Rapid computational screening of materials for energy storage

This PhD project will use materials informatics - a combination of computer science and materials science - to develop software for the rapid screening and identification of new chemical spaces for energy storage. The project will be focused on the substitution of existing components that are formed of non-toxic or rare elements, e.g. LiCoO2 cathodes in high-density Li-ion batteries. Critical to this will be metrics relating to materials sustainability, including element abundance, production rates, as well as geopolitical factors. The research will combine elements of first-principles simulations (density functional theory), combined with chemical filters developed through statistical analysis (machine learning).