Overview
In this project, you will establish new data‑driven approach for polymer-surfactant formulations using open-loop automated screening of structure, composition and flow. You will use a novel rheo‑dialysis platform and small-angle scattering to systematically explore in-use changes in environmental conditions, revealing how structure and mechanical responses in soft matter formulations build, adapt, and relax.
About this opportunity
Personal care products such as shampoo are complex materials that rely on careful and precise structuring of polymers and surfactants in solution to provide the needed material properties for the end user. Blends of polymers and surfactants can create products that have passable properties in controlled conditions, but the end-use conditions can include complex material changes through dilution, shear and environmental chemical changes. To understand these, we require new underpinning molecular design principles.
In this project, you will establish new data‑driven approach for polymer-surfactant formulation using open-loop automated screening of structure, composition and flow. You will have the opportunity to work with a novel rheo‑dialysis device, which is unique to our labs and allows the chemical environment to be altered while simultaneously measuring its flow properties. This approach will be used to systematically vary environmental conditions to emulate in‑use changes, revealing how structure and mechanical responses build, adapt, and relax. You will complement these experiments by structural characterisation and screening of industrially relevant formulations through small-angle X-ray scattering (SAXS). The data generated will be used to train and validate the application of machine learning techniques to link constituent molecular descriptors, their structure, and function. Through combining mechanical and structural characterisation with data driven approaches and industrial formulation principles you will devise new design rules that guide and inspire the future of personal care formulation.
This project will be supervised Dr Anders Aufderhorst-Roberts, Dr William Sharratt (both from the Department of Materials, Design and Manufacturing Engineering), Dr Courtney Thompson and Dr Nick Ainger (both from Unilever).
Dr Aufderhorst-Roberts will lead the project. His research group is focused on the use and development of experimental tools to characterise the dynamic and responsive behaviour of soft and biological materials under changing mechanical environments. His group is highly interdisciplinary, spanning soft matter, biophysics, biomaterials and instrumentation design. A major current focus of his lab is novel rheology techniques for materials characterisation, including the rheodialysis technique, which was invented and pioneered in his group. Dr Sharratt’s group focusses on developing structure-function relationships of designer soft and polymeric materials, with a particular emphasis on small-angle scattering. He has significant expertise in the self-assembly and interfacial behaviour of surfactant and polymer solutions and has active multinational projects in AI-augmented formulation. He will provide training in small-angle scattering and AI and machine learning approaches. The University supervisors are complemented by support industrial supervisors at Unilever (Thompson, Ainger) who have a combined 30 years of industrial formulation chemistry experience. They will provide training in industrial formulation and will support wider employability, including secondments at Unilever alongside technical training and system-specific insight.
This project is expected to start in October 2026 and is offered under the EPSRC Centre for Doctoral Training in Digital and Automated Materials Chemistry based in the Materials Innovation Factory at the University of Liverpool, the largest industry-academia colocation in UK physical science. The successful candidate will benefit from training in robotic, digital, chemical and physical thinking, which they will apply in their domain-specific research in materials design, discovery and processing. PhD training has been developed with 35 industrial partners and is designed to generate flexible, employable, enterprising researchers who can communicate across domains.
Further reading
Aufderhorst-Roberts et al, “The Rheodialysis Approach” Netzsch White Paper, 2026:
Rafique et al., Soft Matter, 2020,16, 7835-7844, https://doi.org/10.1039/D0SM00982B
Khodaparast et. al., JCIS, 2021, 582, 1116-1127, https://doi.org/10.1016/j.jcis.2020.08.002
Sharratt et. al., Gels, 2021, 7(2), 44; https://doi.org/10.3390/gels7020044