Project description
Efficient, autonomous identification of the best reaction conditions
Discovering optimal conditions for new chemical reactions traditionally relies on slow, costly trial-and-error experimentation across a vast chemical space. With the support of the Marie Skłodowska-Curie Actions programme, the AOGCNR project aims to transform this process by integrating two powerful techniques. ‘Self-driving laboratories’ are autonomous research systems integrating AI, robotics and automated instrumentation. Large language model-enhanced Bayesian optimisation efficiently finds the best solution to complex and poorly defined problems. With these tools, AOGCNR aims to reduce over three million possible combinations in a vast chemical space by 97 % and then autonomously identify reaction conditions that perform well across multiple substrates – a significant advance over single-substrate approaches.
Objective
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 combinations, reducing it by over 97% to a manageable subspace. The second phase deploys the LLM-enhanced Bayesian Optimisation algorithm within this refined space to autonomously identify general reaction conditions that perform well across multiple substrates. This approach represents a significant advancement over current methods, which typically focus on single-substrate optimisation. The methodology will be validated on both a known reaction and a novel cyclisation discovered by researchers at the University of Liverpool, demonstrating its ability to accelerate the discovery of novel catalytic reactions.
This project's impact is significant on multiple levels. It advances chemical research by enabling data-efficient exploration of complex reaction spaces. Societally, it democratises access to advanced chemistry tools. Economically, this approach offers a scalable and cost-effective alternative to traditional trial-and-error methods, streamlining industrial research and development, and contributing to more sustainable and efficient innovation.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences chemical sciences catalysis
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering robotics
- natural sciences computer and information sciences artificial intelligence machine learning
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2025-PF
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
L69 7ZX LIVERPOOL
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.