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

Nandy, Aditya, Duan, Chenru, Taylor, Michael G., Liu, Fang, Steeves, Adam H., Kulik, Heather J.·2021·Chemical Reviews
DOI 10.1021/acs.chemrev.1c00347

Cites (718)

Items 201–400 of 716

  1. The Development of Multidimensional Analysis Tools for Asymmetric Catalysis and Beyond
    Sigman, Matthew S., Harper, Kaid C., Bess, Elizabeth N., Milo, Anat · 2016 · Accounts of Chemical Research
  2. Inverse design of porous materials using artificial neural networks
    Baekjun Kim, Sangwon Lee, Jihan Kim · 2020 · Science Advances
  3. Semiempirical quantum–chemical methods
    Walter Thiel · 2013 · Wiley Interdisciplinary Reviews Computational Molecular Science
  4. Gold Atoms Stabilized on Various Supports Catalyze the Water–Gas Shift Reaction
    Maria Flytzani‐Stephanopoulos · 2013 · Accounts of Chemical Research
  5. Machine learning meets continuous flow chemistry: Automated optimization towards the Pareto front of multiple objectives
    Artur M. Schweidtmann, Adam D. Clayton, Nicholas Holmes, Eric Christopher Bradford, Richard A. Bourne, Alexei A. Lapkin · 2018 · Chemical Engineering Journal
  6. Differences between the four halide ligands, and discussion remarks on trigonal-bipyramidal complexes, on oxidation states, and on diagonal elements of one-electron energy
    Chr. Klixbüll Jørgensen · 1966 · Coordination Chemistry Reviews
  7. New diagnostics for coupled-cluster and Møller–Plesset perturbation theory
    Curtis L. Janssen, Ida M. B. Nielsen · 1998 · Chemical Physics Letters
  8. Patterns of organometallic reactions related to homogeneous catalysis
    James P. Collman · 1968 · Accounts of Chemical Research
  9. Evaluating topologically diverse metal–organic frameworks for cryo-adsorbed hydrogen storage
    Gómez-Gualdrón, Diego A., Colón, Yamil J., Zhang, Xu, Wang, Timothy C., Chen, Yu-Sheng, Hupp, Joseph T., Yildirim, Taner, Farha, Omar K., Zhang, Jian, Snurr, Randall Q. · 2016 · Energy & Environmental Science
  10. Generative adversarial networks (GAN) based efficient sampling of chemical composition space for inverse design of inorganic materials
    Yabo Dan, Yong Zhao, Xiang Li, Shaobo Li, Ming Hu, Jianjun Hu · 2020 · npj Computational Materials
  11. Multireference Character for 3d Transition-Metal-Containing Molecules
    Wanyi Jiang, Nathan J. DeYonker, Angela K. Wilson · 2011 · Journal of Chemical Theory and Computation
  12. Artificial Chemist: An Autonomous Quantum Dot Synthesis Bot
    Robert W. Epps, Michael Bowen, Amanda A. Volk, Kameel Abdel‐Latif, Suyong Han, Kristofer G. Reyes, Aram Amassian, Milad Abolhasani · 2020 · Advanced Materials
  13. Automated Selection of Active Orbital Spaces
    Christopher Johannes Stein, Markus Reiher · 2016 · Journal of Chemical Theory and Computation
  14. In silico discovery of metal-organic frameworks for precombustion CO <sub>2</sub> capture using a genetic algorithm
    Chung, Yongchul G., Gómez-Gualdrón, Diego A., Li, Peng, Leperi, Karson T., Deria, Pravas, Zhang, Hongda, Vermeulen, Nicolaas A., Stoddart, J. Fraser, You, Fengqi, Hupp, Joseph T. et al. · 2016 · Science Advances
  15. Topologically Guided, Automated Construction of Metal–Organic Frameworks and Their Evaluation for Energy-Related Applications
    Colón, Yamil J., Gómez-Gualdrón, Diego A., Snurr, Randall Q. · 2017 · Crystal Growth &amp; Design
  16. TeraChem : A graphical processing unit ‐accelerated electronic structure package for large‐scale ab initio molecular dynamics
    Stefan Seritan, Christoph Bannwarth, B. Scott Fales, Edward G. Hohenstein, Christine M. Isborn, Sara I. L. Kokkila-Schumacher, Xin Li, Fang Liu, Nathan Luehr, James W. Snyder et al. · 2020 · Wiley Interdisciplinary Reviews Computational Molecular Science
  17. Optimizing the density-matrix renormalization group method using quantum information entropy
    Örs Legeza, Jenő Sólyom · 2003 · Physical review. B, Condensed matter
  18. Perspective: Kohn-Sham density functional theory descending a staircase
    Haoyu S. Yu, Shaohong L. Li, Donald G. Truhlar · 2016 · The Journal of Chemical Physics
  19. Statistical Improvement Criteria for Use in Multiobjective Design Optimization
    Andy J. Keane · 2006 · AIAA Journal
  20. Carbon–hydrogen (C–H) bond activation at Pd IV : a Frontier in C–H functionalization catalysis
    Joseph J. Topczewski, Melanie Sarah Sanford · 2014 · Chemical Science
  21. Calculation of One-Electron Redox Potentials Revisited. Is It Possible to Calculate Accurate Potentials with Density Functional Methods?
