Publications
] Impact of Approximate DFT Density Delocalization Error on Potential Energy Surfaces in Transition Metal Chemistry,
, (Submitted)
Machine Learning in Chemistry,
, ACS In Focus Series, (Submitted)
Enumeration of de novo inorganic complexes for chemical discovery and machine learning,
, Molecular Systems Design & Engineering, Volume Invited for Emerging Investigators issue, (In Press)
Making machine learning a useful tool in the accelerated discovery of transition metal complexes,
, Wiley Interdisciplinary Reviews: Computational Molecular Science, Volume Invited Opinion, just accepted, (In Press)
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,
, 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,
, Frontiers In Chemistry, Volume 7, p.219, (2019)
Critical Knowledge Gaps in Mass Transport Through Single- Digit Nanopores: A Review and Perspective,
, 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,
, 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,
, 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,
, International Journal of Quantum Chemistry , 10/2018, Volume 119, Issue 1, (2019)
Learning from Failure: Predicting Electronic Structure Calculation Outcomes with Machine Learning Models,
, 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,
, ACS Catalysis, Volume 9, p.8243-8255, (2019)
Non-empirical, low-cost recovery of exact conditions with model-Hamiltonian inspired expressions in jmDFT,
, Journal of Chemical Physics, Volume 150, p.154115, (2019)
Protection of tissue physicochemical properties using polyfunctional crosslinkers,
, 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,
, ACS Catalysis, Volume 9, p.4930-4943, (2019)
A quantitative uncertainty metric controls error in neural network-driven chemical discovery,
, Chemical Science, Volume 10, p.7913-7922, (2019)
Quantum Mechanical Description of Electrostatics Provides a Unified Picture of Catalytic Action Across Methyltransferases,
, The Journal of Physical Chemistry Letters, Volume 10, p.3779-3787, (2019)
Revealing quantum mechanical effects in enzyme catalysis with large-scale electronic structure simulation,
, Reaction Chemistry & Engineering, Volume 4, p.298-315, (2019)
Stable Surfaces that Bind too Tightly: Can Range Separated Hybrids or DFT+U Improve Paradoxical Descriptions of Surface Chemistry?,
, The Journal of Physical Chemistry Letters, Volume 10, p.5090-5098, (2019)
Accelerating Chemical Discovery with Machine Learning: Simulated Evolution of Spin Crossover Complexes with an Artificial Neural Network,
, The Journal of Physical Chemistry Letters, 02/2018, Volume 9, p.1064-1071, (2018)
Electronic Structure Origins of Surface-Dependent Growth in III-V Quantum Dots,
, Chemistry of Materials, 09/2018, Volume 30, p.7154-7165, (2018)
Large-scale QM/MM free energy simulations of enzyme catalysis reveal the influence of charge transfer,
, Physical Chemistry Chemical Physics, 07/2018, Volume 20, p.20650-20660, (2018)
Modeling Mechanochemistry from First Principles,
, Reviews in Computational Chemistry, Volume 31, (2018)
Quantifying electronic effects in QM and QM/MM biomolecular modeling with the Fukui function,
, Acta Physico-Chimica Sinica (invited article for Conceptual Density Functional Theory special issue, ed. Shubin Liu), Volume 34, p.81-91, (2018)
Strategies and Software for Machine Learning Accelerated Discovery in Transition Metal Chemistry,
, Industrial & Engineering Chemistry Research (invited for special issue), 09/2018, Volume 57, (2018)