Publications

Author Title Type [ Year(Asc)]
Submitted
An Irreversible Synthetic Route to an Ultra-Strong Two-Dimensional Polymer, Zeng, Yuwen, Gordiichuk Pavlo, Ichihara Takeo, Zhang Ge, Sandoz-Rosado Emil, Wetzel Eric D., Tresback Jason, Yang Jing, Yang Zhongyue, Kozawa Daichi, et al. , (Submitted)
Molecular Basis of C–S Bond Cleavage in the Glycyl Radical Enzyme Isethionate Sulfite-Lyase, Dawson, Christopher, Irwin Stephania, Backman Lindsey, Le Chip, Wang Jennifer X., Vennelakanti Vyshnavi, Yang Zhongyue, Kulik Heather J., Drennan Catherine L., and Balskus Emily P. , (Submitted)
Quantifying the long-range coupling of electronic properties in proteins with ab initio molecular dynamics, Yang, Zhongyue, Hajlasz Natalia, Steeves Adam H., and Kulik Heather J. , (Submitted)
In Press
Biochemical and crystallographic investigations into isonitrile formation by a non-heme iron-dependent oxidase/decarboxylase, Jonnalagadda, Rohan, Flores Antonio Del Rio, Cai Wenlong, Mehmood Rimsha, Narayanamoorthy Maanasa, Ren Chaoxiang, Zaragoza Jan Paulo T., Kulik Heather J., Zhang Wenjun, and Drennan Catherine L. , (In Press)
Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design, Janet, Jon Paul, Duan Chenru, Nandy Aditya, Liu Fang, and Kulik Heather J. , Accounts of Chemical Research, (In Press)
Quantum-mechanical/Molecular-mechanical (QM/MM) Simulations for Understanding Enzyme Dynamics, Mehmood, Rimsha, and Kulik Heather J. , Methods in Molecular Biology, (In Press)
When Are Two Hydrogen Bonds Better than One? Accurate First-Principles Models Explain the Balance of Hydrogen Bond Donors and Acceptors Found in Proteins, Vennelakanti, Vyshnavi, Qi Helena W., Mehmood Rimsha, and Kulik Heather J. , Chemical Science, (In Press)
2020
Accurate multi-objective design in a space of millions of transition metal complexes with neural-network-driven efficient global optimization, Janet, Jon Paul, Ramesh Sahasrajit, Duan Chenru, and Kulik Heather J. , ACS Central Science, Volume 6, p.513-524, (2020)
Both Configuration and QM Region Size Matter: Zinc Stability in QM/MM Models of DNA Methyltransferase, Mehmood, Rimsha, and Kulik Heather J. , Journal of Chemical Theory and Computation, Volume 16, p.3121-3134, (2020)
Data-Driven Approaches Can Overcome the Cost-Accuracy Tradeoff in Multireference Diagnostics, Duan, Chenru, Liu Fang, Nandy Aditya, and Kulik Heather J. , Journal of Chemical Theory and Computation, Volume 16, p.4373-4387, (2020)
Enumeration of de novo inorganic complexes for chemical discovery and machine learning, Gugler, Stefan, Janet Jon Paul, and Kulik Heather J. , Molecular Systems Design & Engineering, Volume 5, p.139-152, (2020)
Impact of Approximate DFT Density Delocalization Error on Potential Energy Surfaces in Transition Metal Chemistry, Liu, Fang, and Kulik Heather J. , Journal of Chemical Theory and Computation, Volume 16, Issue 1, p.264-277, (2020)
Ionization behavior of nanoporous polyamide membranes, Ritt, Cody L., Werber Jay R., Wang Mengyi, Yang Zhongyue, Zhao Yumeng, Kulik Heather J., and Elimelech Menachem , Proceedings of the National Academy of Sciences, Volume 117, p.30191-30200, (2020)
Large-scale comparison of 3d and 4d transition metal complexes illuminates the reduced effect of exchange on second-row spin-state energetics, Nandy, Aditya, Chu Daniel B. K., Harper Daniel R., Duan Chenru, Arunachalam Naveen, Cytter Yael, and Kulik Heather J. , Physical Chemistry Chemical Physics, Volume 22, p.19326-19341, (2020)
Machine Learning in Chemistry, Janet, Jon Paul, and Kulik Heather J. , ACS In Focus Series, (2020)
Making machine learning a useful tool in the accelerated discovery of transition metal complexes, Kulik, Heather J. , Wiley Interdisciplinary Reviews: Computational Molecular Science, Volume 10, Issue 1, (2020)
Rapid detection of strong correlation with machine learning for transition metal complex high-throughput screening, Liu, Fang, Duan Chenru, and Kulik Heather J. , The Journal of Physical Chemistry Letters, Volume 11, (2020)
Seeing is Believing: Experimental Spin States from Machine Learning Model Structure Predictions, Taylor, Michael G., Yang Tzuhsiung, Lin Sean, Nandy Aditya, Janet Jon Paul, Duan Chenru, and Kulik Heather J. , The Journal of Physical Chemistry A, Volume 124, p.3286-3299, (2020)
Semi-Supervised Machine Learning Enables the Robust Detection of Multireference Character at Low Cost, Duan, Chenru, Liu Fang, Nandy Aditya, and Kulik Heather J. , The Journal of Physical Chemistry Letters, Volume 11, p.6640-6648, (2020)
Uncovering Alternate Pathways to Nafion Membrane Degradation in Fuel Cells with First-Principles Modeling, Bajaj, Akash, Liu Fang, and Kulik Heather J. , The Journal of Physical Chemistry C, Volume 124, p.15094-15106, (2020)
Understanding the diversity of the metal-organic framework ecosystem, Moosavi, Seyed Mohamad, Nandy Aditya, Jablonka Kevin M., Ongari Daniele, Janet Jon Paul, Boyd Peter G., Lee Yongjin, Smit Berend, and Kulik Heather J. , Nature Communications, Volume 11, (2020)
Why Conventional Design Rules for C-H Activation Fail for Open Shell Transition Metal Catalysts, Nandy, Aditya, and Kulik Heather J. , ACS Catalysis, Volume 10, p.15033-15047, (2020)
2019
Anthracene as a Launchpad for a Phosphinidene Sulfide and for Generation of a Phosphorus-Sulfur Material having the Composition P2S, a Vulcanized Red Phosphorus that is Yellow, Transue, Wesley, Nava Matthew, Terban Maxwell, Yang Jing, Greenberg Matthew, Wu Gang, Mustoe Chantal, Kennepohl Pierre, Owen Jonathan, Billinge Simon, et al. , Journal of the American Chemical Society, Volume 141, p.431-440, (2019)
Bridging the homogeneous-heterogeneous divide: modeling spin and reactivity in single atom catalysis, Liu, Fang, Yang Tzuhsiung, Yang Jing, Xu Eve, Bajaj Akash, and Kulik Heather J. , Frontiers In Chemistry, Volume 7, p.219, (2019)
Critical Knowledge Gaps in Mass Transport Through Single- Digit Nanopores: A Review and Perspective, Faucher, Samuel, Aluru Narayana, Bazant Martin, Blankschtein Daniel, Brozena Alexandra, Cumings John, J. de Souza Pedro, Menachem Elimelech, Epsztein Razi, Fourkas John, et al. , The Journal of Physical Chemistry C, Volume 123, p.21309-21326, (2019)

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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: