Development of bespoke algorithms for autonomous optimisation in flow

Description

A key challenge in materials science is how to efficiently and sustainably arrive at the optimal conditions for material production. Flow chemistry’s unique control, spatio-temporal resolution, wide process windows and efficient heat/mass transport enables the selective, high-yielding, and scalable production of a wide range of molecules and, more recently, materials [1]. Algorithms have been used to autonomously optimise chemical processes, e.g., well-understood two-step reactions in flow. The production of materials offers complex optimisation problems, but it is difficult to know which approach (e.g. SNOBFIT, Bayesian optimisation, TSEMO) will perform best, even for simple problems. Thus, there is a need to develop bespoke optimisation algorithms for this application. In this PhD, design-of-experiments will be compared with self-optimising methods in terms of experimental efficiency for a range of organic materials under investigation in the Slater group. Algorithm choice and iterative development will be carried out to optimise the efficiency at which a) cost, product yield, and sustainability are optimised and b) a process model is generated.

The global need for researchers with capabilities in materials chemistry, digital intelligence and automation is intensifying because of the growing challenge posed by Net Zero and the need for high-performance materials across multiple sectors. The disruptive nature of recent advances in artificial intelligence (AI), robotics, and emerging quantum computing offers timely and exciting opportunities for PhD graduates with these skills to make a transformative impact on both R&D and society more broadly.

The University of Liverpool is therefore offering multiple studentships for students from backgrounds spanning the physical and computer sciences to start in October 2024. These students will develop core expertise in robotic, digital, chemical and physical thinking, which they will apply in their domain-specific research in materials design, discovery and processing. By working with each other and benefiting from a tailored training programme they will become both leaders and fully participating team players, aware of the best practices in inclusive and diverse R&D environments.

This training is based on our decade-long development of shared language and student supervision between the physical, engineering and computer sciences, and takes place in the Materials Innovation Factory (MIF), the largest industry-academia colocation in UK physical science. The training content has been co-developed with 35 industrial partners and is designed to generate flexible, employable, enterprising researchers who can communicate across domains. Applicants are advised to apply as soon as possible with applications considered when received and no later than 30/06/2024.

Please apply by completing the online postgraduate research application form:

How to apply for a PhD programme

Please ensure you include the project title and reference number CCPR114 when applying.

We want all of our staff and Students to feel that Liverpool is an inclusive and welcoming environment that actively celebrates and encourages diversity. We are committed to working with students to make all reasonable project adaptations including supporting those with caring responsibilities, disabilities or other personal circumstances. For example, If you have a disability you may be entitled to a Disabled Students Allowance on top of your studentship to help cover the costs of any additional support that a person studying for a doctorate might need as a result.