Experimental Discovery of New Ionic Conducting Materials

This project tackles the discovery of new materials for solid state batteries that will have higher energy densities and superior safety to current technologies. It is based on the design and discovery of new inorganic solids with unprecedented structures that will allow new mechanisms for fast ion motion in solids. Materials that allow the rapid motion of ions are essential for the new energy technologies needed to meet the challenge of net zero, such as batteries, fuel cells and electrolysers for green hydrogen. We recently discovered a new lithium solid electrolyte that changes previous understanding of how to design fast ion transport in solid state materials (Science 383, 739, 2024), and expand upon this new structure type through performance optimisation via substitution (Angew. Chem. Int. Ed., 63, e202409372, 2024). This project will explore the enormous range of possibilities for the synthesis of new lithium- and magnesium-ion conducting materials based on this discovery. It will combine synthetic solid-state chemistry, advanced structural analysis, and measurement of the conductivity and electrochemical properties of the new materials, enabling the successful candidate to develop a diverse experimental skillset. The student will participate in the selection of synthetic targets as part of a multidisciplinary team that combine artificial intelligence and computational methods with chemical understanding to design new materials – the process that led to our recent discovery, which the student will have the opportunity to participate in and improve.

The project is based in the Materials Innovation Factory (https://www.liverpool.ac.uk/materials-innovation-factory/) at the University of Liverpool, a state-of-the-art facility for the digital and automated design and discovery of materials. The project will make use of tools developed in the multi-disciplinary EPSRC Programme Grant: “Digital Navigation of Chemical Space for Function” and the Leverhulme Research Centre for Functional Materials Design, that seek to develop a new approach to materials design and discovery, exploiting machine learning and symbolic artificial intelligence, demonstrated by the realisation of new functional inorganic materials. Examples include the first tools to guarantee the correct prediction of a crystal structure (Nature 68, 619, 2023), and to learn the entirety of known crystalline inorganic materials and guide discovery (Nature Communications 12, 5561, 2021). We recently developed machine learning models based on the largest dataset of experimentally measured Li ion conductivities to yield an easy to use tool that assist experimenter decision in material target selection (npj Computational Materials 9, 9, 2023). You will also make use of the first tools that use explainable symbolic AI to explore chemical space (Angew. Chem. Int. Ed., 2024). You will thus gain understanding of how the artificial intelligence and computational methods developed in the team accelerate materials discovery, and be able to contribute to the development of these models, which are designed to incorporate human expertise.

As well as obtaining knowledge and experience in materials synthesis, crystallography and measurement techniques, the student will develop skills in teamwork and scientific communication, as computational and experimental researchers within the team work closely together. There are extensive opportunities to use synchrotron X-ray and neutron scattering facilities.

Applications are welcomed from students with a 2:1 or higher master’s degree or equivalent in Chemistry, Physics, or Materials Science, particularly those with some of the skills directly relevant to the project outlined above. Experience in structural characterisation of inorganic materials or electron microscopy is an advantage.

Applications from candidates meeting the eligibility requirements of the EPSRC are welcome – please refer to the EPSRC website http://www.epsrc.ac.uk/skills/students/help/eligibility/.

The studentship is open to Home, EU and international students, however, please be aware there is a limit on the number of international students we can appoint per year. Further the studentship does not cover international fees.

Please ensure you include the project title and reference number CCPR135 when applying.