    Lindsay E. Roy, Elena Jakubı́ková, M. Graham Guthrie, Enrique R. Batista · 2009 · The Journal of Physical Chemistry A
  22. CO Adsorption and Oxidation on Ceria Surfaces from DFT+U Calculations
    Min Huang, Stefano Fabris · 2008 · The Journal of Physical Chemistry C
  23. COMBO: An efficient Bayesian optimization library for materials science
    Tsuyoshi Ueno, Trevor David Rhone, Zhufeng Hou, Teruyasu Mizoguchi, Koji Tsuda · 2016 · Materials Discovery
  24. Energy-based descriptors to rapidly predict hydrogen storage in metal–organic frameworks
    Bucior, Benjamin J., Bobbitt, N. Scott, Islamoglu, Timur, Goswami, Subhadip, Gopalan, Arun, Yildirim, Taner, Farha, Omar K., Bagheri, Neda, Snurr, Randall Q. · 2019 · Molecular Systems Design &amp; Engineering
  25. ANI-1, A data set of 20 million calculated off-equilibrium conformations for organic molecules
    Justin S. Smith, Olexandr Isayev, Adrián E. Roitberg · 2017 · Scientific Data
  26. Molecular Engineering of Octupolar NLO Molecules and Materials Based on Bipyridyl Metal Complexes
    Olivier Maury, Hubert Le Bozec · 2005 · Accounts of Chemical Research
  27. A Practicable Real‐Space Measure and Visualization of Static Electron‐Correlation Effects
    Stefan Grimme, Andreas Hansen · 2015 · Angewandte Chemie International Edition
  28. Density functionals that are one- and two- are not always many-electron self-interaction-free, as shown for H2+, He2+, LiH+, and Ne2+
    Adrienn Ruzsinszky, John P. Perdew, Gábor I. Csonka, Oleg A. Vydrov, Gustavo E. Scuseria · 2007 · The Journal of Chemical Physics
  29. Rapid and Accurate Machine Learning Recognition of High Performing Metal Organic Frameworks for CO2 Capture
    Michael Fernández, Peter G. Boyd, Thomas D. Daff, Mohammad Zein Aghaji, Tom K. Woo · 2014 · The Journal of Physical Chemistry Letters
  30. Delocalization Error and “Functional Tuning” in Kohn–Sham Calculations of Molecular Properties
    Jochen Autschbach, Monika Srebro‐Hooper · 2014 · Accounts of Chemical Research
  31. Stochastic Voyages into Uncharted Chemical Space Produce a Representative Library of All Possible Drug-Like Compounds
    Virshup, Aaron M., Contreras-García, Julia, Wipf, Peter, Yang, Weitao, Beratan, David N. · 2013 · Journal of the American Chemical Society
  32. Spectroscopic investigations of excited states of transition-metal complexes
    G. A. Crosby · 1975 · Accounts of Chemical Research
  33. Resolving Transition Metal Chemical Space: Feature Selection for Machine Learning and Structure–Property Relationships
    Janet, Jon Paul, Kulik, Heather J. · 2017 · The Journal of Physical Chemistry A
  34. Comprehensive Thermochemical Benchmark Set of Realistic Closed-Shell Metal Organic Reactions
    Sebastian Dohm, Andreas Hansen, Marc Steinmetz, Stefan Grimme, Marek P. Chęciński · 2018 · Journal of Chemical Theory and Computation
  35. A Machine Learning Approach to Zeolite Synthesis Enabled by Automatic Literature Data Extraction
    Zach Jensen, Edward Kim, Soonhyoung Kwon, Terry Z. H. Gani, Yuriy Román‐Leshkov, Manuel Moliner, Avelino Corma, Elsa Olivetti · 2019 · ACS Central Science
  36. Modeling Metal-Catalyzed Olefin Polymerization
    Anthony K. Rappé, W. M. Skiff, C. J. Casewit · 2000 · Chemical Reviews
  37. Free Energy of Spin-Crossover Complexes Calculated with Density Functional Methods
    Hauke Paulsen, Lars Duelund, Heiner WINKLER, Hans Toftlund, Alfred Xaver TRAUTWEIN · 2001 · Inorganic Chemistry
  38. Fractional spins and static correlation error in density functional theory
    Aron J. Cohen, Paula Mori‐Sánchez, Weitao Yang · 2008 · The Journal of Chemical Physics
  39. Genetic algorithms for computational materials discovery accelerated by machine learning
    Jennings, Paul C., Lysgaard, Steen, Hummelshøj, Jens Strabo, Vegge, Tejs, Bligaard, Thomas · 2019 · npj Computational Materials
  40. Measuring orbital interaction using quantum information theory
    Jörg Rissler, R. M. Noack, Steven R. White · 2005 · Chemical Physics
  41. Spin-crossover in cobalt(II) imine complexes
    Itana Krivokapic̃, Mohamed Zerara, Latévi Max Lawson Daku, Alfredo Vargas, Cristian Enachescu, C. Ambrus, Philip L. W. Tregenna‐Piggott, Nahid Amstutz, Elmars Krausz, Andreas Hauser · 2006 · Coordination Chemistry Reviews
  42. Feedback in Flow for Accelerated Reaction Development
    Brandon J. Reizman, Klavs F. Jensen · 2016 · Accounts of Chemical Research
  43. Deoxyfluorination with Sulfonyl Fluorides: Navigating Reaction Space with Machine Learning
    Matthew K. Nielsen, Derek T. Ahneman, Orestes Riera, Abigail G. Doyle · 2018 · Journal of the American Chemical Society
  44. Capturing chemical intuition in synthesis of metal-organic frameworks
    Moosavi, Seyed Mohamad, Chidambaram, Arunraj, Talirz, Leopold, Haranczyk, Maciej, Stylianou, Kyriakos C., Smit, Berend · 2019 · Nature Communications
  45. Machine Learning Using Combined Structural and Chemical Descriptors for Prediction of Methane Adsorption Performance of Metal Organic Frameworks (MOFs)
    Pardakhti, Maryam, Moharreri, Ehsan, Wanik, David, Suib, Steven L., Srivastava, Ranjan · 2017 · ACS Combinatorial Science
  46. A self optimizing synthetic organic reactor system using real-time in-line NMR spectroscopy
    Víctor Sans, Luzian Porwol, Vincenza Dragone, Leroy Cronin · 2014 · Chemical Science
  47. Computed Ligand Electronic Parameters from Quantum Chemistry and Their Relation to Tolman Parameters, Lever Parameters, and Hammett Constants
    Lionel Perrin, Eric Clot, Odile Eisenstein, Jennifer A. Loch, Robert H. Crabtree · 2001 · Inorganic Chemistry
  48. Parameter Calibration of Transition-Metal Elements for the Spin-Polarized Self-Consistent-Charge Density-Functional Tight-Binding (DFTB) Method: Sc, Ti, Fe, Co, and Ni
    Guishan Zheng, Henryk A. Witek, Petia Bobadova‐Parvanova, Stephan Irle, Djamaladdin G. Musaev, Rajeev S. Prabhakar, Keiji Morokuma, Marcus Lundberg, Marcus Elstner, Christof Köhler et al. · 2007 · Journal of Chemical Theory and Computation
  49. Identification Schemes for Metal–Organic Frameworks To Enable Rapid Search and Cheminformatics Analysis
    Benjamin J. Bucior, Andrew Rosen, Maciej Harańczyk, Zhenpeng Yao, Michael E. Ziebel, Omar K. Farha, Joseph T. Hupp, Joern Ilja Siepmann, Alán Aspuru‐Guzik, Randall Q. Snurr · 2019 · Crystal Growth & Design
  50. Addressing Challenges of Identifying Geometrically Diverse Sets of Crystalline Porous Materials
    Richard Luis Martin, Berend Smit, Maciej Harańczyk · 2011 · Journal of Chemical Information and Modeling
