Author Title Type [ Year(Asc)]
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)
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)
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)
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)
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)
Designing in the Face of Uncertainty: Exploiting Electronic Structure and Machine Learning Models for Discovery in Inorganic Chemistry, Janet, Jon Paul, Liu Fang, Nandy Aditya, Duan Chenru, Yang Tzuhsiung, Lin Sean, and Kulik Heather J. , Inorganic Chemistry, Volume 58, p.10592-10606, (2019)
Evaluating Unexpectedly Short Non-covalent Distances in X-ray Crystal Structures of Proteins with Electronic Structure Analysis, Qi, Helena W., and Kulik Heather J. , Journal of Chemical Information and Modeling, Volume 59, p.2199-2211, (2019)
Exploiting graphical processing units to enable quantum chemistry calculation of large solvated molecules with conductor-like polarizable continuum models, Liu, Fang, Sanchez David M., Kulik Heather J., and Martínez Todd J. , International Journal of Quantum Chemistry , 10/2018, Volume 119, Issue 1, (2019)
Learning from Failure: Predicting Electronic Structure Calculation Outcomes with Machine Learning Models, Duan, Chenru, Janet Jon Paul, Liu Fang, Nandy Aditya, and Kulik Heather J. , Journal of Chemical Theory and Computation, Volume 15, p.2331-2345, (2019)
Machine Learning Accelerates the Discovery of Design Rules and Exceptions in Stable Metal-Oxo Intermediate Formation, Nandy, Aditya, Zhu Jiazhou, Janet Jon Paul, Duan Chenru, Getman Rachel B., and Kulik Heather J. , ACS Catalysis, Volume 9, p.8243-8255, (2019)
Non-empirical, low-cost recovery of exact conditions with model-Hamiltonian inspired expressions in jmDFT, Bajaj, Akash, Liu Fang, and Kulik Heather J. , Journal of Chemical Physics, Volume 150, p.154115, (2019)
Protection of tissue physicochemical properties using polyfunctional crosslinkers, Park, Young-Gyun, Sohn Chang Ho, Chen Ritchie, McCue Margaret, Drummond Gabrielle T., Ku Taeyun, Yun Dae Hee, Evans Nicholas B., Oak Hayeon Caitlyn, Trieu Wendy, et al. , Nature Biotechnology, Volume 37, p.73-83, (2019)
The Protein’s Role in Substrate Positioning and Reactivity for Biosynthetic Enzyme Complexes: the Case of SyrB2/SyrB1, Mehmood, Rimsha, Qi Helena W., Steeves Adam H., and Kulik Heather J. , ACS Catalysis, Volume 9, p.4930-4943, (2019)
A quantitative uncertainty metric controls error in neural network-driven chemical discovery, Janet, Jon Paul, Duan Chenru, Yang Tzuhsiung, Nandy Aditya, and Kulik Heather J. , Chemical Science, Volume 10, p.7913-7922, (2019)
Quantum Mechanical Description of Electrostatics Provides a Unified Picture of Catalytic Action Across Methyltransferases, Yang, Zhongyue, Liu Fang, Steeves Adam H., and Kulik Heather J. , The Journal of Physical Chemistry Letters, Volume 10, p.3779-3787, (2019)


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: