CyRxnOpt
Numerous cutting-edge machine learning algorithms have been developed in recent years for efficiently optimizing chemical processes. While many are open-source, evaluating and applying them to chemical processes remains challenging due to varying, non-standard implementations and interfaces. CyRxnOpt has been developed as a general, Python-based interface to install, use, and switch between reaction optimization algorithms under a single software interface. By integrating optimizers with the CyRxnOpt interface, many state-of-the-art reaction optimization algorithms can be more easily used in other software and workflows.
Resource information
- Format
- gz, zip
- Original repository
- 23019500
- DOI
- 10.5281/zenodo.23019500
- Credit basis
- Creators in Zenodo record metadata
- Access
- Open files available from the original Zenodo deposit
- Last checked
- Nov 5, 2026
- License
- Not specified
- Last record update
- Nov 5, 2026
About this resource
Numerous cutting-edge machine learning algorithms have been developed in recent years for efficiently optimizing chemical processes. While many are open-source, evaluating and applying them to chemical processes remains challenging due to varying, non-standard implementations and interfaces. CyRxnOpt has been developed as a general, Python-based interface to install, use, and switch between reaction optimization algorithms under a single software interface. By integrating optimizers with the CyRxnOpt interface, many state-of-the-art reaction optimization algorithms can be more easily used in other software and workflows.