  51. How to select active space for multiconfigurational quantum chemistry?
    Valera Veryazov, Per‐Åke Malmqvist, Björn Olof Roos · 2011 · International Journal of Quantum Chemistry
  52. Computational characterization and prediction of metal–organic framework properties
    François‐Xavier Coudert, Alain H. Fuchs · 2015 · Coordination Chemistry Reviews
  53. Autonomous Discovery in the Chemical Sciences Part II: Outlook
    Connor W. Coley, Natalie S. Eyke, Klavs F. Jensen · 2019 · Angewandte Chemie International Edition
  54. Ab initio evaluation of Coulomb and exchange parameters for DFT + U calculations
    Nicholas J. Mosey, Emily A. Carter · 2007 · Physical Review B
  55. Extension of the Universal Force Field for Metal–Organic Frameworks
    Damien E. Coupry, Matthew A. Addicoat, Thomas Heine · 2016 · Journal of Chemical Theory and Computation
  56. A quantitative uncertainty metric controls error in neural network-driven chemical discovery
    Janet, Jon Paul, Duan, Chenru, Yang, Tzuhsiung, Nandy, Aditya, Kulik, Heather J. · 2019 · Chemical Science
  57. Role of Pore Chemistry and Topology in the CO 2 Capture Capabilities of MOFs: From Molecular Simulation to Machine Learning
    Ryther Anderson, Jacob Rodgers, Edwin Argueta, Achay Biong, Diego A. Gómez‐Gualdrón · 2018 · Chemistry of Materials
  58. How to explore chemical space using algorithms and automation
    Piotr S. Gromski, Alon Henson, Jarosław M. Granda, Leroy Cronin · 2019 · Nature Reviews Chemistry
  59. Novel Hydroformylation catalysts
    Lynn H. Slaugh, Richard D. Mullineaux · 1968 · Journal of Organometallic Chemistry
  60. Calculation of Redox Potentials and pKaValues of Hydrated Transition Metal Cations by a Combined Density Functional and Continuum Dielectric Theory
    Jian Li, Cindy L. Fisher, Jun L. Chen, Donald Bashford, Louis Noodleman · 1996 · Inorganic Chemistry
  61. molSimplify: A toolkit for automating discovery in inorganic chemistry
    Efthymios I. Ioannidis, Terry Z. H. Gani, Heather J. Kulik · 2016 · Journal of Computational Chemistry
  62. Quantum machine learning using atom-in-molecule-based fragments selected on the fly
    Bing Huang, O. Anatole von Lilienfeld · 2020 · Nature Chemistry
  63. A Shape Index from Molecular Graphs
    Lemont B. Kier · 1985 · Quantitative Structure-Activity Relationships
  64. New Benchmark Set of Transition-Metal Coordination Reactions for the Assessment of Density Functionals
    Thomas Weymuth, Erik P. A. Couzijn, Peter Chen, Markus Reiher · 2014 · Journal of Chemical Theory and Computation
  65. Automated Construction of Molecular Active Spaces from Atomic Valence Orbitals
    Elvira R. Sayfutyarova, Qiming Sun, Garnet Kin‐Lic Chan, Gerald Knizia · 2017 · Journal of Chemical Theory and Computation
  66. Computational Design of Metal–Organic Frameworks Based on Stable Zirconium Building Units for Storage and Delivery of Methane
    Diego A. Gómez‐Gualdrón, Oleksii V. Gutov, Vaiva Krungleviciute, Bhaskarjyoti Borah, Joseph E. Mondloch, Joseph T. Hupp, Taner Yildirim, Omar K. Farha, Randall Q. Snurr · 2014 · Chemistry of Materials
  67. Thermally Activated Delayed Fluorescence (TADF) and Enhancing Photoluminescence Quantum Yields of [Cu I (diimine)(diphosphine)] + Complexes—Photophysical, Structural, and Computational Studies
    Charlotte Linfoot, Markus J. Leitl, P. Richardson, Andreas F. Rausch, Oleg Chepelin, Fraser White, Hartmut Yersin, Neil Robertson · 2014 · Inorganic Chemistry
  68. Design and Optimization of Catalysts Based on Mechanistic Insights Derived from Quantum Chemical Reaction Modeling
    Seihwan Ahn, Mannkyu Hong, Mahesh Sundararajan, Daniel H. Ess, Mu‐Hyun Baik · 2019 · Chemical Reviews
  69. A Fully Integrated High-Throughput Screening Methodology for the Discovery of New Polyolefin Catalysts: Discovery of a New Class of High Temperature Single-Site Group (IV) Copolymerization Catalysts
    Thomas R. Boussie, Gary M. Diamond, Christopher Goh, Keith A. Hall, Anne M. LaPointe, Margarete K. Leclerc, Cheryl Lund, Vince Murphy, James A. W. Shoemaker, Ursula Tracht et al. · 2003 · Journal of the American Chemical Society
  70. Anthropogenic biases in chemical reaction data hinder exploratory inorganic synthesis
    Jia, Xiwen, Lynch, Allyson, Huang, Yuheng, Danielson, Matthew, Lang’at, Immaculate, Milder, Alexander, Ruby, Aaron E., Wang, Hao, Friedler, Sorelle A., Norquist, Alexander J. et al. · 2019 · Nature
  71. Perspective: Treating electron over-delocalization with the DFT+U method
    Heather J. Kulik · 2015 · The Journal of Chemical Physics
  72. Targeted classification of metal–organic frameworks in the Cambridge structural database (CSD)
    Peyman Z. Moghadam, Aurelia Li, Xiaowei Liu, Rocío Bueno-Pérez, Shudong Wang, Seth B. Wiggin, P.A. Wood, David Fairen‐Jiménez · 2020 · Chemical Science
  73. Transferability in Machine Learning for Electronic Structure via the Molecular Orbital Basis
    Matthew Welborn, Lixue Cheng, Thomas F. Miller · 2018 · Journal of Chemical Theory and Computation
  74. Separating Innocence and Non-Innocence of Ligands and Metals in Complexes [(L)Ru(acac)2]n (n = −1, 0, +1; L = o-Iminoquinone or o-Iminothioquinone)
    Srikanta Patra, Biprajit Sarkar, Shaikh Md. Mobin, Wolfgang Kaim, Goutam Kumar Lahiri · 2003 · Inorganic Chemistry
  75. Quantitative Structure−Activity Relationships of Ruthenium Catalysts for Olefin Metathesis
    Giovanni Occhipinti, Hans‐René Bjørsvik, Vidar Remi Jensen · 2006 · Journal of the American Chemical Society
  76. Quantitative Structure–Selectivity Relationships in Enantioselective Catalysis: Past, Present, and Future
    Zahrt, Andrew F., Athavale, Soumitra V., Denmark, Scott E. · 2020 · Chemical Reviews
  77. Low-temperature lifetimes of metastable high-spin states in spin-crossover and in low-spin iron(II) compounds: The rule and exceptions to the rule
    Andreas Hauser, Cristian Enachescu, Latévi Max Lawson Daku, Alfredo Vargas, Nahid Amstutz · 2006 · Coordination Chemistry Reviews
  78. Machine learning meets volcano plots: computational discovery of cross-coupling catalysts
    Meyer, Benjamin, Sawatlon, Boodsarin, Heinen, Stefan, von Lilienfeld, O. Anatole, Corminboeuf, Clémence · 2018 · Chemical Science
  79. Bayesian Error Estimation in Density-Functional Theory
    Mortensen, J. J., Kaasbjerg, K., Frederiksen, S. L., Nørskov, J. K., Sethna, J. P., Jacobsen, K. W. · 2005 · Physical Review Letters
  80. Absorption Spectra of Co-ordination Compounds. I
    Ryutaro Tsuchida · 1938 · Bulletin of the Chemical Society of Japan
  81. MOF‐FF – A flexible first‐principles derived force field for metal‐organic frameworks
    Sareeya Bureekaew, Saeed Amirjalayer, Maxim A. Tafipolsky, Christian Spickermann, Tapta Kanchan Roy, Rochus Schmid · 2013 · physica status solidi (b)
  82. Computation and Experiment: A Powerful Combination to Understand and Predict Reactivities
    Theresa Sperger, Italo A. Sanhueza, Franziska Schoenebeck · 2016 · Accounts of Chemical Research
  83. Search for Catalysts by Inverse Design: Artificial Intelligence, Mountain Climbers, and Alchemists
    Jessica G. Freeze, H. Ray Kelly, Víctor S. Batista · 2019 · Chemical Reviews
  84. All-Valence Electron CNDO Calculations on Transition Metal Complexes
    Dennis W. Clack, Noel S. Hush, John R. Yandle · 1972 · The Journal of Chemical Physics
  85. Comparative assessment of density functional methods for 3d transition-metal chemistry
    Yan Zhao, Donald G. Truhlar · 2006 · The Journal of Chemical Physics
  86. Discovery and Optimization of Materials Using Evolutionary Approaches
    Le, Tu C., Winkler, David A. · 2016 · Chemical Reviews
  87. Accelerating Chemical Discovery with Machine Learning: Simulated Evolution of Spin Crossover Complexes with an Artificial Neural Network
    Janet, Jon Paul, Chan, Lydia, Kulik, Heather J. · 2018 · The Journal of Physical Chemistry Letters
  88. Accurate Multiobjective Design in a Space of Millions of Transition Metal Complexes with Neural-Network-Driven Efficient Global Optimization
    Janet, Jon Paul, Ramesh, Sahasrajit, Duan, Chenru, Kulik, Heather J. · 2020 · ACS Central Science
  89. Predicting electronic structure properties of transition metal complexes with neural networks
    Janet, Jon Paul, Kulik, Heather J. · 2017 · Chemical Science
  90. Transition metal complexes with strong absorption of visible light and long-lived triplet excited states: from molecular design to applications
    Jianzhang Zhao, Shaomin Ji, Wanhua Wu, Wenting Wu, Huimin Guo, Jifu Sun, Haiyang Sun, Yifan Liu, Qiuting Li, Ling Feng Huang · 2011 · RSC Advances
  91. Second-order Mo/ller–Plesset perturbation theory as a configuration and orbital generator in multiconfiguration self-consistent field calculations
    Hans Jørgen Aa. Jensen, Poul Jo rgensen, Hans Ågren, Jeppe Olsen · 1988 · The Journal of Chemical Physics
  92. Calculating Free Energy Changes in Continuum Solvation Models
    Junming Ho, Mehmed Z. Ertem · 2016 · The Journal of Physical Chemistry B
  93. Low-Scaling Algorithm for Nudged Elastic Band Calculations Using a Surrogate Machine Learning Model
    José Antonio Garrido Torres, Paul C. Jennings, Martin Hangaard Hansen, Jacob R. Boes, Thomas Bligaard · 2019 · Physical Review Letters
  94. Structural systematics: the role of P-A .sigma.* orbitals in metal-phosphorus .pi.-bonding in redox-related pairs of M-PA3 complexes (A = R, Ar, OR; R = alkyl)
    A. Guy. Orpen, Neil G. Connelly · 1990 · Organometallics
  95. Shedding Light on the Single-Molecule Magnet Behavior of Mononuclear DyIII Complexes
