merge

.github/workflows/pip_install_test.yml

@@ -40,8 +40,17 @@ jobs:
  sleep 360 # wait 10 minutes for PyPI to update with the new release
  python -m pip install --upgrade pip
  pip install doped[tests] # install only from PyPI
+
+ - name: Install spglib on macOS
+ if: matrix.os == 'macos-14'
+ run: |
  pip install git+https://github.com/spglib/spglib --config-settings=cmake.define.SPGLIB_SHARED_LIBS=OFF # avoid spglib warnings
 
+ - name: Install spglib on ubuntu
+ if: matrix.os == 'ubuntu-latest'
+ run: |
+ conda install -c conda-forge spglib # avoid spglib warnings
+
  - name: Test
  run: |
  pytest -vv -m "not mpl_image_compare" tests # all non-plotting tests

.github/workflows/test.yml

@@ -34,8 +34,17 @@ jobs:
  run: |
  python -m pip install --upgrade pip
  pip install -e .[tests]
+
+ - name: Install spglib on macOS
+ if: matrix.os == 'macos-14'
+ run: |
  pip install git+https://github.com/spglib/spglib --config-settings=cmake.define.SPGLIB_SHARED_LIBS=OFF # avoid spglib warnings
 
+ - name: Install spglib on ubuntu
+ if: matrix.os == 'ubuntu-latest'
+ run: |
+ conda install -c conda-forge spglib # avoid spglib warnings
+
  - name: Test
  run: |
  pytest -vv -m "not mpl_image_compare" tests # all non-plotting tests

CHANGELOG.rst

@@ -1,6 +1,33 @@
 Change Log
 ==========
 
+v.2.4.7
+----------
+- Update doping/carrier concentration functions to be more accurate and robust (following logic discussed
+ here: https://github.com/materialsproject/pymatgen/pull/3879).
+- Improve reverse-supercell-matrix determination for `generate_supercell=False`
+- Refactor `bulk_band_gap_path` to `bulk_band_gap_vr` in `DefectsParser`/`DefectParser`,
+- Update docstrings to reiterate that bulk supercell VBM is used as VBM reference point for the Fermi level
+ by default, unless alternative `bulk_band_gap_vr` provided.
+
+v.2.4.6
+----------
+- Update ``Defect``, ``DefectEntry`` and ``DefectThermodynamics`` properties/methods to be even more
+ efficient with calculations of formation energies and concentrations. Gives ~10x speedup in Fermi
+ solving and concentration calculations (e.g. from 2 hours to 12 minutes for 2D chempot vs temp CdTe grid
+ in thermodynamics tutorial).
+- Avoid unnecessary ``DeprecationWarning``s from latest ``spglib`` release.
+
+v.2.4.5
+----------
+- Enforce ``shakenbreak>=2.3.4`` requirement.
+
+v.2.4.4
+----------
+- Make oxidation state guessing more efficient, semi-significant speed up in generation/parsing for tough cases.
+- Add `bulk_site_concentration` property to `DefectEntry`, giving the concentration of the corresponding lattice site of that defect in the pristine bulk.
+- Minor updates to ensure compatibility with recent ``pymatgen`` and ``ASE`` releases.
+
 v.2.4.3
 ----------
 - Remove ``spglib<=2.0.2`` dependency (set to avoid unnecessary warnings), and update installation instructions accordingly.

README.md

@@ -60,11 +60,20 @@ As shown in the `doped` tutorials, it is highly recommended to use the [`ShakeNB
 
 ## Studies using `doped`, so far
 
+<!--
+Not currently cited but should be for chempot plot:
+- Quadir et al. **_Low-Temperature Synthesis of Stable CaZn<sub>2</sub>P<sub>2</sub> Zintl Phosphide Thin Films as Candidate Top Absorbers_** [_arXiv_](https://arxiv.org/abs/2406.15637) 2024
+-->
+- Z. Yuan & G. Hautier **_First-principles study of defects and doping limits in CaO_** [_Applied Physics Letters_](https://doi.org/10.1063/5.0211707) 2024
 - B. E. Murdock et al. **_Li-Site Defects Induce Formation of Li-Rich Impurity Phases: Implications for Charge Distribution and Performance of LiNi<sub>0.5-x</sub>M<sub>x</sub>Mn<sub>1.5</sub>O<sub>4</sub> Cathodes (M = Fe and Mg; x = 0.05–0.2)_** [_Advanced Materials_](https://doi.org/10.1002/adma.202400343) 2024
 - A. G. Squires et al. **_Oxygen dimerization as a defect-driven process in bulk LiNiO2<sub>2</sub>_** [_ChemRxiv_](https://doi.org/10.26434/chemrxiv-2024-lcmkj) 2024
-- X. Wang et al. **_Upper efficiency limit of Sb<sub>2</sub>Se<sub>3</sub> solar cells_** [_arXiv_](https://arxiv.org/abs/2402.04434) 2024
-- I. Mosquera-Lois et al. **_Machine-learning structural reconstructions for accelerated point defect calculations_** [_arXiv_](https://doi.org/10.48550/arXiv.2401.12127) 2024
-- W. Dou et al. **_Giant Band Degeneracy via Orbital Engineering Enhances Thermoelectric Performance from Sb<sub>2</sub>Si<sub>2</sub>Te<sub>6</sub> to Sc<sub>2</sub>Si<sub>2</sub>Te<sub>6</sub>_** [_ChemRxiv_](https://doi.org/10.26434/chemrxiv-2024-hm6vh) 2024
+- Y. Fu & H. Lohan et al. **_Factors Enabling Delocalized Charge-Carriers in Pnictogen-Based
+Solar Absorbers: In-depth Investigation into CuSbSe<sub>2</sub>_** [_arXiv_](https://doi.org/10.48550/arXiv.2401.02257) 2024
+- S. Hachmioune et al. **_Exploring the Thermoelectric Potential of MgB4: Electronic Band Structure, Transport Properties, and Defect Chemistry_** [_Chemistry of Materials_](https://doi.org/10.1021/acs.chemmater.4c00584) 2024
+- J. Hu et al. **_Enabling ionic transport in Li3AlP2 the roles of defects and disorder_** [_ChemRxiv_](https://doi.org/10.26434/chemrxiv-2024-3s0kh) 2024
+- X. Wang et al. **_Upper efficiency limit of Sb<sub>2</sub>Se<sub>3</sub> solar cells_** [_Joule_](https://doi.org/10.1016/j.joule.2024.05.004) 2024
+- I. Mosquera-Lois et al. **_Machine-learning structural reconstructions for accelerated point defect calculations_** [_npj Computational Materials_](https://doi.org/10.1038/s41524-024-01303-9) 2024
+- W. Dou et al. **_Band Degeneracy and Anisotropy Enhances Thermoelectric Performance from Sb<sub>2</sub>Si<sub>2</sub>Te<sub>6</sub> to Sc<sub>2</sub>Si<sub>2</sub>Te<sub>6</sub>_** [_Journal of the American Chemical Society_](https://doi.org/10.1021/jacs.4c01838) 2024
 - K. Li et al. **_Computational Prediction of an Antimony-based n-type Transparent Conducting Oxide: F-doped Sb<sub>2</sub>O<sub>5</sub>_** [_Chemistry of Materials_](https://doi.org/10.1021/acs.chemmater.3c03257) 2023
 - X. Wang et al. **_Four-electron negative-U vacancy defects in antimony selenide_** [_Physical Review B_](https://journals.aps.org/prb/abstract/10.1103/PhysRevB.108.134102) 2023
 - Y. Kumagai et al. **_Alkali Mono-Pnictides: A New Class of Photovoltaic Materials by Element Mutation_** [_PRX Energy_](http://dx.doi.org/10.1103/PRXEnergy.2.043002) 2023

docs/Dev_ToDo.md

@@ -2,10 +2,8 @@
 ## Chemical potential
 - Check through chemical potential TO-DOs. Need to recheck validity of approximations used for extrinsic competing phases (and code for this). Proper `vasp_std` setup (with `NKRED` folders like for defect calcs) and `vasp_ncl` generation.
 - Efficient generation of competing phases for which there are many polymorphs? See SK notes from CdTe competing phases.
-- Update chemical potential tools to work with new Materials Project API. Currently, supplying an API key for the new Materials Project API returns entries which do not have `e_above_hull` as a property, and so crashes. Ideally would be good to be compatible with both the legacy and new API, which should be fairly straightforward (try importing MPRester from mp_api client except ImportError import from pmg then will need to make a whole separate query/search because `band_gap` and `total_magnetisation` no longer accessible from `get_entries`). See https://docs.materialsproject.org/downloading-data/using-the-api
 - Publication ready chemical potential diagram plotting tool as in Adam Jackson's `plot-cplap-ternary` (3D) and Sungyhun's `cplapy` (4D) (see `doped_chempot_plotting_example.ipynb`; code there, just needs to be implemented in module functions). `ChemicalPotentialGrid` in `py-sc-fermi` interface could be quite useful for this? (Worth moving that part of code out of `interface` subpackage?) Also can see https://github.com/materialsproject/pymatgen-analysis-defects/blob/main/pymatgen/analysis/defects/plotting/phases.py for 2D chempot plotting.
  - Also see `Cs2SnTiI6` notebooks for template code for this.
-- Note in tutorial that LaTeX table generator website can also be used with the `to_csv()` function to generate LaTeX tables for the competing phases.
 
 ## Post-processing / analysis / plotting
 - Better automatic defect formation energy plot colour handling (auto-change colormap based on number of defects, set similar colours for similar defects (types and inequivalent sites)) – and more customisable?
@@ -87,8 +85,8 @@
  there's any useful functionality we want to add!
 
 ## SK To-Do for next update:
-- Remove `typing-extensions` requirement from `pyproject.toml`, once new `pymatgen-analysis-defects` released.
 - `doped` repo/docs cleanup `TODO`s above
+- Note in chempots tutorial that LaTeX table generator website can also be used with the `to_csv()` function to generate LaTeX tables for the competing phases.
 - Quick-start tutorial suggested by Alex G
 - Add chempot grid plotting tool, shown in `JOSS_plots` using Alex's chemical potential grid, and test (and remove TODO from JOSS plots notebook).
 - `dist_tol` should also group defects for the concentration etc functions, currently doesn't (e.g. `CdTe_thermo.get_equilibrium_concentrations(limit="Te-rich", per_charge=False, fermi_level=0.5)` and `CdTe_thermo.dist_tol=10; CdTe_thermo.get_equilibrium_concentrations(limit="Te-rich", per_charge=False, fermi_level=0.5)`, same output)

docs/Installation.rst

@@ -20,6 +20,9 @@ by running the following in Python, and confirming that the same version numbers
  print(spglib.__version__)
  print(spglib.spg_get_version_full())
 
+In some cases, you might need to first uninstall ``spglib`` with both ``conda uninstall spglib`` and
+``pip uninstall spglib`` (to ensure no duplicate installations), before reinstalling.
+
 Alternatively if desired, ``doped`` can also be installed from ``conda`` with:
 
 .. code-block:: bash

docs/Tips.rst

@@ -465,21 +465,21 @@ various stages in the tutorials, this can be achieved using the ``dumpfn``/``loa
 .. code-block:: python
 
  # save a DefectThermodynamics object to a JSON file
- defect_thermo.to_json("MgO_DefectThermodynamics.json")
+ defect_thermo.to_json("MgO_DefectThermodynamics.json.gz")
 
  # then later in a different python session or notebook, we can reload the
  # DefectThermodynamics object from the JSON file, containing all the associated info
  from doped.thermodynamics import DefectThermodynamics
- defect_thermodynamics = DefectThermodynamics.from_json("MgO_DefectThermodynamics.json")
+ defect_thermodynamics = DefectThermodynamics.from_json("MgO_DefectThermodynamics.json.gz")
 
