Research in the Kulik group

The Kulik group develops advanced simulation methodology ranging from data-driven to computationally-demanding but very accurate quantum mechanical simulation for the advancement of understanding and design of materials, inorganic catalysts, and biological enzymes. Simulations provide researchers in the Kulik group unique insights into relationships between how structure (i.e., where the atoms and electrons are) informs function (i.e., what do we see at the macroscopic scale). These tools all underlie our advancement of new methods to design molecules atom-by-atom. We also advance and use novel computing architectures to make normally impossible to solve calculations tractable, providing some key insights into how electronic structure teaches us new design rules in large, complex systems such as enzymes. Keep up to date by:

Conceptual DFT for systematic modeling

Multi-scale quantum-mechanical/molecular-mechanical (QM/MM) and large-scale QM simulation provide valuable insight into enzyme mechanism and structure-property relationships. Analysis of the electron density afforded through these methods can enhance our understanding of how the enzyme environment modulates reactivity at the enzyme active site. From this perspective, tools from conceptual density functional theory to interrogate electron densities can provide added insight into enzyme function.

Predicting electronic structure with ANNs

Direct density functional theory (DFT) simulation is the critical bottleneck in high-throughput computational screening for inorganic materials and molecular transition metal complexes. These calculations are computationally costly and the calculated properties are sensitive to the exchange–correlation functional employed. Screening efforts for molecular inorganic systems are complicated by the uncertain spin-state ordering of hypothetical complexes and difficulty in obtaining good initial guess geometries.

Discovering chemistry from large databases

Using our recently developed inorganic discovery toolkit, molSimplify code, candidate molecules were obtained from the ChEMBL-19 database (> 1M molecules) to address a critical outstanding challenge in materials science. These databases of bioactive organic molecules are typically employed for discovery of therapeutic drug-like molecules; we instead demonstrated their power as a tool to discover design rules for inorganic complexes while maintaining realism (i.e., stable, synthetically accessible substituents) and providing diversity in functional groups.

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About Us

The Kulik group focuses on the development and application of new electronic structure methods and atomistic simulations tools in the broad area of catalysis.

Our Interests

We are interested in transition metal chemistry, with applications from biological systems (i.e. enzymes) to nonbiological applications in surface science and molecular catalysis.

Our Focus

A key focus of our group is to understand mechanistic features of complex catalysts and to facilitate and develop tools for computationally driven design.

Contact Us

Questions or comments? Let us know! Contact Dr. Kulik: