https://github.com/mturiansky/nonrad
Implementation for computing nonradiative recombination rates in semiconductors
Science Score: 23.0%
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Low similarity (17.7%) to scientific vocabulary
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Repository
Implementation for computing nonradiative recombination rates in semiconductors
Basic Info
- Host: GitHub
- Owner: mturiansky
- License: mit
- Language: Python
- Default Branch: master
- Homepage: https://nonrad.readthedocs.io/en/latest/
- Size: 3.22 MB
Statistics
- Stars: 48
- Watchers: 3
- Forks: 22
- Open Issues: 1
- Releases: 7
Topics
Metadata Files
README.md
NONRAD
An implementation of the methodology pioneered by Alkauskas et al. for computing nonradiative recombination rates from first principles. The code includes various utilities for processing first principles calculations and preparing the input for computing capture coefficients. More details on the implementation of the code can be found in our recent paper. Documentation for the code is hosted on Read the Docs.
Installation
NONRAD is implemented in python and can be installed through pip.
Dependencies are kept to a minimum and include standard packages such as numpy, scipy, and pymatgen.
With pip
As always with python, it is highly recommended to use a virtual environment.
To install NONRAD, issue the following command,
$ pip install nonrad
or to install directly from github,
$ pip install git+https://github.com/mturiansky/nonrad
Going Fast (Recommended)
NONRAD can use numba to accelerate certain calculations.
If numba is already installed, it will be used;
otherwise, it can be installed by specifying [fast] during installation with pip, e.g.
$ pip install nonrad[fast]
For Development
To install NONRAD for development purposes, clone the repository
$ git clone https://github.com/mturiansky/nonrad && cd nonrad
then install the package in editable mode with development dependencies
$ pip install -e .[dev]
pytest is used for unittesting.
To run the unittests, issue the command pytest nonrad from the base directory.
Unittests should run correctly with and without numba installed.
Usage
A tutorial notebook that describes the various steps is available here. The basic steps are summarized below:
- Perform a first-principles calculation of the target defect system. A good explanation of the methodology can be found in this Review of Modern Physics. A high quality calculation is necessary as input for the nonradiative capture rate as the resulting values can differ by orders of magnitude depending on the input values.
- Calculate the potential energy surfaces for the configuration coordinate diagram. This is facilitated using the
get_cc_structuresfunction. Extract the relevant parameters from the configuration coordinate diagram, aided byget_dQ,get_PES_from_vaspruns, andget_omega_from_PES. - Calculate the electron-phonon coupling matrix elements, using the method of your choice (see our paper for details on this calculation with
VASP). Extraction of the matrix elements are facilitated by theget_Wif_from_wavecarsor theget_Wif_from_WSWQfunction. - Calculate scaling coefficients using
sommerfeld_parameterand/orcharged_supercell_scaling. - Perform the calculation of the nonradiative capture coefficient using
get_C.
Contributing
To contribute, see the above section on installing for development. Contributions are welcome and any potential change or improvement should be submitted as a pull request on Github. Potential contribution areas are: - [ ] implement a command line interface - [ ] add more robust tests for various functions
How to Cite
If you use our code to calculate nonradiative capture rates, please consider citing
@article{alkauskas_first-principles_2014,
title = {First-principles theory of nonradiative carrier capture via multiphonon emission},
volume = {90},
doi = {10.1103/PhysRevB.90.075202},
number = {7},
journal = {Phys. Rev. B},
author = {Alkauskas, Audrius and Yan, Qimin and Van de Walle, Chris G.},
month = aug,
year = {2014},
pages = {075202},
}
and
@article{turiansky_nonrad_2021,
title = {Nonrad: {Computing} nonradiative capture coefficients from first principles},
volume = {267},
doi = {10.1016/j.cpc.2021.108056},
journal = {Comput. Phys. Commun.},
author = {Turiansky, Mark E. and Alkauskas, Audrius and Engel, Manuel and Kresse, Georg and Wickramaratne, Darshana and Shen, Jimmy-Xuan and Dreyer, Cyrus E. and Van de Walle, Chris G.},
month = oct,
year = {2021},
pages = {108056},
}
If you use the functionality for the Sommerfeld parameter in 2 and 1 dimensions, then please cite
@article{turiansky_dimensionality_2024,
title = {Dimensionality Effects on Trap-Assisted Recombination: The {{Sommerfeld}} Parameter},
shorttitle = {Dimensionality Effects on Trap-Assisted Recombination},
author = {Turiansky, Mark E and Alkauskas, Audrius and Van De Walle, Chris G},
year = {2024},
month = may,
journal = {J. Phys.: Condens. Matter},
volume = {36},
number = {19},
pages = {195902},
doi = {10.1088/1361-648X/ad2588},
}
Owner
- Name: Mark Turiansky
- Login: mturiansky
- Kind: user
- Repositories: 6
- Profile: https://github.com/mturiansky
Physics Graduate Student at UCSB
GitHub Events
Total
- Issues event: 3
- Watch event: 7
- Issue comment event: 13
Last Year
- Issues event: 3
- Watch event: 7
- Issue comment event: 13
Committers
Last synced: almost 3 years ago
All Time
- Total Commits: 97
- Total Committers: 2
- Avg Commits per committer: 48.5
- Development Distribution Score (DDS): 0.01
Top Committers
| Name | Commits | |
|---|---|---|
| Mark Turiansky | m****y@g****m | 96 |
| Seán Kavanagh | 5****e@u****m | 1 |
Issues and Pull Requests
Last synced: 8 months ago
All Time
- Total issues: 5
- Total pull requests: 2
- Average time to close issues: 7 days
- Average time to close pull requests: about 4 hours
- Total issue authors: 5
- Total pull request authors: 2
- Average comments per issue: 4.2
- Average comments per pull request: 1.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 1
- Pull requests: 1
- Average time to close issues: 3 days
- Average time to close pull requests: N/A
- Issue authors: 1
- Pull request authors: 1
- Average comments per issue: 1.0
- Average comments per pull request: 1.0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- msehabibur (1)
- Arindamsannyal (1)
- yuan-gist (1)
- iamcqlin (1)
- Foresttrek (1)
- wangd11 (1)
Pull Request Authors
- Shibu778 (2)
- kavanase (1)
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Packages
- Total packages: 1
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Total downloads:
- pypi 72 last-month
- Total dependent packages: 1
- Total dependent repositories: 1
- Total versions: 7
- Total maintainers: 1
pypi.org: nonrad
Implementation for computing nonradiative recombination rates in semiconductors
- Documentation: https://nonrad.readthedocs.io
- License: MIT
-
Latest release: 1.2.0
published almost 2 years ago
Rankings
Maintainers (1)
Dependencies
- monty *
- numba >=v0.50.1
- numpy *
- pymatgen >=v2020.6.8
- scipy *