Theoretical and Computational Chemistry; Reduced Scaling and Efficient Approaches; Computational Catalysis

The Lambrecht lab develops and applies novel computational approaches to describe “real chemistry” at the electronic structure level. Our main goals are (i) to push the boundaries of what is technically feasible to larger and more complex systems, thus allowing more realistic simulations, (ii) to gain a detailed understanding of chemistry at the electronic structure level, and (iii) to develop rationales for tailor-making molecular systems with specific chemical properties. A particular emphasis is placed on collaboration with experimental partners to devise novel catalysts and materials for energy applications.

Reduced-Scaling Approaches

We aim to enable calculations on larger systems than conventionally possible, which allows for more realistic chemical models. Examples developed in the lab are in the fields of Møller-Plesset perturbation theory to second order (MP2) and double hybrid density functional theory (DHDF), which are the cheapest methods that incorporate van-der-Waals interactions at an electronic structure level. While conventional implementations are typically limited to on the order of 100 atoms due to a computational scaling proportional to N⁵ (where N is the system size), we developed linear-scaling variants that extend the applicability to more than 1,000 atoms - the largest application so far being a 1,600 atom RNA ribozyme molecule. The scaling reduction is achieved by screening approaches exploiting the fact that some interactions between electrons (such as dispersion or vdW forces) are short-ranged and can therefore be neglected if the distance is big enough. Other approaches developed in the lab involve sparse matrix techniques, multi-scale approaches, as well as tensor decompositions.

Computational Catalysis

Chemical reactivity and catalysis are intimately linked to changes in the molecular electronic structure. It is therefore not surprising that electronic structure theory can make valuable contributions to the understanding of catalytic cycles and ultimately the rational design of improved catalysts. We develop electronic structure and embedding methods that yield an accurate and computationally feasible description of chemical reactions in solvent or solid environments. In cooperation with experiment we aim at gaining insights into the thermodynamics, kinetics and spectral signatures along catalytic pathways. Another focus is to provide rationales for the improvement of catalysts. Here we are working on decomposition methods that allow us to extract correlations between electronic structure descriptors for ligands and solvents and thus ultimately allow to make recommendations for more active catalyst systems.