    Daniel Aravena, Eliseo Ruíz · 2013 · Inorganic Chemistry
  96. Virtual screening of inorganic materials synthesis parameters with deep learning
    Kim, Edward, Huang, Kevin, Jegelka, Stefanie, Olivetti, Elsa · 2017 · npj Computational Materials
  97. Configuring Bonds between First-Row Transition Metals
    Reed J. Eisenhart, Laura J. Clouston, Connie C. Lu · 2015 · Accounts of Chemical Research
  98. Conformational Effects on Physical-Organic Descriptors: The Case of Sterimol Steric Parameters
    Alexandre V. Brethomé, Stephen P. Fletcher, Robert S. Paton · 2019 · ACS Catalysis
  99. Automated in Silico Design of Homogeneous Catalysts
    Marco Foscato, Vidar Remi Jensen · 2020 · ACS Catalysis
  100. Chemically intuited, large-scale screening of MOFs by machine learning techniques
    Giorgos Borboudakis, Taxiarchis Stergiannakos, Maria G. Frysali, Emmanuel Klontzas, Ioannis Tsamardinos, George E. Froudakis · 2017 · npj Computational Materials
  101. Computational Discovery of New Zeolite-Like Materials
    Deem, Michael W., Pophale, Ramdas, Cheeseman, Phillip A., Earl, David J. · 2009 · The Journal of Physical Chemistry C
  102. Density functional tight binding: application to organic and biological molecules
    Michael Gaus, Q. Cui, M. Elstner · 2014 · Wiley Interdisciplinary Reviews Computational Molecular Science
  103. Opportunities and challenges of text mining in materials research
    Kononova, Olga, He, Tanjin, Huo, Haoyan, Trewartha, Amalie, Olivetti, Elsa A., Ceder, Gerbrand · 2021 · iScience
  104. A Universal Machine Learning Algorithm for Large-Scale Screening of Materials
    Fanourgakis, George S., Gkagkas, Konstantinos, Tylianakis, Emmanuel, Froudakis, George E. · 2020 · Journal of the American Chemical Society
  105. Evaluating Transition Metal Barrier Heights with the Latest Density Functional Theory Exchange–Correlation Functionals: The MOBH35 Benchmark Database
    Mark A. Iron, Trevor Janes · 2019 · The Journal of Physical Chemistry A
  106. Spin Crossover – Quo Vadis?
    Philipp Gütlich · 2013 · European Journal of Inorganic Chemistry
  107. Machine learning dihydrogen activation in the chemical space surrounding Vaska's complex
    Friederich, Pascal, dos Passos Gomes, Gabriel, De Bin, Riccardo, Aspuru-Guzik, Alán, Balcells, David · 2020 · Chemical Science
  108. Density functionals for static, dynamical, and strong correlation
    Axel D. Becke · 2013 · The Journal of Chemical Physics
  109. Entanglement Measures for Single- and Multireference Correlation Effects
    Katharina Bogusławski, Paweł Tecmer, Örs Legeza, Markus Reiher · 2012 · The Journal of Physical Chemistry Letters
  110. Comparison of density functionals for energy and structural differences between the high- [5T2g: (t2g)4(eg)2] and low- [1A1g: (t2g)6(eg)] spin states of the hexaquoferrous cation [Fe(H2O)6]2+
    Antony Fouqueau, Sébastien Mer, Mark E. Casida, Latévi Max Lawson Daku, Andreas Hauser, Tzonka Mineva, Frank Neese · 2004 · The Journal of Chemical Physics
  111. Toward a Database of Hypothetical Zeolite Structures
    David J. Earl, Michael W. Deem · 2006 · Industrial & Engineering Chemistry Research
  112. Spinning around in Transition-Metal Chemistry
    Marcel Swart, Maja Gruden · 2016 · Accounts of Chemical Research
  113. Addressing uncertainty in atomistic machine learning
    Andrew A. Peterson, Rune Christensen, Alireza Khorshidi · 2017 · Physical Chemistry Chemical Physics
  114. Multi-objective Optimization for Materials Discovery via Adaptive Design
    Abhijith Gopakumar, Prasanna V. Balachandran, Dezhen Xue, James E. Gubernatis, Turab Lookman · 2018 · Scientific Reports
  115. Continuous symmetry measures of penta-coordinate molecules: Berry and non-Berry distortions of the trigonal bipyramid †
    Santiago Álvarez, Miquel Llunell · 2000 · Journal of the Chemical Society Dalton Transactions
  116. Entanglement measures for single- and multireference correlation effects
    Katharina Bogusławski, Paweł Tecmer, Örs Legeza, Markus Reiher · 2016
  117. Geometries of Second-Row Transition-Metal Complexes from Density-Functional Theory
    Mark P. Waller, Heiko Braun, Nils W. Hojdis, Michæl Bühl · 2007 · Journal of Chemical Theory and Computation
  118. <i>In silico</i> Design of Porous Polymer Networks: High-Throughput Screening for Methane Storage Materials
    Martin, Richard L., Simon, Cory M., Smit, Berend, Haranczyk, Maciej · 2014 · Journal of the American Chemical Society
  119. Reduction of Systematic Uncertainty in DFT Redox Potentials of Transition-Metal Complexes
    Steven J. Konezny, Mark D. Doherty, Oana R. Luca, Robert H. Crabtree, Grigorii L. Soloveichik, Víctor S. Batista · 2012 · The Journal of Physical Chemistry C
  120. What Makes for a Bad Catalytic Cycle? A Theoretical Study on the Suzuki−Miyaura Reaction within the Energetic Span Model
    Sebastian Kozuch, Jan M. L. Martin · 2011 · ACS Catalysis
  121. Curvature and Frontier Orbital Energies in Density Functional Theory
    Tamar Stein, Jochen Autschbach, Niranjan Govind, Leeor Kronik, Roi Baer · 2012 · The Journal of Physical Chemistry Letters
  122. Comparison of density functionals for energy and structural differences between the high- [5T2g:(t2g)4(eg)2] and low- [1A1g:(t2g)6(eg)] spin states of iron(II) coordination compounds. II. More functionals and the hexaminoferrous cation, [Fe(NH3)6]2+
    Antony Fouqueau, Mark E. Casida, Latévi Max Lawson Daku, Andreas Hauser, Frank Neese · 2005 · The Journal of Chemical Physics
  123. Atomic Property Weighted Radial Distribution Functions Descriptors of Metal–Organic Frameworks for the Prediction of Gas Uptake Capacity
    Fernandez, Michael, Trefiak, Nicholas R., Woo, Tom K. · 2013 · The Journal of Physical Chemistry C
  124. AARON: An Automated Reaction Optimizer for New Catalysts
    Yanfei Guan, Victoria M. Ingman, Benjamin J. Rooks, Steven E. Wheeler · 2018 · Journal of Chemical Theory and Computation
  125. Multireference Model Chemistries for Thermochemical Kinetics
    Oksana Tishchenko, Jingjing Zheng, Donald G. Truhlar · 2008 · Journal of Chemical Theory and Computation
  126. Accurate Computed Enthalpies of Spin Crossover in Iron and Cobalt Complexes
    Kasper P. Kepp, Jordi Cirera · 2009 · The Journal of Physical Chemistry A
  127. Effects of correlated parameters and uncertainty in electronic-structure-based chemical kinetic modelling
    Jonathan E. Sutton, Wei Guo, Markos A. Katsoulakis, Dionisios G. Vlachos · 2016 · Nature Chemistry
  128. Transition-state modeling with empirical force fields
    John E. Eksterowicz, Kendall N. Houk · 1993 · Chemical Reviews
  129. Does a Molecule-Specific Density Functional Give an Accurate Electron Density? The Challenging Case of the CuCl Electric Field Gradient
    Monika Srebro‐Hooper, Jochen Autschbach · 2012 · The Journal of Physical Chemistry Letters
  130. Optical Properties of [Ru(phen)2dppz]2+as a Function of Nonaqueous Environment
    Rajesh B. Nair, Brian M. Cullum, Catherine Jones Murphy · 1997 · Inorganic Chemistry
  131. Chimera: enabling hierarchy based multi-objective optimization for self-driving laboratories
    Häse, Florian, Roch, Loïc M., Aspuru-Guzik, Alán · 2018 · Chemical Science
  132. Strategies and Software for Machine Learning Accelerated Discovery in Transition Metal Chemistry
    Nandy, Aditya, Duan, Chenru, Janet, Jon Paul, Gugler, Stefan, Kulik, Heather J. · 2018 · Industrial &amp; Engineering Chemistry Research
  133. Acceleration of saddle-point searches with machine learning
    Andrew A. Peterson · 2016 · The Journal of Chemical Physics
  134. Heuristics-Guided Exploration of Reaction Mechanisms
    Maike Bergeler, Gregor N. C. Simm, Jonny Proppe, Markus Reiher · 2015 · Journal of Chemical Theory and Computation
  135. A generalized method for constructing hypothetical nanoporous materials of any net topology from graph theory
    Boyd, Peter G., Woo, Tom K. · 2016 · CrystEngComm
  136. An automated framework for QSAR model building
    Samina Kausar, André O. Falcão · 2018 · Journal of Cheminformatics
  137. Bayesian semi-supervised learning for uncertainty-calibrated prediction of molecular properties and active learning
    Yao Zhang, Alpha A. Lee · 2019 · Chemical Science
  138. Fast and Accurate Uncertainty Estimation in Chemical Machine Learning
    Félix Musil, Michael J. Willatt, Mikhail Langovoy, Michele Ceriotti · 2019 · Journal of Chemical Theory and Computation
  139. Understanding and Breaking Scaling Relations in Single-Site Catalysis: Methane to Methanol Conversion by Fe IV ═O
    Terry Z. H. Gani, Heather J. Kulik · 2017 · ACS Catalysis
  140. Spin State Energetics in First-Row Transition Metal Complexes: Contribution of (3s3p) Correlation and Its Description by Second-Order Perturbation Theory
    Kristine Pierloot, Quan Manh Phung, Alex Domingo · 2016 · Journal of Chemical Theory and Computation
  141. Semi-supervised machine-learning classification of materials synthesis procedures
    Huo, Haoyan, Rong, Ziqin, Kononova, Olga, Sun, Wenhao, Botari, Tiago, He, Tanjin, Tshitoyan, Vahe, Ceder, Gerbrand · 2019 · npj Computational Materials
  142. SHAPES empirical force field: new treatment of angular potentials and its application to square-planar transition-metal complexes
    Viloya S. Allured, Christine M. Kelly, Clark R. Landis · 1991 · Journal of the American Chemical Society
  143. An intermediate neglect of differential overlap model for second‐row transition metal species
    Wayne P. Anderson, Thomas R. Cundari, Michael C. Zerner · 1991 · International Journal of Quantum Chemistry
  144. What Can Density Functional Theory Tell Us about Artificial Catalytic Water Splitting?
    Michael G. Mavros, Takashi Tsuchimochi, Tim Kowalczyk, Alexandra R. McIsaac, Lee‐Ping Wang, Troy Van Voorhis · 2014 · Inorganic Chemistry
  145. Assessment of DFT Methods for Transition Metals with the TMC151 Compilation of Data Sets and Comparison with Accuracies for Main-Group Chemistry
    Bun Chan, Peter M. W. Gill, Masanari Kimura · 2019 · Journal of Chemical Theory and Computation
  146. Computational Catalysis Using the Artificial Force Induced Reaction Method
    W. M. C. Sameera, Satoshi Maeda, Keiji Morokuma · 2016 · Accounts of Chemical Research
  147. Molecular mechanics calculations of transition metal complexes
    Paul V. Bernhardt, Peter Comba · 1992 · Inorganic Chemistry
  148. Multireference Character for 4d Transition Metal-Containing Molecules
    Jiaqi Wang, Sivabalan Manivasagam, Angela K. Wilson · 2015 · Journal of Chemical Theory and Computation
  149. Microkinetic modeling in homogeneous catalysis
    María Besora, Feliu Maseras · 2018 · Wiley Interdisciplinary Reviews Computational Molecular Science
  150. Structural systematics. Part 3. Geometry deformations in triphenylphosphine fragments: a test of bonding theories in phosphine complexes
    Barry J. Dunne, Richard B. Morris, A. Guy. Orpen · 1991 · Journal of the Chemical Society Dalton Transactions
  151. Expansion of the Ligand Knowledge Base for Monodentate P-Donor Ligands (LKB-P)
    Jesús Jover, Natalie Fey, Jeremy Noel Harvey, Guy C. Lloyd‐Jones, A. Guy. Orpen, Gareth J. J. Owen‐Smith, Paul M. Murray, David R. J. Hose, Robert B. Osborne, Mark Purdie · 2010 · Organometallics
  152. Comment on “Predicting reaction performance in C–N cross-coupling using machine learning”
    Kangway V. Chuang, Michael J. Keiser · 2018 · Science
  153. tmQM Dataset─Quantum Geometries and Properties of 86k Transition Metal Complexes
    Balcells, David, Skjelstad, Bastian Bjerkem · 2020 · Journal of Chemical Information and Modeling
  154. Factors Governing Metal−Ligand Distances and Coordination Geometries of Metal Complexes
    Gopi Kuppuraj, Minko Dudev, Carmay Lim · 2009 · The Journal of Physical Chemistry B
  155. Genetic algorithms in chemistry
    Riccardo Leardi · 2007 · Journal of Chromatography A
  156. A simple DFT-based diagnostic for nondynamical correlation
    Uma R. Fogueri, Sebastian Kozuch, Amir Karton, Jan M. L. Martin · 2012 · Theoretical Chemistry Accounts
  157. Factors Governing the Metal Coordination Number in Metal Complexes from Cambridge Structural Database Analyses
    Minko Dudev, Jonathan Wang, Todor Dudev, Carmay Lim · 2006 · The Journal of Physical Chemistry B
  158. Adsorption Isotherm Predictions for Multiple Molecules in MOFs Using the Same Deep Learning Model
    Ryther Anderson, Achay Biong, Diego A. Gómez‐Gualdrón · 2020 · Journal of Chemical Theory and Computation
  159. Development of a Ligand Knowledge Base, Part 1: Computational Descriptors for Phosphorus Donor Ligands
    Natalie Fey, Athanassios C. Tsipis, Stephanie E. Harris, Jeremy Noel Harvey, A. Guy. Orpen, Ralph A. Mansson · 2005 · Chemistry - A European Journal
  160. Toward Highly Accurate Spin State Energetics in First-Row Transition Metal Complexes: A Combined CASPT2/CC Approach
    Quan Manh Phung, Milica Feldt, Jeremy Noel Harvey, Kristine Pierloot · 2018 · Journal of Chemical Theory and Computation
  161. A molecular mechanics model of ligand effects. 3. A new measure of ligand steric effects
    Theodore L. Brown · 1992 · Inorganic Chemistry
  162. Auto-generated materials database of Curie and Néel temperatures via semi-supervised relationship extraction
    Callum J. Court, Jacqueline M. Cole · 2018 · Scientific Data
  163. Linear free energy relations and the reactivity-selectivity principle
    C. David Johnson · 1975 · Chemical Reviews
  164. Predicting electronic structure properties of transition metal complexes with neural networks
    Jon Paul Janet, Heather J. Kulik · 2017 · DSpace@MIT (Massachusetts Institute of Technology)
  165. Directing the reactivity of metal hydrides for selective CO 2 reduction
    Bianca Myraih Ceballos, Jenny Y. Yang · 2018 · Proceedings of the National Academy of Sciences
  166. Comparison of density functionals for differences between the high- (T2g5) and low- (A1g1) spin states of iron(II) compounds. IV. Results for the ferrous complexes [Fe(L)(‘NHS4’)]
    Georg Ganzenmüller, Nabil Berkaïne, Antony Fouqueau, Mark E. Casida, Markus Reiher · 2005 · The Journal of Chemical Physics