  # alternatively, we can directly use the monty dumpfn/loadfn functions
  # directly on any doped object, e.g. with our ``DefectsSet`` object
  # containing all the info on the generated VASP input files:
  from monty.serialization import dumpfn, loadfn
- dumpfn(obj=defects_set, fn="MgO_DefectsSet.json")
+ dumpfn(obj=defects_set, fn="MgO_DefectsSet.json.gz")
 
  # and again later reload the object from the JSON file
- defects_set = loadfn("MgO_DefectsSet.json")
+ defects_set = loadfn("MgO_DefectsSet.json.gz")
 
 .. note::
 

docs/Troubleshooting.rst

@@ -14,7 +14,7 @@ message about the origin of the problem, it is likely to be an issue with your v
 
 .. code:: bash
 
- pip install pymatgen pymatgen-analysis-defects --upgrade
+ pip install pymatgen pymatgen-analysis-defects monty --upgrade
  pip install doped --upgrade
 
 If this does not solve your issue, please check the specific cases noted below. If your issue still isn't
@@ -139,4 +139,4 @@ If you do not use the ``if __name__ == '__main__':...`` syntax, you may encounte
 
 .. NOTE::
  If you run into any issues using ``doped`` that aren't addressed above, please contact the developers
- through the ``GitHub`` `Issues <https://github.com/SMTG-Bham/doped/issues>`_ page, or by email.
+ through the ``GitHub`` `Issues <https://github.com/SMTG-Bham/doped/issues>`_ page.

docs/conf.py

@@ -25,7 +25,7 @@
 author = 'Seán R. Kavanagh'
 
 # The full version, including alpha/beta/rc tags
-release = '2.4.3'
+release = '2.4.7'
 
 
 # -- General configuration ---------------------------------------------------

docs/index.rst

@@ -89,11 +89,18 @@ the
 Studies using ``doped``, so far
 ===============================
 
