Digital chemistry discovery Faraday Discussion

Welcome

Join us in Edinburgh in September 2027 for this edition of the Faraday Discussion series, unique international discussion meetings that address current and emerging topics at the forefront of the chemical sciences.

This Discussion, the second Discussion on the topic of digital chemistry, aims to address the pressing challenges and opportunities in digital chemical discovery, across both computation and experimentation, from machine learning to chemical automation and robotics.

We encourage the involvement of scientists from across the chemical sciences to explore how their expertise can advance the integration of modelling, synthesis, automation and characterisation. Recent progress in autonomous experimentation, faster and more efficient simulation methods, generative approaches for molecular and materials design, and cutting‑edge optimisation strategies is already reshaping areas from drug discovery to materials design. This Discussion will be relevant to computational chemists, synthetic and materials chemists, automation and robotics specialists, chemical engineers, catalysis researchers, and those working in optimisation, machine learning and autonomous laboratory systems.

This Faraday Discussion presents a unique platform to share the latest advances, critically evaluate emerging methodologies and address both the promise and the challenges of applying AI‑driven and automation tools in chemical research. It is an unmissable chance to share new ideas, reconnect with colleagues and spark collaborations that will help define the future of digital chemical discovery.

On behalf of the organising committee, we look forward to welcoming you to Edinburgh.

Kim Jelfs and Keith Butler (Co-chairs)

Why attend?

Find out more about Faraday Discussions in the video and FAQs – see Useful links on the right.

A unique conference format that prioritises discussion

At a Faraday Discussion, the primary research papers written by the speakers are distributed to all participants before the meeting – ensuring that most of the meeting is devoted to discussing the latest research.

This provides a genuinely collaborative environment, where discussion and debate are at the foreground. All delegates, not just speakers, are invited to make comments, ask questions, or present complementary or contradictory measurements and calculations.

An exciting programme of talks – and more

Take part in a well-balanced mix of talks, discussion, poster sessions and informal networking, delivered by our expert events team. You can explore the full programme in the downloadable files on the right – whether you’re attending in-person or online, every minute provides an opportunity.

The conference dinner, included in the registration fee, contains the Marlow Cup ceremony: a unique commemoration of past Faraday Discussion organisers that is sure to encourage further discussions over dinner.

In-depth discussion with leaders in the field

World-leading and established researchers connect with each other and early-career scientists and postgraduate students to discuss the latest research and drive science forwards. It’s a unique atmosphere – and challenging others to get to the heart of the problem is encouraged!

Your contributions, published and citable

A citable record of the discussion is published in the Faraday Discussions journal, alongside the research papers. Questions, comments and remarks become a valuable part of the published scientific conversation, and every delegate can make a major contribution.

Discover Edinburgh

The Discussion will take place in Edinburgh. Step out to explore the city while you're here - or stay a few extra days to explore the city further and the surrounding area.

Themes

Automation and robotics in chemistry

Automation in chemistry is advancing through robotics, optimisation algorithms, and LLM-based agents, accelerating synthesis and characterisation while addressing bottlenecks and enabling adaptive, intelligent lab workflows.

Simulation acceleration

Machine learning is bridging accuracy-size trade-offs in molecular simulation, enabling quantum-level precision, improved sampling, and efficient approximations. Key remaining challenges for scalable, reliable applications will be discussed.

Generative AI

Generative AI is transforming drug and materials design by creating novel chemistries beyond traditional methods. This session will discuss GenAI's potential but also explore key issues of this new technology.

Accelerated optimisation

Chemical optimisation spans vast, multi-objective search spaces. Approaches from design of experiments to Bayesian and machine learning algorithms can accelerate discovery while addressing uncertainty, interpretability, and multi-fidelity challenges.