercell calculations (likely but not necessarily the same as the raw output of a VASP dielectric calculation, if an oddly-defined primitive cell is used). If not provided, charge corrections cannot be computed and so skip_corrections will be set to True. See https://doped.readthedocs.io/en/latest/GGA_workflow_tutorial.html#dielectric-constant for information on calculating and converging the dielectric constant.
charge_state (int) – Charge state of defect. If not provided, will be automatically determined from defect calculation outputs, or if that fails, using the defect folder name (must end in “_+X” or “_-X” where +/-X is the defect charge state).
initial_defect_structure_path (PathLike) – Path to the initial/unrelaxed defect structure. Only recommended for use if structure matching with the relaxed defect structure(s) fails (rare). Default is None.
skip_corrections (bool) – Whether to skip the calculation and application of finite-size charge corrections to the defect energy (not recommended in most cases). Default = False.
error_tolerance (float) – If the estimated error in the defect charge correction, based on the variance of the potential in the sampling region, is greater than this value (in eV), then a warning is raised. (default: 0.05 eV)
bulk_band_gap_vr (PathLike or Vasprun) –
Path to a vasprun.xml(.gz) file, or a pymatgen Vasprun object, from which to determine the bulk band gap and band edge positions. If the VBM/CBM occur at k-points which are not included in the bulk supercell calculation, then this parameter should be used to provide the output of a bulk bandstructure calculation so that these are correctly determined. Alternatively, you can edit/add the "gap" and "vbm" entries in self.defect_entry.calculation_metadata to match the correct (eigen)values. If None, will use DefectEntry.calculation_metadata["bulk_path"] (i.e. the bulk supercell calculation output).

Note that the "gap" and "vbm" values should only affect the reference for the Fermi level values output by doped (as this VBM eigenvalue is used as the zero reference), thus affecting the position of the band edges in the defect formation energy plots and doping window / dopability limit functions, and the reference of the reported Fermi levels.
parse_projected_eigen (bool) – Whether to parse the projected eigenvalues & orbitals from the bulk and defect calculations (so DefectEntry.get_eigenvalue_analysis() can then be used with no further parsing). Will initially try to load orbital projections from vasprun.xml(.gz) files (slightly slower but more accurate), or failing that from PROCAR(.gz) files if present in the bulk/defect directories. Parsing this data can increase total parsing time by anywhere from ~5-25%, so set to False if parsing speed is crucial. Default is None, which will attempt to load this data but with no warning if it fails (otherwise if True a warning will be printed).
**kwargs – Keyword arguments to pass to DefectParser() methods (load_FNV_data(), load_eFNV_data(), load_bulk_gap_data()) point_symmetry_from_defect_entry() or defect_from_structures, including bulk_locpot_dict, bulk_site_potentials, use_MP, mpid, api_key, symprec or oxi_state. Primarily used by DefectsParser to expedite parsing by avoiding reloading bulk data for each defect.

Returns:

DefectParser object.

load_FNV_data(bulk_locpot_dict: dict | None = None)[source]

Load metadata required for performing Freysoldt correction (i.e. LOCPOT planar-averaged potential dictionary).

Requires “bulk_path” and “defect_path” to be present in DefectEntry.calculation_metadata, and VASP LOCPOT files to be present in these directories. Can read compressed “LOCPOT.gz” files. The bulk_locpot_dict can be supplied if already parsed, for expedited parsing of multiple defects.

Saves the bulk_locpot_dict and defect_locpot_dict dictionaries (containing the planar-averaged electrostatic potentials along each axis direction) to the DefectEntry.calculation_metadata dict, for use with DefectEntry.get_freysoldt_correction().

Parameters:: bulk_locpot_dict (dict) – Planar-averaged potential dictionary for bulk supercell, if already parsed. If None (default), will load from LOCPOT(.gz) file in defect_entry.calculation_metadata["bulk_path"]
Returns:: bulk_locpot_dict for reuse in parsing other defect entries

load_and_check_calculation_metadata()[source]: Pull metadata about the defect supercell calculations from the outputs, and check if the defect and bulk supercell calculations settings are compatible.

