H. Kulik

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Making machine learning a useful tool in the accelerated discovery of transition metal complexes

H. Kulik, 2019, WIREs Computational Molecular Science.

Machine Learning in Chemistry

H. Kulik, J. Janet, Yamilee Morency, Chemistry majors, Fordham Univers, 2020 .

Depolymerization Pathways for Branching Lignin Spirodienone Units Revealed with ab Initio Steered Molecular Dynamics.

H. Kulik, Brendan D. Mar, 2017, The journal of physical chemistry. A.

Strategies and Software for Machine Learning Accelerated Discovery in Transition Metal Chemistry

Chenru Duan, Aditya Nandy, Jon Paul Janet, 2018, Industrial & Engineering Chemistry Research.

Resolving Transition Metal Chemical Space: Feature Selection for Machine Learning and Structure-Property Relationships.

Heather J Kulik, Jon Paul Janet, H. Kulik, 2017, The journal of physical chemistry. A.

Perspective: Treating electron over-delocalization with the DFT+U method.

Heather J Kulik, H. Kulik, 2015, The Journal of chemical physics.

Learning from Failure: Predicting Electronic Structure Calculation Outcomes with Machine Learning Models.

Fang Liu, Chenru Duan, Aditya Nandy, 2019, Journal of chemical theory and computation.

Leveraging Cheminformatics Strategies for Inorganic Discovery: Application to Redox Potential Design

Adam H. Steeves, Jon Paul Janet, Heather J. Kulik, 2017 .

A Quantitative Uncertainty Metric Controls Error in Neural Network-Driven Chemical Discovery

H. Kulik, J. Janet, A. Nandy, 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.

H. Kulik, S. Billinge, M. Terban, 2018, Journal of the American Chemical Society.

Designing in the Face of Uncertainty: Exploiting Electronic Structure and Machine Learning Models for Discovery in Inorganic Chemistry.

F. Liu, H. Kulik, J. Janet, 2019, Inorganic chemistry.

When are two hydrogen bonds better than one? Accurate first-principles models explain the balance of hydrogen bond donors and acceptors found in proteins

H. Kulik, Helena W. Qi, Vyshnavi Vennelakanti, 2020, Chemical science.

Electronic Structure and Reactivity of Transition Metal Complexes

N. Marzari, H. Kulik, 2010 .

Density functional theory in transition-metal chemistry: a self-consistent Hubbard U approach.

N. Marzari, M. Cococcioni, H. Kulik, 2006, Physical review letters.

Seeing Is Believing: Experimental Spin States from Machine Learning Model Structure Predictions

Michael G. Taylor, H. Kulik, J. Janet, 2020, The journal of physical chemistry. A.

Large-scale comparison of 3d and 4d transition metal complexes illuminates the reduced effect of exchange on second-row spin-state energetics.

H. Kulik, A. Nandy, Chenru Duan, 2020, Physical chemistry chemical physics : PCCP.

Bridging the Homogeneous-Heterogeneous Divide: Modeling Spin for Reactivity in Single Atom Catalysis

H. Kulik, Akash Bajaj, Tzuhsiung Yang, 2019, Front. Chem..

Unifying Exchange Sensitivity in Transition-Metal Spin-State Ordering and Catalysis through Bond Valence Metrics.

Terry Z. H. Gani, H. Kulik, 2017, Journal of chemical theory and computation.

Towards quantifying the role of exact exchange in predictions of transition metal complex properties.

H. Kulik, E. Ioannidis, 2015, The Journal of chemical physics.

Accelerating inorganic discovery with meta-calculation filtering via a decision classifier

Fang Liu, Chenru Duan, Aditya Nandy, 2019 .

Where Does the Density Localize in the Solid State? Divergent Behavior for Hybrids and DFT+U.

H. Kulik, Qing Zhao, 2018, Journal of chemical theory and computation.

Large-scale QM/MM free energy simulations of enzyme catalysis reveal the influence of charge transfer.

H. Kulik, 2018, Physical chemistry chemical physics : PCCP.

Computational Investigation of the Interplay of Substrate Positioning and Reactivity in Catechol O-Methyltransferase

H. Kulik, E. Ioannidis, N. Patra, 2016, PloS one.

Density functional theory for modelling large molecular adsorbate–surface interactions: a mini-review and worked example

H. Kulik, J. Janet, E. Ioannidis, 2016 .

Exploiting graphical processing units to enable quantum chemistry calculation of large solvated molecules with conductor‐like polarizable continuum models

T. Martínez, F. Liu, H. Kulik, 2018, International Journal of Quantum Chemistry.

Ionization behavior of nanoporous polyamide membranes

Jay R. Werber, M. Elimelech, H. Kulik, 2020, Proceedings of the National Academy of Sciences.

