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Materials with enhanced ionic transport properties are important for the next generation of batteries and solid oxide fuel cells. Typically ordered materials are studied, however recent investigations (Science 343, 519 (2014)) highlight the promise of structurally disordered as in these ionic diffusion can be unusually high. An example is lithium lanthanum titanate ( or LLTO), which has a very high lithium diffusivity, however, its understanding is complicated by its crystal structure. Very recent investigations (Phys. Chem. Chem. Phys. DOI: 10.1039/C4CP04834B) revealed that the use of genetic algorithms in conjunction with atomistic simulation is an efficient way to deconvolute the complexity in these materials. The present doctoral thesis will be concerned with the systematic understanding of the atomic-scale features that result in high ionic conductivity and the application of these to discover further systems of industrial interest. Importantly, the doctoral student will be involved in the application of advanced computational techniques (including genetic algorithms and artificial intelligence) in a way that will accelerate the understanding and improvement of material properties.

Qualifications
Applicants should have or expect a good II(i) honours degree (or an equivalent degree) in Physics or related discipline.

Eligibility: Due to funding restriction this studentship is only available to UK/EU applicants

Further Information

Please submit a cover letter and CV with your application. The cover letter should describe your research interests and motivation for the proposed project in a short paragraph.

For more information and informal enquiries please contact Dr Alex Chroneos [email protected]

Funding Details

The Studentship will provide tuition fees and a tax-free stipend