Load the "gap" and "vbm" values for the parsed DefectEntrys.

If bulk_band_gap_vr is provided, then these values are parsed from it, else taken from the parsed bulk supercell calculation.

Alternatively, one can specify query the Materials Project (MP) database for the bulk gap data, using use_MP = True, in which case the MP entry with the lowest number ID and composition matching the bulk will be used, or the MP ID (mpid) of the bulk material to use can be specified. This is not recommended as it will correspond to a severely-underestimated GGA DFT bandgap!

Parameters:

bulk_band_gap_vr (PathLike or Vasprun) –
Path to a vasprun.xml(.gz) file, or a pymatgen Vasprun object, from which to determine the bulk band gap and band edge positions. If the VBM/CBM occur at k-points which are not included in the bulk supercell calculation, then this parameter should be used to provide the output of a bulk bandstructure calculation so that these are correctly determined. Alternatively, you can edit/add the "gap" and "vbm" entries in self.defect_entry.calculation_metadata to match the correct (eigen)values. If None, will use DefectEntry.calculation_metadata["bulk_path"] (i.e. the bulk supercell calculation output).

Note that the "gap" and "vbm" values should only affect the reference for the Fermi level values output by doped (as this VBM eigenvalue is used as the zero reference), thus affecting the position of the band edges in the defect formation energy plots and doping window / dopability limit functions, and the reference of the reported Fermi levels.
use_MP (bool) – If True, will query the Materials Project database for the bulk gap data.
mpid (str) – If provided, will query the Materials Project database for the bulk gap data, using this Materials Project ID.
api_key (str) – Materials API key to access database.

load_eFNV_data(bulk_site_potentials: list | None = None)[source]

Load metadata required for performing Kumagai correction (i.e. atomic site potentials from the OUTCAR files).

Requires “bulk_path” and “defect_path” to be present in DefectEntry.calculation_metadata, and VASP OUTCAR files to be present in these directories. Can read compressed OUTCAR.gz files. The bulk_site_potentials can be supplied if already parsed, for expedited parsing of multiple defects.

Saves the bulk_site_potentials and defect_site_potentials lists (containing the atomic site electrostatic potentials, from -1*np.array(Outcar.electrostatic_potential)) to DefectEntry.calculation_metadata, for use with DefectEntry.get_kumagai_correction().

Parameters:: bulk_site_potentials (list) – Atomic site potentials for the bulk supercell, if already parsed. If None (default), will load from OUTCAR(.gz) file in defect_entry.calculation_metadata["bulk_path"]
Returns:: bulk_site_potentials for reuse in parsing other defect entries

Bases: object

A class for rapidly parsing multiple VASP defect supercell calculations for a given host (bulk) material.

Loops over calculation directories in output_path (likely the same output_path used with DefectsSet for file generation in doped.vasp) and parses the defect calculations into a dictionary of: {defect_name: DefectEntry}, where the defect_name is set to the defect calculation folder name (if it is a recognised defect name), else it is set to the default doped name for that defect (using the estimated unrelaxed defect structure, for the point group and neighbour distances). By default, searches for folders in output_path with subfolder containing vasprun.xml(.gz) files, and tries to parse them as DefectEntrys.

By default, tries multiprocessing to speed up defect parsing, which can be controlled with processes. If parsing hangs, this may be due to memory issues, in which case you should reduce processes (e.g. 4 or less).

Defect charge states are automatically determined from the defect calculation outputs if POTCARs are set up with pymatgen (see docs Installation page), or if that fails, using the defect folder name (must end in “_+X” or “_-X” where +/-X is the defect charge state).

Uses the (single) DefectParser class to parse the individual defect calculations. Note that the bulk and defect supercells should have the same definitions/basis sets (for site-matching and finite-size charge corrections to work appropriately).