Revealing quantum mechanical effects in enzyme catalysis with large-scale electronic structure simulation.

H. Kulik, A. Steeves, Helena W. Qi, 2018, Reaction chemistry & engineering.

Computational Discovery of Hydrogen Bond Design Rules for Electrochemical Ion Separation

Terry Z. H. Gani, H. Kulik, E. Ioannidis, 2016 .

Where Does the Density Localize? Convergent Behavior for Global Hybrids, Range Separation, and DFT+U.

Heather J Kulik, Terry Z. H. Gani, H. Kulik, 2016, Journal of chemical theory and computation.

Non-empirical, low-cost recovery of exact conditions with model-Hamiltonian inspired expressions in jmDFT.

Fang Liu, H. Kulik, Akash Bajaj, 2019, The Journal of chemical physics.

Transition-metal dioxides: a case for the intersite term in Hubbard-model functionals.

N. Marzari, H. Kulik, 2011, The Journal of chemical physics.

Accurate potential energy surfaces with a DFT+U(R) approach.

N. Marzari, H. Kulik, 2011, The Journal of chemical physics.

Global and local curvature in density functional theory.

H. Kulik, E. Ioannidis, Qing Zhao, 2016, The Journal of chemical physics.

Ab Initio Screening Approach for the Discovery of Lignin Polymer Breaking Pathways.

Fang Liu, H. Kulik, Helena W. Qi, 2015, The journal of physical chemistry. A.

Topical Plenary: Topical Conference in Molecular and Materials Data Science (Invited Talks)

Jim Pfaendtner, Elizabeth Nance, Johannes Hachmann, 2019 .

Detection of multi-reference character imbalances enables a transfer learning approach for virtual high throughput screening with coupled cluster accuracy at DFT cost

H. Kulik, A. Nandy, Chenru Duan, 2022, Chemical science.

New Strategies for Direct Methane-to-Methanol Conversion from Active Learning Exploration of 16 Million Catalysts

H. Kulik, A. Nandy, Chenru Duan, 2022, JACS Au.

Emergence of a proton exchange-based isomerization and lactonization mechanism in the plant coumarin synthase COSY

H. Kulik, J. Weng, Andrew J. Mitchell, 2022, bioRxiv.

Rapid Detection of Strong Correlation with Machine Learning for Transition-Metal Complex High-Throughput Screening.

H. Kulik, Chenru Duan, Fang Liu, 2020, The journal of physical chemistry letters.

Enumeration of de novo inorganic complexes for chemical discovery and machine learning

H. Kulik, J. Janet, Stefan Gugler, 2019, Molecular Systems Design & Engineering.

Accurate Multiobjective Design in a Space of Millions of Transition Metal Complexes with Neural-Network-Driven Efficient Global Optimization

H. Kulik, J. Janet, Chenru Duan, 2019, ACS central science.

Resolving Transition Metal Chemical Space: Feature Selection for Machine Learning and Structure-Property Relationships.

H. Kulik, J. Janet, 2017, The journal of physical chemistry. A.

Impact of Approximate DFT Density Delocalization Error on Potential Energy Surfaces in Transition Metal Chemistry.

H. Kulik, Fang Liu, 2019, Journal of chemical theory and computation.

Communication: Recovering the flat-plane condition in electronic structure theory at semi-local DFT cost.

H. Kulik, Akash Bajaj, J. Janet, 2017, The Journal of chemical physics.

A transferable recommender approach for selecting the best density functional approximations in chemical discovery

H. Kulik, A. Nandy, Chenru Duan, 2022, Nature Computational Science.

Data-Driven Approaches Can Overcome Limitations in Multireference Diagnostics

H. Kulik, A. Nandy, Chenru Duan, 2020 .

Electronic Structure Origins of Surface-Dependent Growth in III–V Quantum Dots

H. Kulik, Qing Zhao, 2018, Proceedings of the nanoGe Fall Meeting 2019.

Systematic Quantum Mechanical Region Determination in QM/MM Simulation.

H. Kulik, M. Karelina, 2017, Journal of chemical theory and computation.

Strategies and Software for Machine Learning Accelerated Discovery in Transition Metal Chemistry

H. Kulik, J. Janet, A. Nandy, 2018, Industrial & Engineering Chemistry Research.

Uncovering Alternate Pathways to Nafion Membrane Degradation in Fuel Cells with First-Principles Modeling

H. Kulik, Akash Bajaj, Fang Liu, 2020 .

Rapid Exploration of a 32.5M Compound Chemical Space with Active Learning to Discover Density Functional Approximation Insensitive and Synthetically Accessible Transitional Metal Chromophores

H. Kulik, A. Nandy, Chenru Duan, 2022, ArXiv.

Quantifying the Long-Range Coupling of Electronic Properties in Proteins with Ab Initio Molecular Dynamics

H. Kulik, A. Steeves, Z. Yang, 2020, Chemistry–Methods.

Large-Scale Screening Reveals That Geometric Structure Matters More Than Electronic Structure in the Bioinspired Catalyst Design of Formate Dehydrogenase Mimics

Michael G. Taylor, H. Kulik, A. Steeves, 2021, ACS Catalysis.

Exploiting Ligand Additivity for Transferable Machine Learning of Multireference Character Across Known Transition Metal Complex Ligands

Michael G. Taylor, H. Kulik, Chenru Duan, 2022, Journal of chemical theory and computation.

Understanding the diversity of the metal-organic framework ecosystem

Peter G. Boyd, Yongjin Lee, S. M. Moosavi, 2020, Nature Communications.

Learning from Failure: Predicting Electronic Structure Calculation Outcomes with Machine Learning Models.

H. Kulik, J. Janet, A. Nandy, 2019, Journal of chemical theory and computation.

Both Configuration and QM Region Size Matter: Zinc Stability in QM/MM Models of DNA Methyltransferase.

H. Kulik, Rimsha Mehmood, 2020, Journal of chemical theory and computation.

Using Computational Chemistry To Reveal Nature’s Blueprints for Single-Site Catalysis of C–H Activation

H. Kulik, A. Nandy, Vyshnavi Vennelakanti, 2022, ACS Catalysis.

Why Conventional Design Rules for C–H Activation Fail for Open-Shell Transition-Metal Catalysts

H. Kulik, A. Nandy, Aditya Nandy, 2020, ACS Catalysis.

Understanding and Breaking Scaling Relations in Single-Site Catalysis: Methane to Methanol Conversion by FeIV═O

Terry Z. H. Gani, H. Kulik, 2018 .

Quantum Chemistry for Solvated Molecules on Graphical Processing Units Using Polarizable Continuum Models.

T. Martínez, H. Kulik, Nathan Luehr, 2015, Journal of chemical theory and computation.

Quantum Chemistry for Solvated Molecules on Graphical Processing Units Using Polarizable Continuum Models.

T. Martínez, F. Liu, H. Kulik, 2015, Journal of chemical theory and computation.

Endohedrally Functionalized Metal-Organic Cage-Cross-Linked Polymer Gels as Modular Heterogeneous Catalysts.

Jeremiah A. Johnson, H. Kulik, M. F. Ottaviani, 2022, Journal of the American Chemical Society.

Semi-Supervised Machine Learning Enables the Robust Detection of Multireference Character at Low Cost.

H. Kulik, A. Nandy, Chenru Duan, 2020, The journal of physical chemistry letters.

Seeing Is Believing: Experimental Spin States from Machine Learning Model Structure Predictions

Michael G. Taylor, H. Kulik, J. Janet, 2020, The journal of physical chemistry. A.

The Protein’s Role in Substrate Positioning and Reactivity for Biosynthetic Enzyme Complexes: The Case of SyrB2/SyrB1

H. Kulik, A. Steeves, Helena W. Qi, 2018, ACS Catalysis.

Non-Native Anionic Ligand Binding and Reactivity in Engineered Variants of the Fe(II)- and α-Ketoglutarate-Dependent Oxygenase, SadA.

