The AIchemy Frontier Fund has now been awarded, marking a significant milestone in the Hub’s vision to supporting and enable world leading research at the intersection of artificial intelligence and chemistry.
This highly competitive call attracted over 50 applications, requesting a combined £44.4M. With £2.5M available through the fund, this response demonstrates both the scale and ambition across the field and the increasing demand for funding in this area. Applications also involved 47 higher education institutes and industry partners, reflecting the breadth of collaboration across sectors.
A Rigorous and Multi-Stage Selection Process
To ensure the strongest alignment with the AIchemy mission, proposals underwent a structured three stage review process.
Initial eligibility screening was carried out by the AIchemy Hub Team, focusing on fundamental criteria such as costing and funding eligibility. Following this, the AIchemy Leadership Team assessed the remaining proposals for alignment with the Hub’s overarching mission: advancing the AI–chemistry interface through transformative research.
Proposals were then ranked, and a longlist of 15 applications was shared with an external review panel who scored and ranked the proposals based on the outlined criteria. From this stage, 7 projects were invited for interview in December, allowing for deeper evaluation of feasibility, impact, and interdisciplinary strength.
Applications were assessed against four key criteria:
- Quality and fit of the proposed research – including clarity of the research challenge, awareness of the state-of-the-art, and contribution to advancing AIchemy’s mission.
- Potential for impact – particularly in enabling new AI-driven advances in chemistry, including software, hardware, data access, industrial methods, and clear pathways beyond the funding period.
- Interdisciplinarity – ensuring research meaningfully spans both AI and chemistry domains.
- Ability to deliver – considering feasibility, resourcing, and the expertise of the project teams.
Funded Projects
Following this process, three projects were selected for funding. Each brings a distinct perspective on how AI can transform chemical research, discovery, and collaboration.
PDRA opportunities will be available across the funded projects.
Leveraging Ontological Knowledge with Argumentative Agentic AI to Accelerate Chemical Development
Professor Alexei Lapkin, University of Cambridge
Professor Francesca Toni, Imperial College London
Dr Antonio Rago, King’s College London
Project Summary
In this project we aim to demonstrate how relational databases can enhance AI workflows, focusing on an advanced argumentative agentic AI approach and a well-known and highly challenging problem of predictive scalability in chemical process development. Specifically, the project will aim to develop a human-in-the-loop AI framework for guiding multi-step process scale-up in the context of small molecule active pharmaceutical ingredients (APIs) manufacture.
Alignment of Generative AI for Materials Discovery via Experimental Feedback
Dr Shijing Sun, University of Cambridge
Professor Aron Walsh, Imperial College London
Project Summary
Our project addresses the challenge of bridging the simulation-to-real gaps in inorganic materials discovery directly. We propose an integrated, closed-loop platform that connects generative AI for crystals with high-throughput robotic synthesis and characterisation. We will deliver a processing-conditioned, disorder-aware generative model that is calibrated by small-batch experimental feedback. Our objective is to align generative models using real experimental outcomes for AI-driven discovery in which hypothesis generation, synthesis, and evaluation are all automated and connected.
Human-AI Teaming for Chemistry (HATCH)
Dr Jihong Zhu, University of York
Dr Gabriella Pizzuto, University of Liverpool
Professor Robert Gaizauskas, University of Sheffield
Professor Ian Fairlamb, University of York
Project Summary
A step-change in synthetic chemistry can only be realised through an intelligent and physical synergy between human chemists, AI coordinators, robotic platforms and chemistry equipment. This project aims to provide and validate such a framework, aiming to bridge the gap between today’s highly-equipped, specialist laboratories and the wider chemistry community, creating an accessible, truly collaborative laboratory of the future.
Looking Ahead
All projects are funded for two years, and updates will be shared on the AIchemy website as they progress. Over this period, we look forward to seeing how each team develops their ideas and advances the AI–chemistry interface in practice.
The scale of interest in this call makes one thing clear: there is a strong and growing demand for funding that supports ambitious, interdisciplinary work at the intersection of AI and chemistry.