Parameters:

output_path (PathLike) – Path to the output directory containing the defect calculation folders (likely the same output_path used with DefectsSet for file generation in doped.vasp). Default = current directory.
dielectric (float or int or 3x1 matrix or 3x3 matrix) – Total dielectric constance (ionic + static contributions), in the same xyz Cartesian basis as the supercell calculations (likely but not necessarily the same as the raw output of a VASP dielectric calculation, if an oddly-defined primitive cell is used). If not provided, charge corrections cannot be computed and so skip_corrections will be set to True. See https://doped.readthedocs.io/en/latest/GGA_workflow_tutorial.html#dielectric-constant for information on calculating and converging the dielectric constant.
subfolder (PathLike) – Name of subfolder(s) within each defect calculation folder (in the output_path directory) containing the VASP calculation files to parse (e.g. vasp_ncl, vasp_std, vasp_gam etc.). If not specified, doped checks first for vasp_ncl, vasp_std, vasp_gam subfolders with calculation outputs (vasprun.xml(.gz) files) and uses the highest level VASP type (ncl > std > gam) found as subfolder, otherwise uses the defect calculation folder itself with no subfolder (set subfolder = "." to enforce this).
bulk_path (PathLike) – Path to bulk supercell reference calculation folder. If not specified, searches for folder with name “X_bulk” in the output_path directory (matching the default doped name for the bulk supercell reference folder).
skip_corrections (bool) – Whether to skip the calculation & application of finite-size charge corrections to the defect energies (not recommended in most cases). Default = False.
error_tolerance (float) – If the estimated error in any charge correction, based on the variance of the potential in the sampling region, is greater than this value (in eV), then a warning is raised. (default: 0.05 eV)
bulk_band_gap_vr (PathLike or Vasprun) –
Path to a vasprun.xml(.gz) file, or a pymatgen Vasprun object, from which to determine the bulk band gap and band edge positions. If the VBM/CBM occur at k-points which are not included in the bulk supercell calculation, then this parameter should be used to provide the output of a bulk bandstructure calculation so that these are correctly determined. Alternatively, you can edit/add the "gap" and "vbm" entries in self.defect_entry.calculation_metadata to match the correct (eigen)values. If None, will use DefectEntry.calculation_metadata["bulk_path"] (i.e. the bulk supercell calculation output).

Note that the "gap" and "vbm" values should only affect the reference for the Fermi level values output by doped (as this VBM eigenvalue is used as the zero reference), thus affecting the position of the band edges in the defect formation energy plots and doping window / dopability limit functions, and the reference of the reported Fermi levels.
processes (int) – Number of processes to use for multiprocessing for expedited parsing. If not set, defaults to one less than the number of CPUs available. Set to 1 for no multiprocessing.
json_filename (PathLike) – Filename to save the parsed defect entries dict (DefectsParser.defect_dict) to in output_path, to avoid having to re-parse defects when later analysing further and aiding calculation provenance. Can be reloaded using the loadfn function from monty.serialization (and then input to DefectThermodynamics etc.). If None (default), set as {Host Chemical Formula}_defect_dict.json.gz. If False, no json file is saved.
parse_projected_eigen (bool) – Whether to parse the projected eigenvalues & orbitals from the bulk and defect calculations (so DefectEntry.get_eigenvalue_analysis() can then be used with no further parsing). Will initially try to load orbital projections from vasprun.xml(.gz) files (slightly slower but more accurate), or failing that from PROCAR(.gz) files if present in the bulk/defect directories. Parsing this data can increase total parsing time by anywhere from ~5-25%, so set to False if parsing speed is crucial. Default is None, which will attempt to load this data but with no warning if it fails (otherwise if True a warning will be printed).
**kwargs – Keyword arguments to pass to DefectParser() methods (load_FNV_data(), load_eFNV_data(), load_bulk_gap_data()) point_symmetry_from_defect_entry() or defect_from_structures, including bulk_locpot_dict, bulk_site_potentials, use_MP, mpid, api_key, symprec or oxi_state. Primarily used by DefectsParser to expedite parsing by avoiding reloading bulk data for each defect.

defect_dict

Dictionary of parsed defect calculations in the format: {"defect_name": DefectEntry} where the defect_name is set to the defect calculation folder name (if it is a recognised defect name), else it is set to the default doped name for that defect (using the estimated unrelaxed defect structure, for the point group and neighbour distances).

