Reaction-network is a Python package for predicting and designing chemical reaction pathways in inorganic materials synthesis.
Project description
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/
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