https://github.com/pyiron/pyiron_dpd
Automated Defect Phase Diagrams and Workflow Prototypes
https://github.com/pyiron/pyiron_dpd
python
Last synced: 3 months ago
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Automated Defect Phase Diagrams and Workflow Prototypes
- Host: GitHub
- URL: https://github.com/pyiron/pyiron_dpd
- Owner: pyiron
- Created: 2023-05-11T12:44:41.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2025-06-09T19:40:01.000Z (about 1 year ago)
- Last Synced: 2025-06-09T20:31:25.264Z (about 1 year ago)
- Topics: python
- Language: Jupyter Notebook
- Homepage:
- Size: 766 KB
- Stars: 0
- Watchers: 2
- Forks: 1
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.rst
- Code of conduct: CODE_OF_CONDUCT.md
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README
# pyiron_dpd - Tools for Defect Phase Diagrams
This repository contains tools and workflows to automatically calculate Defect Phase Diagrams (DPDs) for arbitrary crystalline defects in binary systems.
DPDs show which ordered phase is the most stable segregation pattern at a defect given a certain thermodynamic state variables. This implementation supports DPDs in $\Delta\mu$ and $\Delta\mu-T$ space. Here we understand $\Delta\mu = \mu_2 - \mu_1$ as the difference in the chemical potential of both binary species, i.e. we work in the semi-grandcanonical ensemble.
The two major workflows are `SegregationFlow` and `IterativeSegregation`. Examples are given in the `notebooks` folder. The former exhaustively enumerates all possible segregation patterns up to a configurable number of solutes. The latter has added methods to screen a large number of segregation patterns with an on-the-fly fitted proxy model before deciding which patterns are worth explicitely calculating. Both approaches reduce the number of calculations necessary by taking symmetry into account.
# License
The software is provided here for reference only with all rights reserved. You may **not** copy it without permission. If you are interested in using this code or expanding it, please contact us first. We will likely open source this in the future.
# Installation
Manual installations:
1. the latest `HEAD` of
[python-ace](https://github.com/ICAMS/python-ace/tree/master) (the PyPI
version is not sufficient)
2. a `lammps` binary, either your own or via `conda -c conda-forge lammps`
All other dependencies can be installed by
```
pip install .
```
from the repository root or with the conda environment in
`.ci_support/environment.yml`.
# Example DPDs
Below are the DPDs generated by the example notebooks for a grain boundary and a vacancy in fcc Cu decorated with Ag.
## Cu/Ag $\Sigma 5$ [001] GB
## Cu/Ag Vacancy in Cu host
# Caveat
This repository also contains prototypes of various workflow ideas and utility functions. Do not rely on them in derived work. They will change, be removed or eventually be subsumed into other pyiron packages.