Type:: dict

get_defect_thermodynamics(chempots: dict | None = None, el_refs: dict | None = None, vbm: float | None = None, band_gap: float | None = None, dist_tol: float = 1.5, check_compatibility: bool = True, bulk_dos: FermiDos | None = None, skip_check: bool = False) → DefectThermodynamics[source]

Generates a DefectThermodynamics object from the parsed DefectEntry objects in self.defect_dict, which can then be used to analyse and plot the defect thermodynamics (formation energies, transition levels, concentrations etc).

Note that the DefectEntry.name attributes (rather than the defect_name key in the defect_dict) are used to label the defects in plots.

Parameters:

chempots (dict) –
Dictionary of chemical potentials to use for calculating the defect formation energies. This can have the form of {"limits": [{'limit': [chempot_dict]}]} (the format generated by doped's chemical potential parsing functions (see tutorials)) which allows easy analysis over a range of chemical potentials - where limit(s) (chemical potential limit(s)) to analyse/plot can later be chosen using the limits argument.

Alternatively this can be a dictionary of chemical potentials for a single limit (limit), in the format: {element symbol: chemical potential}. If manually specifying chemical potentials this way, you can set the el_refs option with the DFT reference energies of the elemental phases in order to show the formal (relative) chemical potentials above the formation energy plot, in which case it is the formal chemical potentials (i.e. relative to the elemental references) that should be given here, otherwise the absolute (DFT) chemical potentials should be given.

If None (default), sets all chemical potentials to zero. Chemical potentials can also be supplied later in each analysis function. (Default: None)
el_refs (dict) – Dictionary of elemental reference energies for the chemical potentials in the format: {element symbol: reference energy} (to determine the formal chemical potentials, when chempots has been manually specified as {element symbol: chemical potential}). Unnecessary if chempots is provided in format generated by doped (see tutorials). (Default: None)
vbm (float) – VBM eigenvalue to use as Fermi level reference point for analysis. If None (default), will use "vbm" from the calculation_metadata dict attributes of the parsed DefectEntry objects, which by default is taken from the bulk supercell VBM (unless bulk_band_gap_vr is set during parsing). Note that vbm should only affect the reference for the Fermi level values output by doped (as this VBM eigenvalue is used as the zero reference), thus affecting the position of the band edges in the defect formation energy plots and doping window / dopability limit functions, and the reference of the reported Fermi levels.
band_gap (float) – Band gap of the host, to use for analysis. If None (default), will use “gap” from the calculation_metadata dict attributes of the parsed DefectEntry objects.
dist_tol (float) – Threshold for the closest distance (in Å) between equivalent defect sites, for different species of the same defect type, to be grouped together (for plotting and transition level analysis). If the minimum distance between equivalent defect sites is less than dist_tol, then they will be grouped together, otherwise treated as separate defects. (Default: 1.5)
check_compatibility (bool) – Whether to check the compatibility of the bulk entry for each defect entry (i.e. that all reference bulk energies are the same). (Default: True)
bulk_dos (FermiDos or Vasprun or PathLike) –
pymatgen FermiDos for the bulk electronic density of states (DOS), for calculating Fermi level positions and defect/carrier concentrations. Alternatively, can be a pymatgen Vasprun object or path to the vasprun.xml(.gz) output of a bulk DOS calculation in VASP. Can also be provided later when using get_equilibrium_fermi_level(), get_quenched_fermi_level_and_concentrations etc, or set using DefectThermodynamics.bulk_dos = ... (with the same input options).

