Heather Kulik
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American physicist
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Heather Kulikchemistry Degrees
Chemistry
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Computational Chemistry
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Chemistry Physics
Heather Kulik's Degrees
- PhD Chemical Physics California Institute of Technology
- Bachelors Chemistry University of California, Berkeley
Why Is Heather Kulik Influential?
(Suggest an Edit or Addition)According to Wikipedia, Heather J. Kulik is an American computational materials scientist and engineer who is an associate professor of chemical engineering at the Massachusetts Institute of Technology. Her research considers the computational design of new materials and the use of artificial intelligence to predict material properties.
Heather Kulik's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Density functional theory in transition-metal chemistry: a self-consistent Hubbard U approach. (2006) (409)
- Simultaneous protection of tissue physicochemical properties using polyfunctional crosslinkers (2018) (193)
- Critical Knowledge Gaps in Mass Transport through Single-Digit Nanopores: A Review and Perspective (2019) (186)
- Mechanically triggered heterolytic unzipping of a low-ceiling-temperature polymer (2014) (167)
- Understanding the diversity of the metal-organic framework ecosystem (2020) (158)
- How Large Should the QM Region Be in QM/MM Calculations? The Case of Catechol O-Methyltransferase (2015) (136)
- Resolving Transition Metal Chemical Space: Feature Selection for Machine Learning and Structure-Property Relationships. (2017) (134)
- Perspective: Treating electron over-delocalization with the DFT+U method. (2015) (128)
- Accelerating Chemical Discovery with Machine Learning: Simulated Evolution of Spin Crossover Complexes with an Artificial Neural Network. (2018) (126)
- Predicting electronic structure properties of transition metal complexes with neural networks† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc01247k (2017) (111)
- molSimplify: A toolkit for automating discovery in inorganic chemistry (2016) (100)
- Ab initio quantum chemistry for protein structures. (2012) (98)
- A quantitative uncertainty metric controls error in neural network-driven chemical discovery. (2019) (96)
- Understanding and Breaking Scaling Relations in Single-Site Catalysis: Methane to Methanol Conversion by FeIV═O (2018) (94)
- Strategies and Software for Machine Learning Accelerated Discovery in Transition Metal Chemistry (2018) (94)
- Accurate Multiobjective Design in a Space of Millions of Transition Metal Complexes with Neural-Network-Driven Efficient Global Optimization (2019) (84)
- Towards quantifying the role of exact exchange in predictions of transition metal complex properties. (2015) (82)
- Anion‐Selective Redox Electrodes: Electrochemically Mediated Separation with Heterogeneous Organometallic Interfaces (2016) (78)
- Systematic study of first-row transition-metal diatomic molecules: a self-consistent DFT+U approach. (2010) (77)
- Quantum Chemistry for Solvated Molecules on Graphical Processing Units Using Polarizable Continuum Models. (2015) (76)
- Spatially extended Kondo state in magnetic molecules induced by interfacial charge transfer. (2010) (71)
- A self-consistent Hubbard U density-functional theory approach to the addition-elimination reactions of hydrocarbons on bare FeO+. (2008) (68)
- Systematic Quantum Mechanical Region Determination in QM/MM Simulation. (2017) (67)
- Mediation of donor–acceptor distance in an enzymatic methyl transfer reaction (2015) (64)
- Designing in the Face of Uncertainty: Exploiting Electronic Structure and Machine Learning Models for Discovery in Inorganic Chemistry. (2019) (59)
- Accurate potential energy surfaces with a DFT+U(R) approach. (2011) (59)
- Computational Discovery of Transition-metal Complexes: From High-throughput Screening to Machine Learning. (2021) (58)
- Where Does the Density Localize? Convergent Behavior for Global Hybrids, Range Separation, and DFT+U. (2016) (56)
- Learning from Failure: Predicting Electronic Structure Calculation Outcomes with Machine Learning Models. (2019) (54)
- Machine Learning Accelerates the Discovery of Design Rules and Exceptions in Stable Metal–Oxo Intermediate Formation (2019) (53)
- Transition-metal dioxides: a case for the intersite term in Hubbard-model functionals. (2011) (50)
- Ionization behavior of nanoporous polyamide membranes (2020) (47)
- Where Does the Density Localize in the Solid State? Divergent Behavior for Hybrids and DFT+U. (2018) (46)
- Ligand-Field-Dependent Behavior of Meta-GGA Exchange in Transition-Metal Complex Spin-State Ordering. (2017) (45)
- First-principles study of non-heme Fe(II) halogenase SyrB2 reactivity. (2009) (44)
- Local effects in the X-ray absorption spectrum of salt water. (2010) (40)
- Global and local curvature in density functional theory. (2016) (40)
- Probing the Structure of Salt Water under Confinement with First-Principles Molecular Dynamics and Theoretical X-ray Absorption Spectroscopy. (2012) (40)
- Leveraging Cheminformatics Strategies for Inorganic Discovery: Application to Redox Potential Design (2017) (38)
- Evaluating Unexpectedly Short Non-covalent Distances in X-ray Crystal Structures of Proteins with Electronic Structure Analysis (2019) (38)
- Density functional theory for modelling large molecular adsorbate–surface interactions: a mini-review and worked example (2016) (36)
- Unifying Exchange Sensitivity in Transition-Metal Spin-State Ordering and Catalysis through Bond Valence Metrics. (2017) (34)
- Seeing Is Believing: Experimental Spin States from Machine Learning Model Structure Predictions (2020) (32)
- Substrate Placement Influences Reactivity in Non-heme Fe(II) Halogenases and Hydroxylases* (2013) (32)
- Communication: Recovering the flat-plane condition in electronic structure theory at semi-local DFT cost. (2017) (31)
- Exploiting graphical processing units to enable quantum chemistry calculation of large solvated molecules with conductor‐like polarizable continuum models (2018) (30)
- Using Machine Learning and Data Mining to Leverage Community Knowledge for the Engineering of Stable Metal-Organic Frameworks (2021) (30)
- Bridging the Homogeneous-Heterogeneous Divide: Modeling Spin for Reactivity in Single Atom Catalysis (2019) (30)
- Computational Investigation of the Interplay of Substrate Positioning and Reactivity in Catechol O-Methyltransferase (2016) (29)
- Roadmap on Machine learning in electronic structure (2022) (28)
- Large-scale QM/MM free energy simulations of enzyme catalysis reveal the influence of charge transfer. (2018) (26)
- Revealing quantum mechanical effects in enzyme catalysis with large-scale electronic structure simulation. (2018) (26)
- Machine Learning in Chemistry (2020) (25)
- Making machine learning a useful tool in the accelerated discovery of transition metal complexes (2019) (24)
- Modeling, synthesis and characterization of zinc containing carbonic anhydrase active site mimics (2011) (23)
- The Protein’s Role in Substrate Positioning and Reactivity for Biosynthetic Enzyme Complexes: The Case of SyrB2/SyrB1 (2018) (23)
- Rapid Detection of Strong Correlation with Machine Learning for Transition-Metal Complex High-Throughput Screening. (2020) (22)
- Semi-Supervised Machine Learning Enables the Robust Detection of Multireference Character at Low Cost. (2020) (22)
- Both Configuration and QM Region Size Matter: Zinc Stability in QM/MM Models of DNA Methyltransferase. (2020) (22)
- Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design. (2021) (21)
- Machine learning reveals key ion selectivity mechanisms in polymeric membranes with subnanometer pores (2022) (21)
