Laurie Marlow
Project: Optimized Flow Pathways for Monodisperse Nanoparticles of Porous Materials
Supervisors: Anna Slater, Matt Rosseinsky, Kai Hoettges
Industry Partner: Baker Hughes
What inspired you to pursue this project and join the DAMC CDT?
Having completed my MChem with industrial research at the University of Liverpool in 2024, I developed a strong interest in porous materials chemistry that has only grown since entering industry. Working in chemical manufacturing with polymers and micronized silicas, I witnessed first-hand how downstream applications suffer from the non-uniform properties of polydisperse mixtures. Achieving a monodisperse size distribution demands both a deep understanding of the underlying chemistry and precise control of complex, interdependent parameters - a non-trivial challenge, particularly in batch processes at scale.
I chose this project because the work carries broad, far-reaching impact across some of the most pressing challenges in modern chemistry: gas separation, storage and purification, catalysis, sensing, pharmaceuticals, and beyond. Flow chemistry offers a compelling and practical route to achieving the kind of tight parameter control required for consistent particle size, while simultaneously addressing wider industrial concerns around energy efficiency, productivity, safety, sustainability, and process intensification. Combined with the advanced digital skills cultivated through the University of Liverpool's CDT DAMC, this project brings together exactly the capabilities needed to tackle such a formidable challenge.
What is your research project about, and what impact do you hope it will have?
My project uses flow chemistry to optimise the synthesis of porous nanoparticles toward a uniform size distribution. A reliable route to monodisperse nanoparticles would have far-reaching industrial impact: enabling accurate bulk characterisation of material properties; reducing pressure drop and channelling in packed-bed adsorption systems relevant to carbon capture; minimising material waste from sieving; improving process productivity; and ensuring more consistent adsorption and desorption kinetics in catalytic applications. Uniform particle size also reduces the risk of regulatory non-compliance in pharmaceutical manufacturing.
What has been the most exciting or rewarding part of your PhD journey so far and how does your project benefit from being part of an interdisciplinary CDT?
A highlight of my CDT experience was the AIChemy Robotics Winter School in December, which featured fascinating talks from academic and industry leaders applying optimisation algorithms, machine learning, and AI to chemistry and materials science. The standout moment came during the team project, where we applied a Bayesian optimisation algorithm to a hydrogen evolution reaction, with predictions rationalised by a connected large language model. Despite most of our team having limited prior experience, we placed second - which was an exciting result! The interdisciplinary nature of the CDT has opened the scope of chemistry to access tools and ideas which we would not otherwise have either in industry or during our undergraduate experience.