Usually this is a static calculation with the primitive cell of the bulk material, with relatively dense k-point sampling (especially for materials with disperse band edges) to ensure an accurately-converged DOS and thus Fermi level. ISMEAR = -5 (tetrahedron smearing) is usually recommended for best convergence wrt k-point sampling. Consistent functional settings should be used for the bulk DOS and defect supercell calculations. (Default: None)
skip_check (bool) – Whether to skip the warning about the DOS VBM differing from the defect entries VBM by >0.05 eV. Should only be used when the reason for this difference is known/acceptable. (Default: False)

Returns:

doped DefectThermodynamics object (DefectThermodynamics)

doped.analysis.check_and_set_defect_entry_name(defect_entry: DefectEntry, possible_defect_name: str = '', bulk_symm_ops: list | None = None) → None[source]

Check that possible_defect_name is a recognised format by doped (i.e. in the format "{defect_name}_{optional_site_info}_{charge_state}").

If the DefectEntry.name attribute is not defined or does not end with the charge state, then the entry will be renamed with the doped default name for the unrelaxed defect (i.e. using the point symmetry of the defect site in the bulk cell).

Parameters:

defect_entry (DefectEntry) – DefectEntry object.
possible_defect_name (str) – Possible defect name (usually the folder name) to check if recognised by doped, otherwise defect name is re-determined.
bulk_symm_ops (list) – List of symmetry operations of the defect_entry.bulk_supercell structure (used in determining the unrelaxed point symmetry), to avoid re-calculating. Default is None (recalculates).

Parse the defect calculation outputs in defect_path and return the parsed DefectEntry object.

By default, the DefectEntry.name attribute (later used to label the defects in plots) is set to the defect_path folder name (if it is a recognised defect name), else it is set to the default doped name for that defect (using the estimated unrelaxed defect structure, for the point group and neighbour distances).

Note that the bulk and defect supercells should have the same definitions/basis sets (for site-matching and finite-size charge corrections to work appropriately).

Parameters:

defect_path (PathLike) – Path to defect supercell folder (containing at least vasprun.xml(.gz)).
bulk_path (PathLike) – Path to bulk supercell folder (containing at least vasprun.xml(.gz)).
dielectric (float or int or 3x1 matrix or 3x3 matrix) – Total dielectric constance (ionic + static contributions), in the same xyz Cartesian basis as the supercell calculations (likely but not necessarily the same as the raw output of a VASP dielectric calculation, if an oddly-defined primitive cell is used). If not provided, charge corrections cannot be computed and so skip_corrections will be set to True. See https://doped.readthedocs.io/en/latest/GGA_workflow_tutorial.html#dielectric-constant for information on calculating and converging the dielectric constant.
charge_state (int) – Charge state of defect. If not provided, will be automatically determined from the defect calculation outputs.
initial_defect_structure_path (PathLike) – Path to the initial/unrelaxed defect structure. Only recommended for use if structure matching with the relaxed defect structure(s) fails (rare). Default is None.
skip_corrections (bool) – Whether to skip the calculation and application of finite-size charge corrections to the defect energy (not recommended in most cases). Default = False.
error_tolerance (float) – If the estimated error in the defect charge correction, based on the variance of the potential in the sampling region is greater than this value (in eV), then a warning is raised. (default: 0.05 eV)
bulk_band_gap_vr (PathLike or Vasprun) –
Path to a vasprun.xml(.gz) file, or a pymatgen Vasprun object, from which to determine the bulk band gap and band edge positions. If the VBM/CBM occur at k-points which are not included in the bulk supercell calculation, then this parameter should be used to provide the output of a bulk bandstructure calculation so that these are correctly determined. Alternatively, you can edit/add the "gap" and "vbm" entries in self.defect_entry.calculation_metadata to match the correct (eigen)values. If None, will use DefectEntry.calculation_metadata["bulk_path"] (i.e. the bulk supercell calculation output).

Note that the "gap" and "vbm" values should only affect the reference for the Fermi level values output by doped (as this VBM eigenvalue is used as the zero reference), thus affecting the position of the band edges in the defect formation energy plots and doping window / dopability limit functions, and the reference of the reported Fermi levels.
**kwargs – Keyword arguments to pass to DefectParser() methods (load_FNV_data(), load_eFNV_data(), load_bulk_gap_data()) point_symmetry_from_defect_entry() or defect_from_structures, including bulk_locpot_dict, bulk_site_potentials, use_MP, mpid, api_key, symprec or oxi_state.