- Stable Surfaces That Bind Too Tightly: Can Range-Separated Hybrids or DFT+U Improve Paradoxical Descriptions of Surface Chemistry? (2019) (21)
- Adapting DFT+U for the Chemically Motivated Correction of Minimal Basis Set Incompleteness. (2016) (20)
- 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. (2018) (19)
- Harnessing Organic Ligand Libraries for First-Principles Inorganic Discovery: Indium Phosphide Quantum Dot Precursor Design Strategies (2017) (19)
- Putting Density Functional Theory to the Test in Machine-Learning-Accelerated Materials Discovery (2021) (19)
- Direct Observation of Early-Stage Quantum Dot Growth Mechanisms with High-Temperature Ab Initio Molecular Dynamics (2015) (18)
- Data-Driven Approaches Can Overcome the Cost-Accuracy Trade-off in Multireference Diagnostics. (2020) (18)
- Electronic Structure Origins of Surface-Dependent Growth in III–V Quantum Dots (2018) (17)
- Harder, better, faster, stronger: Large-scale QM and QM/MM for predictive modeling in enzymes and proteins. (2021) (17)
- Designing small-molecule catalysts for CO2 capture (2011) (16)
- Quantum Mechanical Description of Electrostatics Provides a Unified Picture of Catalytic Action Across Methyltransferases. (2019) (16)
- Quantum Chemistry Common Driver and Databases (QCDB) and Quantum Chemistry Engine (QCEngine): Automation and interoperability among computational chemistry programs (2021) (15)
- Ab Initio Screening Approach for the Discovery of Lignin Polymer Breaking Pathways. (2015) (15)
- Enumeration of de novo inorganic complexes for chemical discovery and machine learning (2019) (13)
- Computational Discovery of Hydrogen Bond Design Rules for Electrochemical Ion Separation (2016) (13)
- Why Conventional Design Rules for C–H Activation Fail for Open-Shell Transition-Metal Catalysts (2020) (13)
- Impact of Approximate DFT Density Delocalization Error on Potential Energy Surfaces in Transition Metal Chemistry. (2019) (13)
- Audacity of huge: overcoming challenges of data scarcity and data quality for machine learning in computational materials discovery (2021) (12)
- Spectroscopically Guided Simulations Reveal Distinct Strategies for Positioning Substrates to Achieve Selectivity in Nonheme Fe(II)/α-Ketoglutarate-Dependent Halogenases (2021) (12)
- Depolymerization Pathways for Branching Lignin Spirodienone Units Revealed with ab Initio Steered Molecular Dynamics. (2017) (12)
- Non-empirical, low-cost recovery of exact conditions with model-Hamiltonian inspired expressions in jmDFT. (2019) (12)
- When Is Ligand p Ka a Good Descriptor for Catalyst Energetics? In Search of Optimal CO2 Hydration Catalysts. (2018) (12)
- Discovering Amorphous Indium Phosphide Nanostructures with High-Temperature ab Initio Molecular Dynamics (2015) (11)
- MOFSimplify, machine learning models with extracted stability data of three thousand metal–organic frameworks (2021) (10)
- Advancing Discovery in Chemistry with Artificial Intelligence: From Reaction Outcomes to New Materials and Catalysts. (2021) (10)
- Irreversible synthesis of an ultrastrong two-dimensional polymeric material (2022) (10)
- Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles (2021) (9)
- Molecular basis of C-S bond cleavage in the glycyl radical enzyme isethionate sulfite-lyase (2021) (9)
- Molecular DFT+U: A Transferable, Low-Cost Approach to Eliminate Delocalization Error. (2021) (8)
- When are two hydrogen bonds better than one? Accurate first-principles models explain the balance of hydrogen bond donors and acceptors found in proteins (2020) (8)
- Developing an approach for first-principles catalyst design: application to carbon-capture catalysis. (2014) (8)
- Ab initio investigation of high multiplicity + + optical transitions in the spectra of CN and isoelectronic species (2009) (8)
- Representations and Strategies for Transferable Machine Learning Models in Chemical Discovery (2021) (7)
