I use electronic structure methods and high performance computing to investigate the structural, optical and transport properties of new materials for energy generation and storage. I am particularly interested in building models that incorporate the effects of defects, disorder and heat.

 

My research interests is centred around materials used for renewable energy generation (e.g. solar cells) and storage (e.g. reusable batteries). I use Density Functional Theory (DFT) to predict the properties of these materials and link the macroscopic observables (such as open circuit voltage or thermodynamic stability) with microscopic processes (such as electron capture or electron-phonon coupling).

DFT is an ab-initio method derived from quantum mechanics and can be used to predict material properties without experimental input. The resulting atomic scale models can be used to guide experimental investigations - for example, to predict a new material with a particular target property.

When DFT is applied to crystalline materials it is usually assumed that there is perfect translational symmetry - that there are no defects (missing or extra atoms) - and that the atoms are perfectly static. However a real material always has defects, and the atomic lattice vibrates with heat. These defects and vibrations are important to understand because they can have a large impact upon the performance of a device. A large part of my research has focused on the modelling the defects and vibrations of hybrid halide perovskites, a family of materials that have become incredibly popular over the last decade as they can convert sunlight into electricity efficiently, and have the potential to form more flexible, lightweight and cheaper solar panels than those currently on the market.