Returns:

Parsed DefectEntry object.

doped.analysis.defect_from_structures(bulk_supercell: Structure, defect_supercell: Structure, return_all_info: bool = False, bulk_voronoi_node_dict: dict | None = None, skip_atom_mapping_check: bool = False, **kwargs)[source]

Auto-determines the defect type and defect site from the supplied bulk and defect structures, and returns a corresponding Defect object.

If return_all_info is set to true, then also returns:

relaxed defect site in the defect supercell
the defect site in the bulk supercell
defect site index in the defect supercell
bulk site index (index of defect site in bulk supercell)
guessed initial defect structure (before relaxation)
‘unrelaxed defect structure’ (also before relaxation, but with interstitials at their final relaxed positions, and all bulk atoms at their unrelaxed positions).

Parameters:

bulk_supercell (Structure) – Bulk supercell structure.
defect_supercell (Structure) – Defect structure to use for identifying the defect site and type.
return_all_info (bool) – If True, returns additional python objects related to the site-matching, listed above. (Default = False)
bulk_voronoi_node_dict (dict) – Dictionary of bulk supercell Voronoi node information, for expedited site-matching. If None, will be re-calculated.
skip_atom_mapping_check (bool) – If True, skips the atom mapping check which ensures that the bulk and defect supercell lattice definitions are matched (important for accurate defect site determination and charge corrections). Can be used to speed up parsing when you are sure the cell definitions match (e.g. both supercells were generated with doped). Default is False.
**kwargs – Keyword arguments to pass to Defect initialization, such as oxi_state or multiplicity. These are mainly intended for use cases when fast site matching and Defect creation are desired (e.g. when analysing MD trajectories of defects), where providing these parameters can greatly speed up parsing. Setting oxi_state='N/A' and multiplicity=1 will skip their auto-determination and accelerate parsing, if these properties are not required.

Returns:

doped Defect object.

If return_all_info is True, then also:

defect_site (Site):: pymatgen Site object of the relaxed defect site in the defect supercell.
defect_site_in_bulk (Site):: pymatgen Site object of the defect site in the bulk supercell (i.e. unrelaxed vacancy/substitution site, or final relaxed interstitial site for interstitials).
defect_site_index (int):: index of defect site in defect supercell (None for vacancies)
bulk_site_index (int):: index of defect site in bulk supercell (None for interstitials)
guessed_initial_defect_structure (Structure):: pymatgen Structure object of the guessed initial defect structure.
unrelaxed_defect_structure (Structure):: pymatgen Structure object of the unrelaxed defect structure.
bulk_voronoi_node_dict (dict):: Dictionary of bulk supercell Voronoi node information, for further expedited site-matching.

Return type:

defect (Defect)

doped.analysis.defect_name_from_structures(bulk_structure: Structure, defect_structure: Structure)[source]

Get the doped/SnB defect name using the bulk and defect structures.

Parameters:

bulk_structure (Structure) – Bulk (pristine) structure.
defect_structure (Structure) – Defect structure.

Returns:

Defect name.

Return type:

str

doped.analysis.guess_defect_position(defect_supercell: Structure) → ndarray[float][source]

Guess the position (in Cartesian coordinates) of a defect in an input defect supercell, without a bulk/reference supercell.

This is achieved by computing cosine dissimilarities between site SOAP vectors (and the mean SOAP vectors for each species) and then determining the centre of mass of sites, weighted by the squared cosine dissimilarities. For accurate defect site determination, the defect_from_structure function (or underlying code) is preferred. These coordinates are unlikely to _directly_ match the defect position (especially in the presence of random noise), but should provide a pretty good estimate in most cases. If the defect is an extrinsic interstitial/substitution, then this will identify the exact defect site.

Parameters:: defect_supercell (Structure) – Defect supercell structure.
Returns:: Guessed position of the defect in Cartesian coordinates.
Return type:: np.ndarray[float]