Reaction Network (rxn_network) is a Python package for predicting likely inorganic chemical reaction pathways using combinatorial and graph theoretical methods.

Installation directions

We recommend installing using pip:

pip install reaction-network

The package will then be installed under the name rxn_network.

As of version 7.0, 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.

Tutorial notebooks

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_network.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 or Python package in your work, please consider citing the following paper:

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/