Heather J. Kulik

Heather J. Kulik

Associate Professor of Chemical Engineering

Massachusetts Institute of Technology

Heather J. Kulik is an Associate Professor in Chemical Engineering at MIT. She received her B.E. in Chemical Engineering from Cooper Union in 2004 and her Ph.D. in Materials Science and Engineering from MIT in 2009. She completed postdocs at Lawrence Livermore (2010) and Stanford (2010−2013), prior to returning to MIT as a faculty member in 2013 and receiving tenure in 2021.

Her work has been recognized by a Burroughs Wellcome Fund Career Award at the Scientific Interface (2012-2017), Office of Naval Research Young Investigator Award (2018), DARPA Young Faculty Award (2018), AAAS Marion Milligan Mason Award (2019-2020), NSF CAREER Award (2019), the Industrial & Engineering Chemistry Research “Class of Influential Researchers”, the ACS COMP Division OpenEye Award for Outstanding Junior Faculty in Computational Chemistry, the JPCB Lectureship (ACS PHYS), the DARPA Director’s Fellowship (2020), and a Sloan Fellowship (2021).

Interests
  • Computational Chemistry
  • Molecular Design
  • Enzymatic Catalysis
Education
  • PhD in Materials Science and Engineering, 2009

    Massachusetts Institute of Technology

  • BE in Chemical Engineering, 2004

    Massachusetts Institute of Technology

Publications

  1. A Transferable Recommender Approach for Selecting the Best Density Functional Approximations in Chemical Discovery (2022)
  2. Emergence of a Proton Exchange-Based Isomerization and Lactonization Mechanism in the Plant Coumarin Synthase COSY (2022)
  3. Insights into the Stability of Engineered Mini-Proteins from Their Dynamic Electronic Properties (2022)
  4. Self-Trapped Excitons in 2D Silver Phenylchalcogenolates (2022)
  5. Highly Efficient Bromine Capture and Storage Using N-containing Porous Organic Cages (2022)
  6. Endohedrally Functionalized Metal–Organic Cage-Cross-Linked Polymer Gels as Modular Heterogeneous Catalysts (2022)
  7. Using Computational Chemistry to Reveal Nature's Blueprints for Single-Site Catalysis of C–H Activation (2022)
  8. Mechanistic Studies of a Skatole-Forming Glycyl Radical Enzyme Suggest Reaction Initiation via Hydrogen Atom Transfer (2022)
  9. Exploiting Ligand Additivity for Transferable Machine Learning of Multireference Character Across Known Transition Metal Complex Ligands (2022)
  10. Machine learning models predict calculation outcomes with the transferability necessary for computational catalysis (2022)
  11. Mechanochemically Assisted Release of Hydrogen Fluoride and its Application in Triggered Polymer Degradation (2022)
  12. Non-native Anionic Ligand Binding and Reactivity in Engineered Variants of the Fe(II)- and α-Ketoglutarate-Dependent Oxygenase, SadA (2022)
  13. Fluids and Electrolytes under Confinement in Single-Digit Nanopores (2022)
  14. Roadmap on Machine Learning in Electronic Structure (2022)
  15. Influence of the Greater Protein Environment on the Electrostatic Potential in Metalloenzyme Active Sites: The Case of Formate Dehydrogenase (2022)
  16. What's Left for a Computational Chemist To Do in the Age of Machine Learning? (2022)
  17. Are Vanadium Intermediates Suitable Mimics in Non-Heme Iron Enzymes? An Electronic Structure Analysis (2022)
  18. Audacity of huge: overcoming challenges of data scarcity and data quality for machine learning in computational materials discovery (2022)
  19. Computational Modeling of Conformer Stability in Benenodin-1, a Thermally Actuated Lasso Peptide Switch (2022)
  20. Computational Scaling Relationships Predict Experimental Activity and Rate Limiting Behavior in Homogenous Water Oxidation (2022)
  21. Detection of multi-reference character imbalances enables a transfer learning approach for chemical discovery with coupled cluster accuracy at DFT cost (2022)
  22. Eliminating Delocalization Error to Improve Heterogeneous Catalysis Predictions with Molecular DFT+U (2022)
  23. Harder, better, faster, stronger: large-scale QM and QM/MM for predictive modeling in enzymes and proteins (2022)
  24. Large-scale Screening Reveals Geometric Structure Matters More than Electronic Structure in Bioinspired Catalyst Design of Formate Dehydrogenase Mimics (2022)
