CORDIS Project
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This project aims to create a fully autonomous method for optimizing organic catalysis reactions using a self-driving laboratory and advanced machine learning techniques. It seeks to enhance the efficiency of chemical research and development.
This proposal, AOGCNR, proposes to develop a fully autonomous, data-driven methodology for optimising general conditions for a novel organic catalysis reaction.
It integrates a self-driving laboratory (SDL) with a Large Language Model (LLM)-enhanced Bayesian Optimisation framework, combining cutting-edge robotics, machine learning and expert chemical reasoning. A two-phase approach is proposed.
The first phase uses a statistical pipeline to screen a vast chemical space of over 3 million combinat…
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