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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 (formerly at Berkeley Lab).

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Reaction Network

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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:

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). https://doi.org/10.1038/s41467-021-23339-x

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: https://www.stonybrook.edu/genesis/