H. Kulik, Qian Du, Vyshnavi Vennelakanti, 2022, Inorganic chemistry.

Substrate Placement Influences Reactivity in Non-heme Fe(II) Halogenases and Hydroxylases*

H. Kulik, C. Drennan, 2013, The Journal of Biological Chemistry.

Active Learning Exploration of Transition-Metal Complexes to Discover Method-Insensitive and Synthetically Accessible Chromophores

H. Kulik, A. Nandy, Chenru Duan, 2022, JACS Au.

Towards quantifying the role of exact exchange in predictions of transition metal complex properties.

H. Kulik, E. Ioannidis, 2015, The Journal of chemical physics.

When are two hydrogen bonds better than one? Accurate first-principles models explain the balance of hydrogen bond donors and acceptors found in proteins

H. Kulik, Helena W. Qi, Vyshnavi Vennelakanti, 2020, Chemical science.

Evaluating Unexpectedly Short Non-covalent Distances in X-ray Crystal Structures of Proteins with Electronic Structure Analysis

H. Kulik, Helena W. Qi, 2019, J. Chem. Inf. Model..

Mechanistic Studies of a Skatole-Forming Glycyl Radical Enzyme Suggest Reaction Initiation via Hydrogen Atom Transfer

H. Kulik, E. Balskus, Z. Yang, 2022, Journal of the American Chemical Society.

Roadmap on Machine learning in electronic structure

Kristof T. Schütt, T. Carrington, S. Manzhos, 2022, Electronic Structure.

A quantitative uncertainty metric controls error in neural network-driven chemical discovery

H. Kulik, J. Janet, A. Nandy, 2019, Chemical science.

A Quantitative Uncertainty Metric Controls Error in Neural Network-Driven Chemical Discovery

H. Kulik, J. Janet, A. Nandy, 2019 .

Low-cost machine learning approach to the prediction of transition metal phosphor excited state properties

H. Kulik, A. Nandy, Chenru Duan, 2022, ArXiv.

Where Does the Density Localize? Convergent Behavior for Global Hybrids, Range Separation, and DFT+U.

Terry Z. H. Gani, H. Kulik, 2016, Journal of chemical theory and computation.

Adapting DFT+U for the Chemically Motivated Correction of Minimal Basis Set Incompleteness.

T. Martínez, H. Kulik, Brendan D. Mar, 2016, The journal of physical chemistry. A.

A Database of Ultrastable MOFs Reassembled from Stable Fragments with Machine Learning Models

H. Kulik, A. Nandy, Chenru Duan, 2022, SSRN Electronic Journal.

Insights into the stability of engineered mini-proteins from their dynamic electronic properties

H. Kulik, A. Steeves, 2022, Electronic Structure.

Local effects in the X-ray absorption spectrum of salt water.

N. Marzari, G. Galli, E. Schwegler, 2010, The journal of physical chemistry. B.

Light Emission in 2D Silver Phenylchalcogenolates.

H. Kulik, W. Tisdale, W. Lee, 2022, ACS nano.

Ligand additivity relationships enable efficient exploration of transition metal chemical space.

Michael G. Taylor, H. Kulik, J. Janet, 2022, The Journal of chemical physics.

DFT-Based Multireference Diagnostics in the Solid State: Application to Metal-Organic Frameworks.

H. Kulik, A. Nandy, Chenru Duan, 2022, Journal of chemical theory and computation.

Molecular DFT+U: A Transferable, Low-Cost Approach to Eliminate Delocalization Error.

H. Kulik, Akash Bajaj, 2021, The journal of physical chemistry letters.

Influence of the Greater Protein Environment on the Electrostatic Potential in Metalloenzyme Active Sites: The Case of Formate Dehydrogenase.

H. Kulik, A. Steeves, Azadeh Nazemi, 2021, The journal of physical chemistry. B.

Understanding the Role of Geometric and Electronic Structure in Bioinspired Catalyst Design: the Case of Formate Dehydrogenase

H. Kulik, A. Steeves, A. Nandy, 2021 .

Computational Scaling Relationships Predict Experimental Activity and Rate-Limiting Behavior in Homogeneous Water Oxidation.

H. Kulik, Daniel R Harper, 2021, Inorganic chemistry.

Computational Discovery of Transition-metal Complexes: From High-throughput Screening to Machine Learning.

Michael G. Taylor, F. Liu, H. Kulik, 2021, Chemical reviews.

Emergence of a proton exchange-based isomerization and lactonization mechanism in the plant coumarin synthase COSY

H. Kulik, J. Weng, Andrew J. Mitchell, 2022, bioRxiv.

Anion‐Selective Redox Electrodes: Electrochemically Mediated Separation with Heterogeneous Organometallic Interfaces

Timothy F. Jamison, T. Alan Hatton, Heather J. Kulik, 2016 .

MODELING MECHANOCHEMISTRY FROM FIRST PRINCIPLES

H. Kulik, 2018, Reviews in Computational Chemistry.

Enumeration of de novo inorganic complexes for chemical discovery and machine learning

Jon Paul Janet, Heather J. Kulik, Stefan Gugler, 2019 .

Enumeration of de novo Inorganic Complexes for Chemical Discovery and Machine Learning

H. Kulik, J. Janet, Stefan Gugler, 2019 .

Developing an approach for first-principles catalyst design: application to carbon-capture catalysis.

Sergio E. Wong, J. Satcher, H. Kulik, 2014, Acta crystallographica. Section C, Structural chemistry.

Deciphering Cryptic Behavior in Bimetallic Transition Metal Complexes with Machine Learning

Aditya Nandy, Heather J. Kulik, Michael G. Taylor, 2021, The journal of physical chemistry letters.

Mechanically triggered heterolytic unzipping of a low-ceiling-temperature polymer

Heather J Kulik, Todd J Martínez, Joshua A. Kaitz, 2014, Nature Chemistry.

Remolding and Deconstruction of Industrial Thermosets via Carboxylic Acid-Catalyzed Bifunctional Silyl Ether Exchange.

Jeremiah A. Johnson, N. Sottos, H. Kulik, 2023, Journal of the American Chemical Society.

Critical Knowledge Gaps in Mass Transport through Single-Digit Nanopores: A Review and Perspective

M. Reed, M. Bazant, YuHuang Wang, 2019, The Journal of Physical Chemistry C.

Simultaneous protection of tissue physicochemical properties using polyfunctional crosslinkers

Kwanghun Chung, Heather J Kulik, Heejin Choi, 2018, Nature Biotechnology.

Biochemical and crystallographic investigations into isonitrile formation by a nonheme iron-dependent oxidase/decarboxylase

H. Kulik, C. Drennan, Wenjun Zhang, 2020, The Journal of biological chemistry.

Designing small-molecule catalysts for CO2 capture

Sergio E. Wong, J. Satcher, H. Kulik, 2011 .

Predicting the Stability of Fullerene Allotropes Throughout the Periodic Table

H. Kulik, S. Ng, Qing Zhao, 2016 .

molSimplify: A toolkit for automating discovery in inorganic chemistry

Heather J. Kulik, Terry Z. H. Gani, Efthymios I. Ioannidis, 2016, J. Comput. Chem..

Systematic study of first-row transition-metal diatomic molecules: a self-consistent DFT+U approach.

Heather J Kulik, Nicola Marzari, N. Marzari, 2010, The Journal of chemical physics.

Protein Dynamics and Substrate Protonation States Mediate the Catalytic Action of trans-4-Hydroxy-l-Proline Dehydratase.

H. Kulik, Zhongyue Yang, 2021, The journal of physical chemistry. B.

Influence of the Greater Protein Environment on the Electrostatic Potential in Metalloenzyme Active Sites: The Case of Formate Dehydrogenase.

H. Kulik, A. Steeves, Azadeh Nazemi, 2022, Journal of Physical Chemistry B.

Mechanistic Insights into Substrate Positioning That Distinguish Non-heme Fe(II)/α-Ketoglutarate-Dependent Halogenases and Hydroxylases

H. Kulik, Rimsha Mehmood, D. Kastner, 2023, ACS Catalysis.

Modeling, synthesis and characterization of zinc containing carbonic anhydrase active site mimics

J. Satcher, H. Kulik, R. Aines, 2011 .

Predicting electronic structure properties of transition metal complexes with neural networks† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc01247k

Heather J Kulik, Jon Paul Janet, H. Kulik, 2017, Chemical science.

How Large Should the QM Region Be in QM/MM Calculations? The Case of Catechol O-Methyltransferase

Heather J. Kulik, Todd J. Martínez, J. Klinman, 2015, The journal of physical chemistry. B.

What's Left for a Computational Chemist To Do in the Age of Machine Learning?

H. Kulik, 2021 .

1D Hybrid Semiconductor Silver 2,6-Difluorophenylselenolate.

H. Kulik, W. Tisdale, P. Müller, 2023, Journal of the American Chemical Society.

Ab initio quantum chemistry for protein structures.

Heather J Kulik, Ivan S Ufimtsev, Todd J Martinez, 2012, The journal of physical chemistry. B.

Fluids and Electrolytes under Confinement in Single-Digit Nanopores

Volodymyr B. Koman, M. Bazant, YuHuang Wang, 2023, Chemical reviews.

A self-consistent Hubbard U density-functional theory approach to the addition-elimination reactions of hydrocarbons on bare FeO+.

N. Marzari, H. Kulik, 2008, The Journal of chemical physics.

Computational Modeling of Conformer Stability in Benenodin-1, a Thermally Actuated Lasso Peptide Switch.

H. Kulik, Natalia Hajlasz, Zhongyue Yang, 2022, The journal of physical chemistry. B.

Harder, better, faster, stronger: Large-scale QM and QM/MM for predictive modeling in enzymes and proteins.

H. Kulik, A. Steeves, Vyshnavi Vennelakanti, 2021, Current opinion in structural biology.

Machine Learning in Chemistry

H. Kulik, J. Janet, Yamilee Morency, Chemistry majors, Fordham Univers, 2020, ACS In Focus.

Spectroscopically Guided Simulations Reveal Distinct Strategies for Positioning Substrates to Achieve Selectivity in Nonheme Fe(II)/α-Ketoglutarate-Dependent Halogenases

H. Kulik, Vyshnavi Vennelakanti, Rimsha Mehmood, 2021, ACS Catalysis.

Putting Density Functional Theory to the Test in Machine-Learning-Accelerated Materials Discovery

F. Liu, H. Kulik, Chenru Duan, 2021, The journal of physical chemistry letters.

Data-Driven Approaches Can Overcome the Cost-Accuracy Trade-off in Multireference Diagnostics.

Chenru Duan, Aditya Nandy, Heather J Kulik, 2020, Journal of chemical theory and computation.

Eliminating Delocalization Error to Improve Heterogeneous Catalysis Predictions with Molecular DFT + U.

H. Kulik, Akash Bajaj, 2021, Journal of chemical theory and computation.

Stable Surfaces That Bind Too Tightly: Can Range-Separated Hybrids or DFT+U Improve Paradoxical Descriptions of Surface Chemistry?

H. Kulik, Qing Zhao, 2019, The journal of physical chemistry letters.

Ligand-Field-Dependent Behavior of Meta-GGA Exchange in Transition-Metal Complex Spin-State Ordering.

Heather J. Kulik, H. Kulik, E. Ioannidis, 2017, The journal of physical chemistry. A.

Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles

Chenru Duan, Heather J. Kulik, Fang Liu, 2021, Chemical science.

Audacity of huge: overcoming challenges of data scarcity and data quality for machine learning in computational materials discovery pdf

Chenru Duan, Aditya Nandy, Heather J. Kulik, 2021, Current Opinion in Chemical Engineering.

Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model

H. Kulik, Chenru Duan, Yuanqi Du, 2023, ArXiv.

Machine learning models predict calculation outcomes with the transferability necessary for computational catalysis

H. Kulik, Yuriy Román‐Leshkov, Chenru Duan, 2022, Journal of chemical theory and computation.

Two Wrongs Can Make a Right: A Transfer Learning Approach for Chemical Discovery with Chemical Accuracy pdf

Chenru Duan, Aditya Nandy, Heather J. Kulik, 2022, ArXiv.

Ligand Additivity and Divergent Trends in Two Types of Delocalization Errors from Approximate Density Functional Theory.

H. Kulik, Akash Bajaj, Yael Cytter, 2022, The journal of physical chemistry letters.

The Effect of Hartree-Fock Exchange on Scaling Relations and Reaction Energetics for C–H Activation Catalysts

H. Kulik, Vyshnavi Vennelakanti, Aditya Nandy, 2021, Topics in Catalysis.

Using Machine Learning and Data Mining to Leverage Community Knowledge for the Engineering of Stable Metal-Organic Frameworks

Chenru Duan, Aditya Nandy, Heather J. Kulik, 2021, Journal of the American Chemical Society.

Machine learning reveals key ion selectivity mechanisms in polymeric membranes with subnanometer pores

M. Elimelech, T. Pham, H. Kulik, 2022, Science advances.

Probing the Structure of Salt Water under Confinement with First-Principles Molecular Dynamics and Theoretical X-ray Absorption Spectroscopy.

