Advancing battery intelligence using digital parameterisation of battery electrode microstructures

Details

Batteries are a critical technology in achieving net zero, and will be crucial for the successful decarbonisation of a range of sectors from transport to energy storage. The next generation of batteries must be lighter, have higher energy densities, last longer and use less of the critical raw materials found in the technologies of today. This will require rapid innovations in materials design and electrode engineering to ensure this next generation of battery materials are well-suited to the ever increasing technological demands. Battery intelligence is a key pathway to achieving these urgently-needed innovations.

This project will tackle the urgent need for novel battery intelligence tools that can analyse large multidimensional datasets, to extract meaningful, statistical information about battery microstructure evolution and degradation. By combining the use of state-of-the-art testing facilities within the Sheffield Tomography Centre, coupled with the advanced algorithms for data processing, rapid analysis on battery materials can be done.

This project will be carried out in close collaboration with the industrial partner, Elysia Battery Intelligence by Fortescue WAE, who have significant expertise in cloud-based analysis of battery systems. By harnessing the existing decades of expertise at Elysia, the student will benefit from interaction with a leading company in the field and the project will help solve truly relevant industrial challenges. The successful student will join the new CDT in Materials 4.0 - a national effort to rapidly accelerate the discovery and development of materials. The student will benefit from a tailored training programme, with multiple opportunities to present high-impact work at conferences, and receive training in digital skills, leadership and outreach.

You will be supervised by Dr Jennifer Hack and Professor Beverley Inkson at the University of Sheffield, along with support from an industrial supervisor at Fortescue WAE/Elysia Battery Intelligence, and will benefit from the significant expertise, lab facilities, technical support and mentorship from the supervisory team. The supervisory team is committed to creating an inclusive, positive research culture within their groups, and candidates from traditionally underrepresented STEM backgrounds are encouraged to apply. The project would be well suited to a candidate from any STEM background with a keen interest in battery technologies, and prior modelling experience would be beneficial, but not a necessary requirement. 

Interested candidates are encouraged to contact the primary supervisor, Dr Jennifer Hack ([email protected]) to discuss the project. 

Applications can be made using the information on this page: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying.

Please indicate that you are applying for this advertised post.