rlmolecule
About
A library for general-purpose material and molecular optimization using AlphaZero-style reinforcement learning.
Code under development as part of the End-to-End Optimization for Battery Materials and Molecules by Combining Graph Neural Networks and Reinforcement Learning project at the National Renewable Energy Laboratory (NREL), Colorado School of Mines (CSU), and Colorado State University (CSU). Funding provided by the Advanced Research Projects Agency–Energy (ARPA-E)'s DIFFERENTIATE program.
For more information, see our publication:
S. V., S. S., Law, J. N., Tripp, C. E., Duplyakin, D., Skordilis, E., Biagioni, D., Paton, R. S., & St. John, P. C. (2022). Multi-objective goal-directed optimization of de novo stable organic radicals for aqueous redox flow batteries. Nature Machine Intelligence. 10.1038/s42256-022-00506-3
Installation
pip install rlmolecule
Running in AWS Ray clusters
Refer to the instructions available in: devtools/aws/README.md
1 maintainer
Metadata
1 maintainer
Release files for rlmolecule 0.0.10
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| rlmolecule-0.0.10.tar.gz | 272.2 kB | Without provenance | Details for rlmolecule-0.0.10.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| rlmolecule-0.0.10-py3-none-any.whl | Python 3 | none | any | Details for rlmolecule-0.0.10-py3-none-any.whl |
Total release size: 296.6 kB
Release files / rlmolecule-0.0.10.tar.gz
| Download URL | rlmolecule-0.0.10.tar.gz |
|---|---|
| Size | 272.2 kB |
| Tags | Source |
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Release files / rlmolecule-0.0.10-py3-none-any.whl
| Download URL | rlmolecule-0.0.10-py3-none-any.whl |
|---|---|
| Size | 24.4 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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twine/5.0.0 CPython/3.12.2
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