- Predicting the Stability of Fullerene Allotropes Throughout the Periodic Table (2016) (7)
- Large-scale comparison of 3d and 4d transition metal complexes illuminates the reduced effect of exchange on second-row spin-state energetics. (2020) (6)
- Endohedrally Functionalized Metal-Organic Cage-Cross-Linked Polymer Gels as Modular Heterogeneous Catalysts. (2022) (6)
- New Strategies for Direct Methane-to-Methanol Conversion from Active Learning Exploration of 16 Million Catalysts (2022) (6)
- Biochemical and crystallographic investigations into isonitrile formation by a nonheme iron-dependent oxidase/decarboxylase (2020) (6)
- The Effect of Hartree-Fock Exchange on Scaling Relations and Reaction Energetics for C–H Activation Catalysts (2021) (5)
- Eliminating Delocalization Error to Improve Heterogeneous Catalysis Predictions with Molecular DFT + U. (2021) (5)
- Modeling the roles of rigidity and dopants in single-atom methane-to-methanol catalysts (2022) (5)
- First-principles study of non-heme Fe ( II ) halogenase SyrB 2 reactivity (2011) (4)
- Coding solvation: challenges and opportunities (2018) (4)
- What's Left for a Computational Chemist To Do in the Age of Machine Learning? (2021) (4)
- Influence of the Greater Protein Environment on the Electrostatic Potential in Metalloenzyme Active Sites: The Case of Formate Dehydrogenase. (2022) (4)
- Machine Learning for the Discovery, Design, and Engineering of Materials. (2022) (4)
- Detection of multi-reference character imbalances enables a transfer learning approach for virtual high throughput screening with coupled cluster accuracy at DFT cost (2022) (4)
- Quantifying the Long-Range Coupling of Electronic Properties in Proteins with Ab Initio Molecular Dynamics (2020) (4)
- Deciphering Cryptic Behavior in Bimetallic Transition Metal Complexes with Machine Learning (2021) (3)
- Mapping the Origins of Surface- and Chemistry-Dependent Doping Trends in III–V Quantum Dots with Density Functional Theory (2021) (3)
- Large-Scale Screening Reveals That Geometric Structure Matters More Than Electronic Structure in the Bioinspired Catalyst Design of Formate Dehydrogenase Mimics (2021) (3)
- Exploiting Ligand Additivity for Transferable Machine Learning of Multireference Character Across Known Transition Metal Complex Ligands (2022) (3)
- Electronic Structure and Reactivity of Transition Metal Complexes (2010) (2)
- Uncertain Times Call for Quantitative Uncertainty Metrics: Controlling Error in Neural Network Predictions for Chemical Discovery (2019) (2)
- MODELING MECHANOCHEMISTRY FROM FIRST PRINCIPLES (2018) (2)
- Non-Native Anionic Ligand Binding and Reactivity in Engineered Variants of the Fe(II)- and α-Ketoglutarate-Dependent Oxygenase, SadA. (2022) (2)
- Using Computational Chemistry To Reveal Nature’s Blueprints for Single-Site Catalysis of C–H Activation (2022) (2)
- Computational Modeling of Conformer Stability in Benenodin-1, a Thermally Actuated Lasso Peptide Switch. (2022) (2)
- A transferable recommender approach for selecting the best density functional approximations in chemical discovery (2022) (2)
- Understanding the chemical bonding of ground and excited states of HfO and HfB with correlated wavefunction theory and density functional approximations. (2022) (2)
- Machine learning models predict calculation outcomes with the transferability necessary for computational catalysis (2022) (2)
- Light Emission in 2D Silver Phenylchalcogenolates. (2022) (2)
- Emergence of a proton exchange-based isomerization and lactonization mechanism in the plant coumarin synthase COSY (2022) (1)
- Molecular orbital projectors in non-empirical jmDFT recover exact conditions in transition-metal chemistry. (2021) (1)
- A Database of Ultrastable MOFs Reassembled from Stable Fragments with Machine Learning Models (2022) (1)