G. Galli, E. Schwegler, H. Kulik, 2012, The journal of physical chemistry letters.

Quantum Mechanical Description of Electrostatics Provides a Unified Picture of Catalytic Action Across Methyltransferases.

H. Kulik, A. Steeves, Fang Liu, 2019, The journal of physical chemistry letters.

MOFSimplify: Machine Learning Models with Extracted Stability Data of Three Thousand Metal-Organic Frameworks pdf

N. Arunachalam, G. Terrones, A. Nandy, 2021, ArXiv.

Molecular orbital projectors in non-empirical jmDFT recover exact conditions in transition-metal chemistry.

Michael G. Taylor, H. Kulik, Akash Bajaj, 2021, The Journal of chemical physics.

Mapping the Origins of Surface- and Chemistry-Dependent Doping Trends in III–V Quantum Dots with Density Functional Theory

Michael G. Taylor, H. Kulik, 2021, Chemistry of Materials.

Mapping the Electronic Structure Origins of Surface- and Chemistry-Dependent Doping Trends in III-V Quantum Dots

Michael G. Taylor, H. Kulik, 2021, 2107.04696.

Quantum Chemistry Common Driver and Databases (QCDB) and Quantum Chemistry Engine (QCEngine): Automation and interoperability among computational chemistry programs.

Zachary L Glick, Andrew C. Simmonett, Levi N. Naden, 2021, The Journal of chemical physics.

Representations and Strategies for Transferable Machine Learning Models in Chemical Discovery pdf

Chenru Duan, Aditya Nandy, Jon Paul Janet, 2021, The Journal of chemical physics.

Machine Learning Accelerates the Discovery of Design Rules and Exceptions in Stable Metal–Oxo Intermediate Formation

Rachel B. Getman, H. Kulik, J. Janet, 2019, ACS Catalysis.

Harnessing Organic Ligand Libraries for First-Principles Inorganic Discovery: Indium Phosphide Quantum Dot Precursor Design Strategies

H. Kulik, A. Steeves, Jeong Yun Kim, 2017 .

Discovering Amorphous Indium Phosphide Nanostructures with High-Temperature ab Initio Molecular Dynamics

H. Kulik, Lisi Xie, Qing Zhao, 2015 .

Accelerating Chemical Discovery with Machine Learning: Simulated Evolution of Spin Crossover Complexes with an Artificial Neural Network.

Heather J Kulik, Jon Paul Janet, Lydia Chan, 2018, The journal of physical chemistry letters.

Isonitrile Formation by a Non-heme Iron(II)-dependent Oxidase/Decarboxylase

H. Kulik, Wenjun Zhang, Vyshnavi Vennelakanti, 2018, bioRxiv.

Effects of MOF linker rotation and functionalization on methane uptake and diffusion

H. Kulik, Shuwen Yue, Chang-Ho Oh, 2023, Molecular Systems Design & Engineering.

Are Vanadium Intermediates Suitable Mimics in Non-Heme Iron Enzymes? An Electronic Structure Analysis

H. Kulik, Vyshnavi Vennelakanti, Rimsha Mehmood, 2022, ACS Catalysis.

Revealing Substrate Positioning Dynamics in Non-heme Fe(II)/αKG-dependent Halogenases Through Spectroscopically Guided Simulation

H. Kulik, Vyshnavi Vennelakanti, Rimsha Mehmood, 2021 .

Spatially extended Kondo state in magnetic molecules induced by interfacial charge transfer.

S. Ulloa, N. Marzari, H. Kulik, 2010, Physical review letters.

Irreversible synthesis of an ultrastrong two-dimensional polymeric material

Zhe Yuan, Ge Zhang, A. T. Liu, 2022, Nature.

Molecular basis of C-S bond cleavage in the glycyl radical enzyme isethionate sulfite-lyase

H. Kulik, E. Balskus, C. Drennan, 2021, Cell chemical biology.

Computational Discovery of Stable Metal-Organic Frameworks for Methane-to-Methanol Catalysis.

H. Kulik, Yuriy Román‐Leshkov, Ilia Kevlishvili, 2023, Journal of the American Chemical Society.

Quantum-Mechanical/Molecular-Mechanical (QM/MM) Simulations for Understanding Enzyme Dynamics.

