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Biography

Dr Becky Greenaway MRSC is an associate professor (reader) and Royal Society University Research Fellow (URF) in the Department of Chemistry at Imperial College. She obtained her MChem in 2009 at the University of Sheffield and completed her DPhil in 2013 at the University of Oxford under the supervision of Professor Ed Anderson. She then worked with Prof. Andy Cooper FRS as a postdoctoral researcher at the University of Liverpool, before being awarded a URF in allowing her to establish an independent research career. In May 2020 she joined the Department of Chemistry at Imperial College, where she was then appointed as a lecturer in 2022 and promoted to senior lecturer in 2023 and then reader in 2025. 

She is the automation lead in the Institute for Digital Molecular Design and Fabrication (DigiFAB), Co-Director of the EPSRC Centre for Rapid Online Analysis of Reactions (ROAR), and co-investigator and on the management team for several other EPSRC Strategic Equipment Grants providing high-throughput automation facilities including ATLAS (Automated High-throughput Platform Suite) and DIGIBAT (energy materials acceleration platform for sustainable batteries and fuels). She is also a co-investigator for the UKRI AIchemy AI for Chemistry Hub, and a committee member on the RSC Porous Materials Interest Group.

Talent, facilities, and reputation will only take you so far – without a diverse, collaborative, and mutually supportive team, you simply cannot do the best science.

Dr Rebecca Greenaway

Q&A

Can you tell us more about your work?

My research has concentrated on developing high-throughput automated approaches that accelerate the discovery and synthesis of molecular organic materials assembled using dynamic covalent chemistries and supramolecular strategies. By also investigating the properties of these materials by studying their porosity, solubility, guest-host behaviour, and thermal and optical properties, I use the approach to target and develop non-conventional phases of porous organic materials, such as liquids and glasses, for applications in gas uptake and molecular separations. However, while the use of high-throughput automation can accelerate screening, this approach is inelegant and inefficient when applied blindly. Therefore, in close collaboration with computational groups, I am increasingly integrating computational modelling and machine learning approaches with these automated workflows to help guide the design and discovery process, preventing experimental efforts being wasted on unpromising materials.

What has been the most rewarding or memorable highlight of your career so far? 

I think one of the most memorable highlights of my career so far has been when we published the first examples of porous liquids – it got a lot of traction at the time, which was the first time some of my research had received media attention. It’s not often you get to realise a completely novel class of materials, and being instrumental in that discovery was very exciting!

What have been the biggest challenges that you have faced over the course of your time in science, and what have you learned from those experiences? 

One of my biggest personal challenges has been balancing real-life difficulties alongside building a research career, from losing loved ones unexpectedly and supporting seriously ill family members, to managing my own mental and physical health and realising my neurodivergence. While finding that balance isn't always easy, I believe these experiences have made me more empathetic and attuned as a group leader. I understand that life doesn't pause for science, and that shapes how I support the researchers in my group. I've also learned, sometimes the hard way, that asking for help can be daunting, but that colleagues and team members will often rally around in ways that genuinely surprise you.

Are there any scientific developments, either recent or on the horizon, that you are excited about? 

Chemical research automation is rapidly evolving, from what started as stand-alone and semi-automated workflows, towards more fully automated and autonomous approaches that accelerate discovery. Equally important is ensuring these advances aren't restricted to well-resourced labs. I'm genuinely excited about where this is heading, particularly the push towards 'Digital Lab Fairness' and standardised orchestration frameworks.

What does good research culture mean to you, and why does it matter? 

For me, good research culture spans several interconnected areas, including integrity and pride in our work, ambition and productivity without burn-out, and a genuine commitment to openness and collaboration. Talent, facilities, and reputation will only take you so far – without a diverse, collaborative, and mutually supportive team, you simply cannot do the best science.

How important would you say collaboration is for producing high quality science? How has collaboration influenced your work? 

Collaboration is, for me, one of the most important and enjoyable aspects of research. Working in isolation tends to narrow our thinking – we become blinkered to the broader branches our research could take, and the science is often poorer for it. Bringing together different expertise and perspectives is where the most exciting discoveries happen. As a group, most of our best publications involve at least one collaborator, and the majority of my researchers are either co-supervised or embedded in a collaborative project. A particular strength of our work is our long-term, productive relationships with both computational and experimental groups enabling us to apply automation where it has the greatest impact.