- Efficiency and accuracy in transition-metal chemistry: a self-consistent GGA+U approach (2006) (1)
- Ligand Additivity and Divergent Trends in Two Types of Delocalization Errors from Approximate Density Functional Theory. (2022) (1)
- Liu, Luehr, Kulik, and Martínez – GPU-based PCM Calculations Quantum Chemistry for Solvated Molecules on Graphical Processing Units (GPUs) using Polarizable Continuum Models (2015) (1)
- Two Wrongs Can Make a Right: A Transfer Learning Approach for Chemical Discovery with Chemical Accuracy (2022) (1)
- Computational Scaling Relationships Predict Experimental Activity and Rate-Limiting Behavior in Homogeneous Water Oxidation. (2021) (1)
- Are Vanadium Intermediates Suitable Mimics in Non-Heme Iron Enzymes? An Electronic Structure Analysis (2022) (1)
- Uncovering Alternate Pathways to Nafion Membrane Degradation in Fuel Cells with First-Principles Modeling (2020) (1)
- Reply to "Comment on 'Evaluating Unexpectedly Short Non-covalent Distances in X-ray Crystal Structures of Proteins with Electronic Structure Analysis'" (2019) (1)
- Insights into the stability of engineered mini-proteins from their dynamic electronic properties (2022) (1)
- Influence of the Greater Protein Environment on the Electrostatic Potential in Metalloenzyme Active Sites: the Case of Formate Dehydrogenase (2021) (1)
- MOFSimplify, machine learning models with extracted stability data of three thousand metal–organic frameworks (2022) (1)
- Remolding and Deconstruction of Industrial Thermosets via Carboxylic Acid-Catalyzed Bifunctional Silyl Ether Exchange. (2023) (1)
- Encontro de Outono da SBF 2018 / ID: 510-1 1 Electronic transport properties of graphene in different aqueous solutions (2018) (0)
- Spin-Delocalization in Molecular Orbital Kondo Resonance (2010) (0)
- Probing the Structure of Salt Water Under Confinement with Computation (2013) (0)
- Quantum-Mechanical/Molecular-Mechanical (QM/MM) Simulations for Understanding Enzyme Dynamics. (2021) (0)
- Insights into the deviation from piecewise linearity in transition metal complexes from supervised machine learning models. (2023) (0)
- Highly Efficient Bromine Capture and Storage Using N-containing Porous Organic Cages (2022) (0)
- Accurate binding curves in transition-metal molecules using a DFT plus U(R) approach (2010) (0)
- Artificial intelligence in computational materials science (2022) (0)
- Ab initio investigation of high multiplicity Rþ—Rþ [sigma superscript + - sigma superscript +] optical transitions in the spectra of CN and isoelectronic species (2009) (0)
- Chemical design by artificial intelligence. (2022) (0)
- DFT-Based Multireference Diagnostics in the Solid State: Application to Metal-Organic Frameworks. (2022) (0)
- Understanding the Role of Geometric and Electronic Structure in Bioinspired Catalyst Design: the Case of Formate Dehydrogenase (2021) (0)
- Enumeration of de novo inorganic complexes for chemical discovery and machine learning (2019) (0)
- Final Technical Report (2022) (0)
- Ab Initio Quantum Chemistry for Protein Structures B (2012) (0)
- An Irreversible Synthetic Route to an Ultra-Strong Two-Dimensional Polymer (2021) (0)
- Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model (2023) (0)
- PUTTING DENSITY FUNCTIONAL THEORY TO THE TEST WITH MACHINE LEARNING (2022) (0)
- Local Effects in the X-ray Absorption Spectrum of CaCl2, MgCl2, and NaCl Solutions (2010) (0)
- Mechanistic Insights into Substrate Positioning That Distinguish Non-heme Fe(II)/α-Ketoglutarate-Dependent Halogenases and Hydroxylases (2023) (0)
- First-Principles Study of Non-Heme Fe(II) Halogenase SyrB2 Reactivity (2010) (0)
- Ligand additivity relationships enable efficient exploration of transition metal chemical space. (2022) (0)
- Mapping the Electronic Structure Origins of Surface- and Chemistry-Dependent Doping Trends in III-V Quantum Dots (2021) (0)