H. Kulik, Rimsha Mehmood, 2021, Methods in molecular biology.

First-principles study of non-heme Fe(II) halogenase SyrB2 reactivity.

N. Marzari, H. Kulik, L. C. Blasiak, 2009, Journal of the American Chemical Society.

Direct Observation of Early-Stage Quantum Dot Growth Mechanisms with High-Temperature Ab Initio Molecular Dynamics

K. Jensen, H. Kulik, Lisi Xie, 2015, 1512.08565.

Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design.

H. Kulik, J. Janet, Chenru Duan, 2021, Accounts of chemical research.

Reply to "Comment on 'Evaluating Unexpectedly Short Non-covalent Distances in X-ray Crystal Structures of Proteins with Electronic Structure Analysis'"

Heather J Kulik, Helena W Qi, H. Kulik, 2019, J. Chem. Inf. Model..

Mediation of donor–acceptor distance in an enzymatic methyl transfer reaction

J. Klinman, T. Martínez, H. Kulik, 2015, Proceedings of the National Academy of Sciences.

Synthesis and Ring-Opening Metathesis Polymerization of a Strained trans-Silacycloheptene and Single-Molecule Mechanics of Its Polymer.

Jeremiah A. Johnson, H. Kulik, M. Siegler, 2023, Journal of the American Chemical Society.

An Irreversible Synthetic Route to an Ultra-Strong Two-Dimensional Polymer

Ge Zhang, A. T. Liu, M. Strano, 2021, 2103.13925.

Ab initio investigation of high multiplicity + + optical transitions in the spectra of CN and isoelectronic species

H. Kulik, R. Field, A. Steeves, 2009 .

Assessing the performance of approximate density functional theory on 95 experimentally characterized Fe(II) spin crossover complexes.

Michael G. Taylor, H. Kulik, Chenru Duan, 2023, The Journal of chemical physics.

Understanding the chemical bonding of ground and excited states of HfO and HfB with correlated wavefunction theory and density functional approximations.

H. Kulik, Chenru Duan, I. Ariyarathna, 2022, The Journal of chemical physics.

First-principles transition-metal catalysis : efficient and accurate approaches for studying enzymatic systems

Heather J Kulik, H. Kulik, 2009 .

SESAMI APP: An Accessible Interface for Surface Area Calculation of Materials from Adsorption Isotherms

H. Kulik, Li‐Chiang Lin, Archit Datar, 2023, J. Open Source Softw..

Modeling the roles of rigidity and dopants in single-atom methane-to-methanol catalysts

H. Kulik, Mingjie Liu, Haojun Jia, 2022, Journal of Materials Chemistry A.

Unraveling Polymer–Ion Interactions in Electrochromic Polymers for their Implementation in Organic Electrochemical Synaptic Devices

H. Kulik, Aristide Gumyusenge, Hang Hu, 2023, Advanced Functional Materials.

Chemical design by artificial intelligence.

H. Kulik, K. Jelfs, D. Ess, 2022, The Journal of chemical physics.

First-principles study of non-heme Fe ( II ) halogenase SyrB 2 reactivity

N. Marzari, H. Kulik, L. C. Blasiak, 2011 .

Reversible O-O Bond Scission and O2 Evolution at MOF-Supported Tetramanganese Clusters.

H. Kulik, M. Dincǎ, Tianyang Chen, 2023, Journal of the American Chemical Society.

Tailoring Dynamic Hydrogels by Controlling Associative Exchange Rates.

H. Kulik, C. Stern, J. Kalow, 2023, Chem.

Simultaneous protection of tissue physicochemical properties using polyfunctional crosslinkers

T. Golub, B. Lim, M. Frosch, 2018, Nature Biotechnology.

Predicting electronic structure properties of transition metal complexes with neural networks† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc01247k

H. Kulik, J. Janet, 2017, Chemical science.

MOFSimplify, machine learning models with extracted stability data of three thousand metal–organic frameworks

H. Kulik, Chenru Duan, N. Arunachalam, 2022, Scientific Data.

Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model

H. Kulik, Chenru Duan, Yuanqi Du, 2023, Nat. Comput. Sci..

Computational Investigation of the Interplay of Substrate Positioning and Reactivity in Catechol O-Methyltransferase

H. Kulik, E. Ioannidis, Niladri Patra, 2016, PloS one.