Our research interests range from small molecules to large, condensed phase systems, and from methods development to applications (i.e., drug or materials discovery and design).
One particular area of emphasis is the accurate and efficient calculation of intermolecular interactions, which is a challenging problem for electronic structure theory. Tuning intermolecular interactions in drug binding and organic molecular materials is a key step in controlling the efficacy of drug molecules and function of molecular materials. In many cases, it is prohibitively expensive to investigate large numbers of potential molecules and structures experimentally. For other cases, an analysis of atomistic details of interest helps interpret ambiguous experimental data or resolve dissimilar models. Our research goal is to develop fast and accurate approaches for gaining a fundamental understanding of the factors governing the drug binding and molecular materials packing in order to provide a basis for the development of new drug molecules and functionalized molecular materials. Furthermore, adapting the methodology we are going to develop to the rapid evolution of machine-learning techniques offers a unique opportunity to generate new noncovalent molecular electronics and drug molecules through large-scale computational screening and design since the combination of different strategies to functionalize molecules is seemingly infinite.
Our group primarily works with a quantum chemistry software program called Q-Chem, to which we contribute new methods and algorithms.