  25. Ligand Additivity and Divergent Trends in Two Types of Delocalization Errors from Approximate Density Functional Theory (2022)
  26. Machine Learning for the Discovery, Design, and Engineering of Materials (2022)
  27. Machine Learning Reveals Key Ion Selectivity Mechanisms in Polymeric Membranes (2022)
  28. Modeling the roles of rigidity and dopants in single-atom methane-to-methanol catalysts (2022)
  29. MOFSimplify, machine learning models with extracted stability data of three thousand metal–organic frameworks (2022)
  30. Molecular orbital projectors in non-empirical jmDFT recover exact conditions in transition-metal chemistry (2022)
  31. New Strategies for Direct Methane-to-Methanol Conversion from Active Learning Exploration of 16 Million Catalysts (2022)
  32. Probing the mechanism of isonitrile formation by a non-heme iron(II)-dependent oxidase/decarboxylase (2022)
  33. Quantum-Mechanical/Molecular-Mechanical (QM/MM) Simulations for Understanding Enzyme Dynamics (2022)
  34. Representations and Strategies for Transferable Machine Learning Improve Model Performance in Chemical Discovery (2022)
  35. Understanding the chemical bonding of ground and excited states of HfO and HfB with correlated wavefunction theory and density functional approximations (2022)
  36. Advancing Discovery in Chemistry with Artificial Intelligence: From Reaction Outcomes to New Materials and Catalysts (2021)
  37. Molecular DFT+U: A Transferable, Low-Cost Approach to Eliminate Delocalization Error (2021)
  38. Protein Dynamics and Substrate Protonation State Mediate the Catalytic Action of Trans-4-Hydroxy-L-Proline Dehydratase (2021)
  39. Irreversible synthesis of an ultrastrong two-dimensional polymeric material (2021)
  40. Molecular basis of C-S bond cleavage in the glycyl radical enzyme isethionate sulfite-lyase (2021)
  41. Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design (2021)
  42. Biochemical and crystallographic investigations into isonitrile formation by a nonheme iron-dependent oxidase/decarboxylase (2021)
  43. Computational Discovery of Transition-Metal Complexes: From High-throughput Screening to Machine Learning (2021)
  44. Deciphering Cryptic Behavior in Bimetallic Transition Metal Complexes with Machine Learning (2021)
  45. Machine learning to tame divergent density functional approximations a new path to consensus materials design principles (2021)
  46. Mapping the Origins of Surface- and Chemistry-Dependent Doping Trends in III-V Quantum Dots with Density Functional Theory (2021)
  47. Putting Density Functional Theory to the Test in Machine-Learning-Accelerated Materials Discovery (2021)
  48. Quantifying the Long-Range Coupling of Electronic Properties in Proteins with Ab Initio Molecular Dynamics (2021)
  49. Quantum Chemistry Common Driver and Databases (QCDB) and Quantum Chemistry Engine (QCEngine): Automation and interoperability among computational chemistry programs (2021)
  50. Spectroscopically Guided Simulations Reveal Distinct Strategies for Positioning Substrates to Achieve Selectivity in Nonheme Fe(II)/α-Ketoglutarate-Dependent Halogenases (2021)
  51. Using Machine Learning and Data Mining to Leverage Community Knowledge for the Engineering of Stable Metal-Organic Frameworks (2021)
  52. When are two hydrogen bonds better than one? Accurate first-principles models explain the balance of hydrogen bond donors and acceptors found in proteins (2021)
  53. Ionization behavior of nanoporous polyamide membranes (2020)
  54. Why Conventional Design Rules for C–H Activation Fail for Open-Shell Transition-Metal Catalysts (2020)
  55. Rapid Detection of Strong Correlation with Machine Learning for Transition-Metal Complex High-Throughput Screening (2020)
  56. Semi-supervised Machine Learning Enables the Robust Detection of Multireference Character at Low Cost (2020)
  57. Understanding the diversity of the metal-organic framework ecosystem (2020)
  58. Data-Driven Approaches Can Overcome the Cost–Accuracy Trade-Off in Multireference Diagnostics (2020)
  59. Uncovering Alternate Pathways to Nafion Membrane Degradation in Fuel Cells with First-Principles Modeling (2020)
  60. Both Configuration and QM Region Size Matter: Zinc Stability in QM/MM Models of DNA Methyltransferase (2020)
