Kulik Group

The Kulik group is focused on developing and applying accurate and efficient quantum mechanical methods to understand and design heterogeneous, molecular, and biological catalysts. A firm understanding of the fundamentals of catalysis is critical for tackling human health challenges and managing disease as well as addressing modern challenges in energy and efficient use of raw feedstocks. Through studying a wide range of catalysts - from enzymes to surface science - we aim to elucidate unifying principles that govern catalysis and provide a blueprint for catalyst design.

While quantum mechanical approaches are crucial for providing an atomic scale vision of catalysis, the accuracy and efficiency of available computational approaches has been a major obstacle to both designing catalysts and enhancing our understanding of catalytic mechanisms. We develop and employ accelerated quantum chemical techniques on graphical processing units (GPUs) that allow direct quantum mechanical simulation of systems thousands of atoms in size. A typical calculation carried out on CPUs that would normally take half a week now takes half an hour with these methods. We also have developed methods that allow us to carry out efficient, small basis set quantum chemistry with the accuracy afforded typically only with larger basis sets. In related work, we develop and employ Hubbard-augmented density functional approaches to achieve near-chemical accuracy in transition metal complexes.

Projects of key interest in the group are in (i) understanding long-range quantum effects in enzymes and developing approaches for large-scale QM mechanistic study of prototypical enzymes relevant to Parkinson's disease (ii) developing ab initio approaches to augment existing drug and inhibitor design techniques, (iii) rapid screening and design of molecular and molecular-motif catalysts for carbon capture and methane conversion, and (iv) developing approaches to tackle enzyme-complex-driven catalysis with QM/MM approaches and using these simulations as a basis for biomimetic design.