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Synergistic Cobalt/Enamine Catalysis Reaction Discovery and Optimization

Project Overview

This project employs a heuristic data-driven strategy to discovery an optimal catalytic system for the enamine-Co(IV) catalysis. Using an ML-driven optimization loop, we screened over 100,000 conditions and found the optimal condition in just 64 experiments. Furthermore, a clustering-based analysis facilitated a systematic assessment of substrate generality, confirming the broad applicability of the catalytic mode.

Table of Contents

Installation

To set up the environment and install the necessary dependencies, follow these steps:

  1. Create a new Conda environment with Python 3.10:

    conda create -n react_opt python=3.10 -y
  2. Activate the new environment:

    conda activate react_opt
  3. Install the dependencies from requirements.txt:

    pip install -r requirements.txt
  4. Some bug fix of summit package:change <CONDA_ENV_PATH>/lib/python3.10/site-packages/summit/benchmarks/experimental_emulator.py.

    • Comment out the _check_fit_params parameter imported on line 40
    • Comment out from sklearn.utils.fixes import delayed on line 43

Running

see more in demo.ipynb

Contributing

We welcome contributions from the community. Please fork the repository and submit pull requests.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

For any questions or inquiries, please contact us at tzz24@mails.tsinghua.edu.cn.

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AI guided new reaction discovery and optimization pipeline for synergistic cobalt enamine catalysis

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