Research plans

My PhD within subproject P09 of the TACO SFB will revolve around structure prediction of oxide surfaces, using machine-learning methods and density functional theory. A vital goal during the early stages is the improved treatment of long-range interactions in a neural-network potential that will serve as a tool for accelerating calculations at first-principles accuracy. Another project will be to scrutinize the surface reconstructions of Fe₂O₃, in cooperation with the group of Gareth Parkinson (P04), using evolutionary algorithms. In more general terms, I enjoy the idea that, through applications in catalysis, my work may help alleviate some of the pressing energy-related issues the world is facing, and of furthering my skills in machine learning and coding along the way.