Research and Values of the Kulik group

We are an inclusive, creative, and collaborative group of people who work at the interface of computational chemistry, chemical engineering, and materials science for a wide range of applications from fundamental biochemistry to data-driven discovery of new molecules and materials. We prioritize learning - from each other and from the world around us - in our goal to advance the field and our own fundamental knowledge, while staying mindful of the impact we have on each other and society. The Kulik lab prioritizes the mental and physical health of its members as much as our quest to develop into world class scientists. Finally, we embrace very #random (but probably fairly uncool) jokes in our Slack channels. We are computational researchers after all!
 
Our home is in the Chemical Engineering department at MIT, and we are also members of the Center for Computational Science and Engineering and Computational Systems Biology (CSBi) program. Our group is excited to be a part of three multidisciplinary center efforts that bring together researchers across disciplines and universities: the Inorganometallic Catalyst Design Center (ICDC) EFRC, the Center for Enhanced Nanofluidic Transport (CENT) EFRC, and the Center for the Exascale Simulation of Material Interfaces in Extreme Environments (CESMIX) PSAAP-III.
 
Research in the Kulik group leverages computational modeling to aid the discovery of new materials and mechanisms. Our group uses first-principles modeling to unearth fundamental aspects of structure-property relationships in catalysts and materials. By taking a computational approach, we carry out studies that allow us to make connections across a wide range of catalytic systems from biological enzymes to emerging heterogeneous single-atom catalysts. We develop computational software and machine learning models that accelerate the discovery of new materials and design rules. This approach enables the prediction of new materials properties in seconds, the exploration of million-compound design spaces, and the identification of design rules and exceptions that go beyond intuition. To ensure the predictive power of our approach, our group develops new methods to increase the accuracy of density functional theory especially for materials with challenging electronic structure such as transition metal complexes and solids.

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Detecting strong correlation with ML

Despite its widespread use in chemical discovery, approximate density functional theory (DFT) is poorly suited to many targets, such as those containing open-shell, 3d transition metals that can be expected to have strong multi-reference (MR) character. For discovery workflows to be predictive, we need automated, low-cost methods that can distinguish the regions of chemical space where DFT should be applied from those where it should not.

Moving on up: 3d vs 4d TMCs in DFT

Density functional theory (DFT) is widely used in transition-metal chemistry, yet essential properties such as spin-state energetics in transition-metal complexes (TMCs) are well known to be sensitive to the choice of the exchange–correlation functional. Increasing the amount of exchange in a functional typically shifts the preferred ground state in first-row TMCs from low-spin to high-spin by penalizing delocalization error, but the effect on properties of second-row complexes is less well known.

RACs shed light on metal-organic frameworks

Millions of distinct metal-organic frameworks (MOFs) can be made by combining metal nodes and organic linkers. At present, over 90,000 MOFs have been synthesized and over 500,000 predicted. This raises the question whether a new experimental or predicted structure adds new information. For MOF chemists, the chemical design space is a combination of pore geometry, metal nodes, organic linkers, and functional groups, but at present we do not have a formalism to quantify optimal coverage of chemical design space.

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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: