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2
Protein3D: Enabling analysis and extraction of metal-containing sites from the Protein Data Bank with molSimplify
Metalloenzymes catalyze a wide range of chemical transformations, with the active site residues playing a key role in modulating …
Freya Edholm
,
Aditya Nandy
,
Clorice Reinhardt
,
David Kastner
,
Heather J. Kulik
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DOI
Large-scale Comparison of Fe and Ru Polyolefin C–H Activation Catalysts
We performed a large-scale density functional theory comparison of polyolefin C–H hydroxylation trends across over 200 Fe and Ru …
Husain Adamji
,
Ilia Kevlishvili
,
Aditya Nandy
,
Yuriy Roman-Leshkov
,
Heather J. Kulik
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DOI
ChemRxiv
Computational Discovery of Codoped Single-Atom Catalysts for Methane-to-Methanol Conversion
The absence of a synthetic catalyst that can selectively oxidize methane to methanol motivates extensive study of single-site catalysts …
Haojun Jia
,
Chenru Duan
,
Ilia Kevlishvili
,
Aditya Nandy
,
Mingjie Liu
,
Heather J. Kulik
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DOI
ChemRxiv
Benchmarking Nitrous Oxide Adsorption and Activation in Metal-Organic Frameworks Bearing Coordinatively Unsaturated Metal Centers
Anthropogenic emissions of N
2
O, the third most abundant greenhouse gas after CO
2
and CH
4
, are contributing to global climate change. …
Tristan Pitt
,
Haojun Jia
,
Tyler Azbell
,
Mary Zick
,
Aditya Nandy
,
Heather J. Kulik
,
Phillip Milner
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DOI
ChemRxiv
Machine Learning Prediction of the Experimental Transition Temperature of Fe(II) Spin-Crossover Complexes
Spin-crossover (SCO) complexes are materials that exhibit changes in the spin state in response to external stimuli, with potential …
Vyshnavi Vennelakanti
,
Irem B. Kilic
,
Gianmarco Terrones
,
Chenru Duan
,
Heather J. Kulik
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DOI
ChemRxiv
Uncertain of uncertainties? A comparison of uncertainty quantification metrics for chemical data sets
With the increasingly more important role of machine learning (ML) models in chemical research, the need for putting a level of …
Maria H. Rasmussen
,
Chenru Duan
,
Heather J. Kulik
,
Jan Halborg Jensen
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DOI
ChemRxiv
Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model
Transition state (TS) search is key in chemistry for elucidating reaction mechanisms and exploring reaction networks. The search for …
Chenru Duan
,
Yuanqi Du
,
Haojun Jia
,
Heather J. Kulik
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DOI
arXiv
Classification of Hemilabile Ligands Using Machine Learning
Hemilabile ligands have the capacity to partially disengage from a metal center, providing a strategy to balance stability and …
Ilia Kevlishvili
,
Chenru Duan
,
Heather J. Kulik
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DOI
ChemRxiv
Discovering Molecular Coordination Environment Trends for Selective Ion Binding to Molecular Complexes Using Machine Learning
The design of ion-selective materials with improved separation efficacy and efficiency is paramount, as current technologies fail to …
Shuwen Yue
,
Aditya Nandy
,
Heather J. Kulik
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DOI
ChemRxiv
Why Nonheme Iron Halogenases Do Not Fluorinate C–H Bonds: A Computational Investigation
Selective halogenation is necessary for a range of fine chemical applications, including the development of therapeutic drugs. While …
Vyshnavi Vennelakanti
,
Grace Li
,
Heather J. Kulik
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DOI
ChemRxiv
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