  61. Machine Learning in Chemistry (2020)
  62. Accurate Multiobjective Design in a Space of Millions of Transition Metal Complexes with Neural-Network-Driven Efficient Global Optimization (2020)
  63. Seeing Is Believing: Experimental Spin States from Machine Learning Model Structure Predictions (2020)
  64. Enumeration of de novo inorganic complexes for chemical discovery and machine learning (2020)
  65. Impact of Approximate DFT Density Delocalization Error on Potential Energy Surfaces in Transition Metal Chemistry (2020)
  66. Large-scale comparison of 3d and 4d transition metal complexes illuminates the reduced effect of exchange on second-row spin-state energetics (2020)
  67. Making machine learning a useful tool in the accelerated discovery of transition metal complexes (2020)
  68. Critical Knowledge Gaps in Mass Transport through Single-Digit Nanopores: A Review and Perspective (2019)
  69. Machine Learning Accelerates the Discovery of Design Rules and Exceptions in Stable Metal–Oxo Intermediate Formation (2019)
  70. Reply to “Comment on ‘Evaluating Unexpectedly Short Non-covalent Distances in X-ray Crystal Structures of Proteins with Electronic Structure Analysis’” (2019)
  71. Stable Surfaces That Bind Too Tightly: Can Range-Separated Hybrids or DFT+U Improve Paradoxical Descriptions of Surface Chemistry? (2019)
  72. Designing in the Face of Uncertainty: Exploiting Electronic Structure and Machine Learning Models for Discovery in Inorganic Chemistry (2019)
  73. Quantum Mechanical Description of Electrostatics Provides a Unified Picture of Catalytic Action Across Methyltransferases (2019)
  74. The Protein’s Role in Substrate Positioning and Reactivity for Biosynthetic Enzyme Complexes: The Case of SyrB2/SyrB1 (2019)
  75. Evaluating Unexpectedly Short Non-covalent Distances in X-ray Crystal Structures of Proteins with Electronic Structure Analysis (2019)
  76. Learning from Failure: Predicting Electronic Structure Calculation Outcomes with Machine Learning Models (2019)
  77. Non-empirical, low-cost recovery of exact conditions with model-Hamiltonian inspired expressions in jmDFT (2019)
  78. A quantitative uncertainty metric controls error in neural network-driven chemical discovery (2019)
  79. 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 (2019)
  80. Bridging the Homogeneous-Heterogeneous Divide: Modeling Spin for Reactivity in Single Atom Catalysis (2019)
  81. Coding solvation: challenges and opportunities (2019)
  82. Exploiting graphical processing units to enable quantum chemistry calculation of large solvated molecules with conductor-like polarizable continuum models (2019)
  83. Protection of tissue physicochemical properties using polyfunctional crosslinkers (2019)
  84. Revealing quantum mechanical effects in enzyme catalysis with large-scale electronic structure simulation (2019)
  85. Electronic Structure Origins of Surface-Dependent Growth in III–V Quantum Dots (2018)
  86. Strategies and Software for Machine Learning Accelerated Discovery in Transition Metal Chemistry (2018)
  87. When Is Ligand pKa a Good Descriptor for Catalyst Energetics? In Search of Optimal CO2 Hydration Catalysts (2018)
  88. Accelerating Chemical Discovery with Machine Learning: Simulated Evolution of Spin Crossover Complexes with an Artificial Neural Network (2018)
  89. Understanding and Breaking Scaling Relations in Single-Site Catalysis: Methane to Methanol Conversion by FeIV═O (2018)
  90. Where Does the Density Localize in the Solid State? Divergent Behavior for Hybrids and DFT+U (2018)
  91. Large-scale QM/MM free energy simulations of enzyme catalysis reveal the influence of charge transfer (2018)
  92. Modeling Mechanochemistry from First Principles (2018)
  93. Communication: Recovering the flat-plane condition in electronic structure theory at semi-local DFT cost (2017)
  94. Quantifying Electronic Effects in QM and QM/MM Biomolecular Modeling with the Fukui Function (2017)
  95. Resolving Transition Metal Chemical Space: Feature Selection for Machine Learning and Structure–Property Relationships (2017)
  96. Unifying Exchange Sensitivity in Transition-Metal Spin-State Ordering and Catalysis through Bond Valence Metrics (2017)
