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.
 
Interested to learn more about our group's research? Check out these recent presentations on YouTube:
 
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.

Keep up to date by:

Chem. Rev. on ML for transition metals is out!

Transition-metal complexes are attractive targets for the design of catalysts and functional materials. The behavior of the metal–organic bond, while very tunable for achieving target properties, is challenging to predict and necessitates searching a wide and complex space to identify needles in haystacks for target applications. This review will focus on the techniques that make high-throughput search of transition-metal chemical space feasible for the discovery of complexes with desirable properties.

Electronic allostery in protein dynamics

The delicate interplay of covalent and noncovalent interactions in proteins is inherently quantum mechanical and highly dynamic in nature. To directly interrogate the evolving nature of the electronic structure of proteins, we carry out 100-ps-scale ab initio molecular dynamics simulations of three representative small proteins with range-separated hybrid density functional theory. We quantify the nature and length-scale of the coupling of residue-specific charge probability distributions in these proteins.

What's needed for intelligent workflows?

Accelerated discovery with machine learning (ML) has begun to provide the advances in efficiency needed to overcome the combinatorial challenge of computational materials design. Nevertheless, ML-accelerated discovery both inherits the biases of training data derived from density functional theory (DFT) and leads to many attempted calculations that are doomed to fail. Many compelling functional materials and catalytic processes involve strained chemical bonds, open-shell radicals and diradicals, or metal–organic bonds to open-shell transition-metal centers.

Pages

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: