https://github.com/chiang-yuan/muse

A python package for fast building amorphous solids and liquid mixtures from @materialsproject computed structures and machine learning interatomic potentials
https://github.com/chiang-yuan/muse

atomistic-simulations high-throughput interatomic-potentials machine-learning materials molecular-dynamics

Last synced: 4 days ago
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A python package for fast building amorphous solids and liquid mixtures from @materialsproject computed structures and machine learning interatomic potentials

• Host: GitHub
• URL: https://github.com/chiang-yuan/muse
• Owner: chiang-yuan
• License: mit
• Created: 2023-07-29T00:36:06.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-11-27T00:21:07.000Z (26 days ago)
• Last Synced: 2024-11-27T01:20:57.964Z (26 days ago)
• Topics: atomistic-simulations, high-throughput, interatomic-potentials, machine-learning, materials, molecular-dynamics
• Language: Python
• Homepage: https://chiang-yuan.github.io/muse/
• Size: 2.19 MB
• Stars: 4
• Watchers: 1
• Forks: 0
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Citation: CITATION.cff

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README

        
# Muse

Muse is a python package for fast building amorphous solids and liquid mixtures based on relaxed solid-state structures on [Materials Project](https://materialsproject.org/) using [Packmol](http://m3g.iqm.unicamp.br/packmol/home.shtml) and machine learning interatomic potentials/force fields (MLIPs/MLFFs), especially universal interatomic potentials (UIPs) such as MACE and CHGNet.

## Usage

### Building the book

If you'd like to develop and/or build the muse book, you should:

1. Clone this repository

2. Run `pip install -r requirements.txt` (it is recommended you do this within a virtual environment)

3. (Optional) Edit the books source files located in the `docs/` directory

4. Run `jupyter-book clean docs/` to remove any existing builds

5. Run `jupyter-book build docs/`

A fully-rendered HTML version of the book will be built in `docs/_build/html/`.

### Hosting the book

Please see the [Jupyter Book documentation](https://jupyterbook.org/publish/web.html) to discover options for deploying a book online using services such as GitHub, GitLab, or Netlify.

For GitHub and GitLab deployment specifically, the [cookiecutter-jupyter-book](https://github.com/executablebooks/cookiecutter-jupyter-book) includes templates for, and information about, optional continuous integration (CI) workflow files to help easily and automatically deploy books online with GitHub or GitLab. For example, if you chose `github` for the `include_ci` cookiecutter option, your book template was created with a GitHub actions workflow file that, once pushed to GitHub, automatically renders and pushes your book to the `gh-pages` branch of your repo and hosts it on GitHub Pages when a push or pull request is made to the main branch.

## Contributors

We welcome and recognize all contributions. You can see a list of current contributors in the [contributors tab](https://github.com/chiang-yuan/docs/graphs/contributors).

## Credits

This project is created using the excellent open source [Jupyter Book project](https://jupyterbook.org/) and the [executablebooks/cookiecutter-jupyter-book template](https://github.com/executablebooks/cookiecutter-jupyter-book).