https://github.com/materialsproject/reaction-network

Reaction Network is a Python package for predicting likely inorganic chemical reaction pathways using graph theoretical methods. Project led by @mattmcdermott (Lawrence Berkeley National Lab).
https://github.com/materialsproject/reaction-network

chemistry materials-science python reaction-network reactions simulation

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Reaction Network is a Python package for predicting likely inorganic chemical reaction pathways using graph theoretical methods. Project led by @mattmcdermott (Lawrence Berkeley National Lab).

• Host: GitHub
• URL: https://github.com/materialsproject/reaction-network
• Owner: materialsproject
• License: other
• Created: 2019-07-12T15:03:27.000Z (over 5 years ago)
• Default Branch: main
• Last Pushed: 2024-03-08T21:26:37.000Z (8 months ago)
• Last Synced: 2024-05-19T14:05:21.332Z (6 months ago)
• Topics: chemistry, materials-science, python, reaction-network, reactions, simulation
• Language: Python
• Homepage: https://materialsproject.github.io/reaction-network/
• Size: 69.2 MB
• Stars: 76
• Watchers: 4
• Forks: 13
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Citation: CITATION.bib

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README

        
# ![Reaction Network](docs/_static/img/logo.png)

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Reaction Network (`rxn_network`) is a Python package for synthesis planning and predicting chemical reaction pathways in inorganic materials synthesis.

## Installation

We recommend installing using pip:

```properties

pip install -U reaction-network

```

The package will then be installed under the name `rxn_network`. The Materials Project

API is not installed by default; to install it, run: `pip install -U mp-api`.

> **Note**

> As of version 7.0 and beyond, the `reaction-network` package no longer uses `graph-tool`. All network functionality is now implemented using `rustworkx`. This means it is no longer required to complete any extra installations.

## Tutorials

The `examples` folder contains two (2) demonstration notebooks:

- **1_enumerators.ipynb**: how to enumerate reactions from a set of entries; running

  enumerators using jobflow

- **2_networks.ipynb**: how to build reaction networks from a list of enumerators and

  entries; how to perform pathfinding to recommend balanced reaction pathways; running

  reaction network analysis using jobflow

## Citation

If you use this code in your work, please consider citing the following paper (see

`CITATION.bib`):

> McDermott, M. J., Dwaraknath, S. S., and Persson, K. A. (2021). A graph-based network

> for predicting chemical reaction pathways in solid-state materials synthesis. Nature

> Communications, 12(1). 

## Acknowledgements

This work was supported as part of GENESIS: A Next Generation Synthesis Center, an

Energy Frontier Research Center funded by the U.S. Department of Energy, Office of

Science, Basic Energy Sciences under Award Number DE-SC0019212.

Learn more about the GENESIS EFRC here: