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https://github.com/killiansheriff/warrencowleyparameters

OVITO Python modifier to compute the Warren-Cowley parameters.

https://github.com/killiansheriff/warrencowleyparameters

Science Score: 36.0%

This score indicates how likely this project is to be science-related based on various indicators:

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    CITATION.cff file
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    .zenodo.json file
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    DOI references
    Found 2 DOI reference(s) in README
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    Academic publication links
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    Committers with academic emails
    1 of 2 committers (50.0%) from academic institutions
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    Scientific vocabulary similarity
    Low similarity (13.2%) to scientific vocabulary

Keywords

high-entropy-alloys materials-science order-parameters ovito python-modifiers warren-cowley
Last synced: 9 months ago · JSON representation

Repository

OVITO Python modifier to compute the Warren-Cowley parameters.

Basic Info
  • Host: GitHub
  • Owner: killiansheriff
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 1.24 MB
Statistics
  • Stars: 29
  • Watchers: 2
  • Forks: 9
  • Open Issues: 0
  • Releases: 8
Topics
high-entropy-alloys materials-science order-parameters ovito python-modifiers warren-cowley
Created almost 3 years ago · Last pushed about 1 year ago
Metadata Files
Readme Funding

README.md

WarrenCowleyParameters

PyPI Version PyPI Downloads tests

OVITO Python modifier to compute the Warren-Cowley parameters, defined as:

$$\alpha{ij}^m = 1-\frac{p{ij}^m}{c_j},$$

where $m$ denotes the $m$-th nearest-neighbor shell, $p{ij}^m$ is the average probability of finding a $j$-type atom around an $i$-type atom in the $m$-th shell, and $cj$ is the average concentration of $j$-type atom in the system. A negative $\alpha_{ij}^m$ suggests the tendency of $j$-type clustering in the $m$-th shell of an $i$-type atom, while a positive value means repulsion.

Utilisation

Here is an example of how to compute the 1st and 2nd nearest neighbor shell Warren-Cowley parameters of the fcc.dump dump file. Note that in the fcc crystal structure, the 1st nearest neighbor shell has 12 atoms, while the second one has 6 atoms.

```python from ovito.io import import_file import WarrenCowleyParameters as wc

pipeline = importfile("fcc.dump") mod = wc.WarrenCowleyParameters(nneigh=[0, 12, 18], onlyselected=False) pipeline.modifiers.append(mod) data = pipeline.compute()

wcforshells = data.attributes["Warren-Cowley parameters"] print(f"1NN Warren-Cowley parameters: \n {wcforshells[0]}") print(f"2NN Warren-Cowley parameters: \n {wcforshells[1]}")

Alternatively, can see it as a dictionarry

print(data.attributes["Warren-Cowley parameters by particle name"])

The per-particle Warren-Cowley parameter are accessible as well

print("Per-particle 1NN Warren-Cowley parameters:\n", data.particles["Warren-Cowley parameter (shell=1)"][...]) print("Per-particle 2NN Warren-Cowley parameters:\n", data.particles["Warren-Cowley parameter (shell=2)"][...])

` Example scripts can be found in theexamples/`` folder.

Installation

For a standalone Python package or Conda environment, please use: bash pip install --user WarrenCowleyParameters

For OVITO PRO built-in Python interpreter, please use: bash ovitos -m pip install --user WarrenCowleyParameters

If you want to install the lastest git commit, please replace WarrenCowleyParameters by git+https://github.com/killiansheriff/WarrenCowleyParameters.git.

Contact

If any questions, feel free to contact me (ksheriff at mit dot edu).

References & Citing

If you use this repository in your work, please cite:

@article{sheriffquantifying2024, title = {Quantifying chemical short-range order in metallic alloys}, doi = {10.1073/pnas.2322962121}, journaltitle = {Proceedings of the National Academy of Sciences}, author = {Sheriff, Killian and Cao, Yifan and Smidt, Tess and Freitas, Rodrigo}, date = {2024-06-18}, }

and

@article{sheriff2024chemicalmotif, title = {Chemical-motif characterization of short-range order with E(3)-equivariant graph neural networks}, DOI = {10.1038/s41524-024-01393-5}, journal = {npj Computational Materials}, author = {Sheriff, Killian and Cao, Yifan and Freitas, Rodrigo}, year = {2024}, month = sep, }

Owner

  • Name: Killian Sheriff
  • Login: killiansheriff
  • Kind: user
  • Location: Cambridge, MA
  • Company: MIT

@MIT DMSE Ph.D. Student | @McGillUPhysics graduate | Doing Materials Science + AI research to better understand high-entropy alloys.

GitHub Events

Total
  • Create event: 3
  • Issues event: 2
  • Release event: 5
  • Watch event: 9
  • Issue comment event: 7
  • Push event: 7
  • Pull request review event: 2
  • Pull request event: 2
  • Fork event: 3
Last Year
  • Create event: 3
  • Issues event: 2
  • Release event: 5
  • Watch event: 9
  • Issue comment event: 7
  • Push event: 7
  • Pull request review event: 2
  • Pull request event: 2
  • Fork event: 3

Committers

Last synced: over 1 year ago

All Time
  • Total Commits: 87
  • Total Committers: 2
  • Avg Commits per committer: 43.5
  • Development Distribution Score (DDS): 0.069
Past Year
  • Commits: 20
  • Committers: 1
  • Avg Commits per committer: 20.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Killian Sheriff k****f@m****u 81
Daniel Utt u****t@o****g 6
Committer Domains (Top 20 + Academic)
ovito.org: 1 mit.edu: 1

Issues and Pull Requests

Last synced: 12 months ago

All Time
  • Total issues: 2
  • Total pull requests: 2
  • Average time to close issues: 7 months
  • Average time to close pull requests: about 3 hours
  • Total issue authors: 2
  • Total pull request authors: 1
  • Average comments per issue: 4.0
  • Average comments per pull request: 0.5
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 1
  • Average time to close issues: about 2 hours
  • Average time to close pull requests: about 4 hours
  • Issue authors: 1
  • Pull request authors: 1
  • Average comments per issue: 3.0
  • Average comments per pull request: 1.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • lichao505917586 (1)
  • spriti523 (1)
Pull Request Authors
  • nnn911 (3)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 96 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 10
  • Total maintainers: 1
pypi.org: warrencowleyparameters

OVITO Python modifier to compute Warren-Cowley parameters.

  • Versions: 10
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 96 Last month
Rankings
Dependent packages count: 7.5%
Downloads: 15.5%
Average: 30.9%
Dependent repos count: 69.8%
Maintainers (1)
KillianSheriff
Last synced: 10 months ago

Dependencies

.github/workflows/black.yml actions
  • actions/checkout v2 composite
  • rickstaa/action-black v1 composite
pyproject.toml pypi
  • numpy >= 1.22
  • ovito >= 3.9.0.dev35
.github/workflows/publish.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v3 composite
  • pypa/gh-action-pypi-publish 27b31702a0e7fc50959f5ad993c78deac1bdfc29 composite
.github/workflows/python-tests.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v4 composite