+.. Not currently cited but should be for chempot plot:
+ Quadir et al. **_Low-Temperature Synthesis of Stable CaZn<sub>2</sub>P<sub>2</sub> Zintl Phosphide Thin Films as Candidate Top Absorbers_** [_arXiv_](https://arxiv.org/abs/2406.15637) 2024
+
+- Z\. Yuan & G. Hautier **First-principles study of defects and doping limits in CaO** `Applied Physics Letters <https://doi.org/10.1063/5.0211707>`_ 2024
 - B\. E. Murdock et al. **Li-Site Defects Induce Formation of Li-Rich Impurity Phases: Implications for Charge Distribution and Performance of LiNi** :sub:`0.5-x` **M** :sub:`x` **Mn** :sub:`1.5` **O** :sub:`4` **Cathodes (M = Fe and Mg; x = 0.05–0.2)** `Advanced Materials <https://doi.org/10.1002/adma.202400343>`_ 2024
 - A\. G. Squires et al. **Oxygen dimerization as a defect-driven process in bulk LiNiO₂** `ChemRxiv <https://doi.org/10.26434/chemrxiv-2024-lcmkj>`_ 2024
-- X\. Wang et al. **Upper efficiency limit of Sb₂Se₃ solar cells** `arXiv <https://arxiv.org/abs/2402.04434>`_ 2024
-- I\. Mosquera-Lois et al. **Machine-learning structural reconstructions for accelerated point defect calculations** `arXiv <https://doi.org/10.48550/arXiv.2401.12127>`_ 2024
-- W\. Dou et al. **Giant Band Degeneracy via Orbital Engineering Enhances Thermoelectric Performance from Sb₂Si₂Te₆ to Sc₂Si₂Te₆** `ChemRxiv <https://doi.org/10.26434/chemrxiv-2024-hm6vh>`_ 2024
+- Y\. Fu & H. Lohan et al. **Factors Enabling Delocalized Charge-Carriers in Pnictogen-Based Solar Absorbers: In-depth Investigation into CuSbSe<sub>2</sub>** `arXiv <https://doi.org/10.48550/arXiv.2401.02257>`_ 2024
+- S\. Hachmioune et al. **Exploring the Thermoelectric Potential of MgB4: Electronic Band Structure, Transport Properties, and Defect Chemistry** `Chemistry of Materials <https://doi.org/10.1021/acs.chemmater.4c00584>`_ 2024
+- J\. Hu et al. **Enabling ionic transport in Li3AlP2 the roles of defects and disorder** `ChemRxiv <https://doi.org/10.26434/chemrxiv-2024-3s0kh>`_ 2024
+- X\. Wang et al. **Upper efficiency limit of Sb₂Se₃ solar cells** `Joule <https://doi.org/10.1016/j.joule.2024.05.004>`_ 2024
+- I\. Mosquera-Lois et al. **Machine-learning structural reconstructions for accelerated point defect calculations** `npj Computational Materials <https://doi.org/10.1038/s41524-024-01303-9>`_ 2024
+- W\. Dou et al. **Band Degeneracy and Anisotropy Enhances Thermoelectric Performance from Sb₂Si₂Te₆ to Sc₂Si₂Te₆** `Journal of the American Chemical Society <https://doi.org/10.1021/jacs.4c01838>`_ 2024
 - K\. Li et al. **Computational Prediction of an Antimony-based n-type Transparent Conducting Oxide: F-doped Sb₂O₅** `Chemistry of Materials <https://doi.org/10.1021/acs.chemmater.3c03257>`_ 2024
 - X\. Wang et al. **Four-electron negative-U vacancy defects in antimony selenide** `Physical Review B <https://journals.aps.org/prb/abstract/10.1103/PhysRevB.108.134102>`_ 2023
 - Y\. Kumagai et al. **Alkali Mono-Pnictides: A New Class of Photovoltaic Materials by Element Mutation** `PRX Energy <http://dx.doi.org/10.1103/PRXEnergy.2.043002>`__ 2023

doped/VASP_sets/DefectSet.yaml

@@ -9,7 +9,7 @@ INCAR:
 # Notes:
 # KPAR is set to 2 for `vasp_std` calculations (multiple kpoints)
 # NUPDOWN is set to 0 (singlet) or 1 (doublet) depending on the number of electrons
-# (even or odd, respectively) – see https://doped.readthedocs.io/en/latest/Tips.html#spin-polarisation
+# (even or odd, respectively) -- see https://doped.readthedocs.io/en/latest/Tips.html#spin-polarisation
 # Note that even-electron defects with multiple spin-polarised states (e.g. bipolarons;
 # Fig. 2c in doi.org/10.1021/acsenergylett.1c00380) could also have triplet spin states
 # (NUPDOWN=2), but the energy difference is likely to be small.

doped/__init__.py

@@ -64,17 +64,16 @@ def _ignore_pmg_warnings():
  warnings.filterwarnings("ignore", message="Use get_magnetic_symmetry()")
  warnings.filterwarnings("ignore", message="Use of properties is now deprecated")
 
- warnings.filterwarnings("ignore", message="get_vasp_input") # deprecation warning introduced
- # in pymatgen>2024.1.6, fixed in our PR: https://github.com/materialsproject/pymatgen/pull/3601
- # (now merged) -- delete later if pymatgen requirement is updated beyond this
-
  # avoid warning about selective_dynamics properties (can happen if user explicitly set "T T T" (or
  # otherwise) for the bulk):
  warnings.filterwarnings("ignore", message="Not all sites have property")
 
  # ignore warning about structure charge that appears when getting Vasprun.as_dict():
  warnings.filterwarnings("ignore", message="Structure charge")
 
+ # SpglibDataset warning introduced in v2.4.1
+ warnings.filterwarnings("ignore", message="dict interface")
+
 
 _ignore_pmg_warnings()