- Accelerating inorganic discovery with meta-calculation filtering via a decision classifier (2019) (0)
- Low-cost machine learning approach to the prediction of transition metal phosphor excited state properties (2022) (0)
- New tools for detecting strong correlation in automated transition metal complex screening (2020) (0)
- Accurate binding energies in transition-metal molecules using a position-dependent GGA+U(R) approach (2010) (0)
- Redox Electrodes: Anion‐Selective Redox Electrodes: Electrochemically Mediated Separation with Heterogeneous Organometallic Interfaces (Adv. Funct. Mater. 20/2016) (2016) (0)
- 1D Hybrid Semiconductor Silver 2,6-Difluorophenylselenolate. (2023) (0)
- Improving electronic structure methods to predict nano-optoelectronics and nano-catalyst functions. (2009) (0)
- Ab-initio calculations on the energetics of H-2 oxidation by FeO+ using GGA+U (2005) (0)
- Challenges and advances in large-scale DFT calculations on GPUs (2014) (0)
- A GGA+U approach to realistic modeling of transition-metal complexes (2008) (0)
- Rapid Exploration of a 32.5M Compound Chemical Space with Active Learning to Discover Density Functional Approximation Insensitive and Synthetically Accessible Transitional Metal Chromophores (2022) (0)
- Computational Modeling of Conformer Stability in Benenodin-1, A Thermally-Actuated Lasso Peptide Switch (2022) (0)
- Peptide Bond Cleavage through Asparagine Cyclization (2015) (0)
- Enumeration of de novo Inorganic Complexes for Chemical Discovery and Machine Learning (2019) (0)
- Computational design of organic molecules for reducing friction at the nanoscale (2019) (0)
- First-principles transition-metal catalysis : efficient and accurate approaches for studying enzymatic systems (2009) (0)
- When Is Ligand pK[subscript a] a Good Descriptor for Catalyst Energetics? In Search of Optimal CO₂ Hydration Catalysts (2018) (0)
- Excitonic light emission in 2D silver phenylchalcogenolates (2022) (0)
- Low-cost machine learning prediction of excited state properties of iridium-centered phosphors (2023) (0)
- Topical Plenary: Topical Conference in Molecular and Materials Data Science (Invited Talks) (2019) (0)
- TDDFT+{\it U} for transition-metal complexes (2009) (0)
- Protein Dynamics and Substrate Protonation States Mediate the Catalytic Action of trans-4-Hydroxy-l-Proline Dehydratase. (2021) (0)
- Isonitrile Formation by a Non-heme Iron(II)-dependent Oxidase/Decarboxylase (2018) (0)
- Accurate potential energy surfaces for transition-metal complexes with DFT+U(R) (2012) (0)
- New discovery tools for molecular materials design (2017) (0)
- CHAPTER 14 Electronic Structure and Reactivity of Transition Metal Complexes (2010) (0)
- Active Learning Exploration of Transition-Metal Complexes to Discover Method-Insensitive and Synthetically Accessible Chromophores (2022) (0)
- Effects of MOF linker rotation and functionalization on methane uptake and diffusion (2023) (0)
- Revealing Substrate Positioning Dynamics in Non-heme Fe(II)/αKG-dependent Halogenases Through Spectroscopically Guided Simulation (2021) (0)
- Synthesis and Ring-Opening Metathesis Polymerization of a Strained trans-Silacycloheptene and Single-Molecule Mechanics of Its Polymer. (2023) (0)
- Data-Driven Approaches Can Overcome Limitations in Multireference Diagnostics (2020) (0)
- PHYS 400-A self-consistent Hubbard U approach to transition metal chemistry (2007) (0)
- Fluids and Electrolytes under Confinement in Single-Digit Nanopores (2023) (0)
- Mechanistic Studies of a Skatole-Forming Glycyl Radical Enzyme Suggest Reaction Initiation via Hydrogen Atom Transfer (2022) (0)
- Cover Feature: Quantifying the Long‐Range Coupling of Electronic Properties in Proteins with ab initio Molecular Dynamics (Chemistry ‐ Methods 8/2021)** (2021) (0)
- Accurate electronic-structure description of Mn complexes: a GGA+U approach (2008) (0)
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