The Chair of AI-based Materials Science is developing electronic structure and machine learning methods and applies them to pertinent problems in material science, surface science, physics, chemistry and the nano sciences.The electronic structure gives us an atomistic view on matter that is important for many applications.
Examples are materials for clean energy production, light-emitting devices (LEDs) or information and communication technologies (ICT). Perturbing the electronic structure, as done in spectroscopy, reveals more information about matter.
We develop and use theoretical spectroscopy methods to probe the properties of molecules, molecules on surfaces, nanostructures, as well as semiconductors and their surfaces. We also investigate data as new resource in materials science. We participate in the development of a large scale materials database and study the potential of database driven materials science.
