Sampling and QM region are equally important

Quantum-mechanical/molecular-mechanical (QM/MM) methods are essential to the study of metalloproteins, but the relative importance of sampling and degree of QM treatment in achieving quantitative predictions is poorly understood. We study the relative magnitude of configurational and QM-region sensitivity of energetic and electronic properties in a representative Zn2+ metal binding site of a DNA methyltransferase. To quantify property variations, we analyze snapshots extracted from 250 ns of molecular dynamics simulation.

Predicting experimental spin states with an ANN

Determination of ground-state spins of open-shell transition metal complexes is critical to understanding catalytic and materials properties but also challenging with approximate electronic structure methods. As an alternative approach, we demonstrate how structure alone can be used to guide assignment of ground-state spin from experimentally determined crystal structures of transition metal complexes. We first identify the limits of distance-based heuristics from distributions of metal–ligand bond lengths of over 2,000 unique mononuclear Fe(II)/Fe(III) transition metal complexes.

Accelerating practical materials design

The accelerated discovery of materials for real world applications requires the achievement of multiple design objectives. The multi-dimensional nature of the search necessitates exploration of multi-million compound libraries over which even density-functional theory (DFT) screening is intractable. Machine learning (ML, e.g., artificial neural network, ANN, or Gaussian process, GP) models for this task are limited by training data availability and predictive uncertainty quantification (UQ).

DFT density delocalization error on the PES

For approximate density functional theory (DFT) to be useful in catalytic applications of transition metal complexes, modeling strategies must simultaneously address electronic, geometric, and energetic properties of the relevant species. We show that for representative transition metal triatomics (MO2, where M = Cr, Mn, Fe, Co, or Ni) and related diatomics the incorporation of Hartree–Fock (HF) exchange in most cases improves the properties of the Born–Oppenheimer potential energy surface (PES) with respect to accurate experimental or CCSD(T) references.


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: