The Computational Chemistry Group simulates chemical and biochemical reactions under consideration of environmental effects. We complement experiment and provide answers where experiment alone is not able to do so. We study enzymes, biological receptors, astrochemistry, materials science, and catalysis. Many of the projects make use of the QM/MM method, the combination of quantum mechanics (QM) and empirical force fields (MM).
We develop methods that allow us to investigate these kinds of problems in innovative ways. We use machine learning techniques to investigate chemical reactions and to optimize geometries. The program package is co-authored by us and we lead the development of the optimization library DL-FIND. Our group extends the capabilities of geometry optimization in systems with many thousand degrees of freedom and developed methods to calculate tunneling processes in large systems as well as the free-energy sampling technique umbrella integration.