  97. Leveraging Cheminformatics Strategies for Inorganic Discovery: Application to Redox Potential Design (2017)
  98. Density functional theory for modelling large molecular adsorbate–surface interactions: a mini-review and worked example (2017)
  99. Harnessing Organic Ligand Libraries for First-Principles Inorganic Discovery: Indium Phosphide Quantum Dot Precursor Design Strategies (2017)
  100. Ligand-Field-Dependent Behavior of Meta-GGA Exchange in Transition-Metal Complex Spin-State Ordering (2017)
  101. Systematic Quantum Mechanical Region Determination in QM/MM Simulation (2017)
  102. Depolymerization Pathways for Branching Lignin Spirodienone Units Revealed with ab Initio Steered Molecular Dynamics (2017)
  103. Predicting electronic structure properties of transition metal complexes with neural networks (2017)
  104. Where Does the Density Localize? Convergent Behavior for Global Hybrids, Range Separation, and DFT+U (2016)
  105. How Large Should the QM Region Be in QM/MM Calculations? The Case of Catechol O-Methyltransferase (2016)
  106. Computational Discovery of Hydrogen Bond Design Rules for Electrochemical Ion Separation (2016)
  107. Computational Investigation of the Interplay of Substrate Positioning and Reactivity in Catechol O-Methyltransferase (2016)
  108. Global and local curvature in density functional theory (2016)
  109. Predicting the Stability of Fullerene Allotropes Throughout the Periodic Table (2016)
  110. Adapting DFT+U for the Chemically Motivated Correction of Minimal Basis Set Incompleteness (2016)
  111. Direct Observation of Early-Stage Quantum Dot Growth Mechanisms with High-Temperature Ab Initio Molecular Dynamics (2016)
  112. Anion-Selective Redox Electrodes: Electrochemically Mediated Separation with Heterogeneous Organometallic Interfaces (2016)
  113. molSimplify: A toolkit for automating discovery in inorganic chemistry (2016)
  114. Discovering Amorphous Indium Phosphide Nanostructures with High-Temperature ab Initio Molecular Dynamics (2015)
  115. Quantum Chemistry for Solvated Molecules on Graphical Processing Units Using Polarizable Continuum Models (2015)
  116. Towards quantifying the role of exact exchange in predictions of transition metal complex properties (2015)
  117. Ab Initio Screening Approach for the Discovery of Lignin Polymer Breaking Pathways (2015)
  118. Mediation of donor–acceptor distance in an enzymatic methyl transfer reaction (2015)
  119. Perspective: Treating electron over-delocalization with the DFT+U method (2015)
  120. Mechanically triggered heterolytic unzipping of a low-ceiling-temperature polymer (2014)
  121. Developing an approach for first-principles catalyst design: application to carbon-capture catalysis (2014)
  122. Substrate Placement Influences Reactivity in Non-heme Fe(II) Halogenases and Hydroxylases* (2013)
  123. Ab Initio Quantum Chemistry for Protein Structures (2012)
  124. Probing the Structure of Salt Water under Confinement with First-Principles Molecular Dynamics and Theoretical X-ray Absorption Spectroscopy (2012)
  125. Accurate potential energy surfaces with a DFT+U(R) approach (2011)
  126. Transition-metal dioxides: A case for the intersite term in Hubbard-model functionals (2011)
  127. Designing small-molecule catalysts for CO2 capture (2011)
  128. Modeling, synthesis and characterization of zinc containing carbonic anhydrase active site mimics (2011)
  129. Spatially Extended Kondo State in Magnetic Molecules Induced by Interfacial Charge Transfer (2010)
  130. Systematic study of first-row transition-metal diatomic molecules: A self-consistent DFT+U approach (2010)
  131. Local Effects in the X-ray Absorption Spectrum of Salt Water (2010)
  132. Electronic Structure and Reactivity of Transition Metal Complexes (2010)
  133. Ab initio investigation of high multiplicity Σ+–Σ+ optical transitions in the spectra of CN and isoelectronic species (2009)
  134. First-Principles Study of Non-heme Fe(II) Halogenase SyrB2 Reactivity (2009)
  135. A self-consistent Hubbard U density-functional theory approach to the addition-elimination reactions of hydrocarbons on bare FeO+ (2008)
  136. Density Functional Theory in Transition-Metal Chemistry: A Self-Consistent Hubbard U Approach (2006)

Posts