Digitally-led Discovery of Solid Electrolyte Materials for Net Zero Applications

Description

The discovery of new functional materials is essential to enable the transition to net zero. Given the size of chemical space, we need to harness digital tools to identify the best candidates for experimental synthesis, but computational prediction alone is insufficient – we need to experimentally realise and evaluate the materials. The student will use machine learning and crystal structure prediction to identify the compositions of candidate materials as new solid electrolytes for lithium and magnesium ion batteries, key technologies for the net zero transition. The student will then perform synthesis at these compositions in the laboratory and characterise the structures and properties of the materials discovered. Such a computational-experimental workflow was successfully used recently to identify a state-of-the-art lithium electrolyte with a unique structure [1], demonstrating the scope for the discovery of more transformative materials. The student will deploy existing tools and develop the combined computational-experimental workflow informed by the results generated in the project. The work will take place in a multidisciplinary team spanning computational chemistry, computer science, experimental materials synthesis, structural characterisation and property measurements.

This project will be supervised by Prof Matthew Rosseinsky and Dr Matthew Dyer (Dept. Chemistry). With the broad scope of skills available within the supervisory team, the project provides sufficient flexibility for students from a broad range of backgrounds to both grow their initial strengths and develop new capabilities – the most obvious candidates would be those with aptitude for experimental work and also numerical capability, but this is far from the only possible solutionThe project will allow the first real evaluation of the new symbolic AI tools for automated reasoning exploration of chemical space [2], developed by the supervisors with colleagues in CS, in practical workflows, providing further opportunity for students with a range of backgrounds to engage with the project and allowing the project to drive forwards Liverpool’s leadership in this space that remains fragile in the face of escalating and far better resourced competition across the world.

Informal enquiries on the project can be directed to M.S.Dyer@liverpool.ac.uk.

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 EPSRC Centre for Doctoral Training in Digital and Automated Materials Chemistry is therefore offering multiple studentships for students from backgrounds spanning the physical and computer sciences to start in October 2025. 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.

Applicant Eligibility

Candidates will have, or be due to obtain, a Master’s Degree or equivalent related to Physical Science, Engineering or Computational Science. Exceptional candidates with a First Class Bachelor’s Degree in an appropriate field will also be considered.

Application Process

Applicants are advised to apply as soon as possible no later than 17^th February 2025. The CDT will hold two rounds of applications assessment:

• Assessment Round 1: for all applications received between 11^th December 2024 – 15^th January 2025.
• Assessment Round 2: for all applications received between 16^th January 2025 – 17^th February 2025

Applicants who wish to be considered in Assessment Round 1 must apply by 15^th January 2025. Projects will be closed when suitable candidate has been identified (this could be before the 17th February 2025 deadline). 

Please review our guide on “How to Apply How to apply for a PhD | Postgraduate research | University of Liverpool carefully and complete the online postgraduate research application form to apply for this PhD project in Chemistry.

We strongly encourage candidates to get in touch with the supervisory team to get a better idea of the project.

We want all 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.

Please ensure you include the project title and reference number CCPR141 for example when applying.