  167. Chemical reaction coordinates from crystal structure data. I.
    Hans Beat Buergi · 1973 · Inorganic Chemistry
  168. Automated Discovery and Refinement of Reactive Molecular Dynamics Pathways
    Lee‐Ping Wang, Robert T. McGibbon, Vijay S. Pande, Todd J. Martı́nez · 2015 · Journal of Chemical Theory and Computation
  169. Machine learning and molecular descriptors enable rational solvent selection in asymmetric catalysis
    Amar, Yehia, Schweidtmann, Artur M., Deutsch, Paul, Cao, Liwei, Lapkin, Alexei · 2019 · Chemical Science
  170. Gaussian process regression for geometry optimization
    Alexander Denzel, Johannes Kästner · 2018 · The Journal of Chemical Physics
  171. Solvent modified spin crossover in an iron( iii ) complex: phase changes and an exceptionally wide hysteresis
    Wasinee Phonsri, Phimphaka Harding, Lujia Liu, Shane G. Telfer, Keith S. Murray, Boujemaa Moubaraki, T.M. Ross, Guy N. L. Jameson, David J. Harding · 2017 · Chemical Science
  172. High-Throughput Computational Screening of Multivariate Metal–Organic Frameworks (MTV-MOFs) for CO2 Capture
    Song Li, Yongchul G. Chung, Cory M. Simon, Randall Q. Snurr · 2017 · The Journal of Physical Chemistry Letters
  173. Structure–Activity Relationships That Identify Metal–Organic Framework Catalysts for Methane Activation
    Andrew S. Rosen, Justin M. Notestein, R. Snurr · 2019 · ACS Catalysis
  174. Active site electronic structure and dynamics during metalloenzyme catalysis
    Oded Kleifeld, Anatoly I. Frenkel, Jan M. L. Martin, Irit Sagi · 2003 · Nature Structural Biology
  175. Counterion and solvent effects on the electrode reactions of iron porphyrins
    Lawrence A. Bottomley, Karl M. Kadish · 1981 · Inorganic Chemistry
  176. Evolution of Catalysts Directed by Genetic Algorithms in a Plug-Based Microfluidic Device Tested with Oxidation of Methane by Oxygen
    Kreutz, Jason E., Shukhaev, Anton, Du, Wenbin, Druskin, Sasha, Daugulis, Olafs, Ismagilov, Rustem F. · 2010 · Journal of the American Chemical Society
  177. Prediction of Bond Dissociation Energies/Heats of Formation for Diatomic Transition Metal Compounds: CCSD(T) Works
    Zongtang Fang, Monica Vasiliu, Kirk A. Peterson, David A. Dixon · 2017 · Journal of Chemical Theory and Computation
  178. Molecular modelling for transition metal complexes: Dealing with d-electron effects
    Robert James Deeth, Anna E. Anastasi, Christian Diedrich, Kris Randell · 2008 · Coordination Chemistry Reviews
  179. Computational Ligand Design for the Reductive Elimination of ArCF3 from a Small Bite Angle PdII Complex: Remarkable Effect of a Perfluoroalkyl Phosphine
    Mads C. Nielsen, Karl J. Bonney, Franziska Schoenebeck · 2014 · Angewandte Chemie International Edition
  180. Nonclassical Single-State Reactivity of an Oxo-Iron(IV) Complex Confined to Triplet Pathways
    Claudia Küpper, Bhaskar Mondal, Joan Serrano‐Plana, Iris Klawitter, Frank Neese, Miguel Costas, Shengfa Ye, Franc Meyer · 2017 · Journal of the American Chemical Society
  181. The application of electrospray ionization mass spectrometry to homogeneous catalysis
    Krista L. Vikse, Zohrab Ahmadi, J. Scott McIndoe · 2014 · Coordination Chemistry Reviews
  182. Linear scaling relationships and volcano plots in homogeneous catalysis – revisiting the Suzuki reaction
    Michael Busch, Matthew D. Wodrich, Clémence Corminbœuf · 2015 · Chemical Science
  183. Rapid virtual screening of enantioselective catalysts using CatVS
    Anthony R. Rosales, Jessica Wahlers, Elaine Limé, Rebecca E. Meadows, Kevin W. Leslie, Rhona Savin, Fiona M. Bell, Eric Hansen, Paul M. Helquist, Rachel H. Munday et al. · 2018 · Nature Catalysis
  184. Do Practical Standard Coupled Cluster Calculations Agree Better than Kohn–Sham Calculations with Currently Available Functionals When Compared to the Best Available Experimental Data for Dissociation Energies of Bonds to 3 d Transition Metals?
    Xuefei Xu, Wenjing Zhang, Mingsheng Tang, Donald G. Truhlar · 2015 · Journal of Chemical Theory and Computation
  185. Linear‐Scaling Methods in Quantum Chemistry
    Christian Ochsenfeld, Jörg Kußmann, Daniel S. Lambrecht · 2007 · Reviews in computational chemistry
  186. Transition metal complexes as electrocatalysts—Development and applications in electro-oxidation reactions
    Kwong-Chak Cheung, Wing‐Leung Wong, Dik‐Lung Ma, Tat‐Shing Lai, Kwok‐Yin Wong · 2007 · Coordination Chemistry Reviews
  187. Application of a genetic algorithm and a neural network for the discovery and optimization of new solid catalytic materials
    Uwe Rodemerck, Manfred Baerns, Martin Holeňa, D. Wolf · 2003 · Applied Surface Science
  188. Beyond Density Functional Theory: The Multiconfigurational Approach To Model Heterogeneous Catalysis
    Carlo Alberto Gaggioli, Samuel J. Stoneburner, Christopher J. Cramer, Laura Gagliardi · 2019 · ACS Catalysis
  189. autodE: Automated Calculation of Reaction Energy Profiles— Application to Organic and Organometallic Reactions
    Tom A. Young, Joseph J. Silcock, Alistair J. Sterling, Fernanda Duarte · 2020 · Angewandte Chemie International Edition
  190. Efficient search of compositional space for hybrid organic–inorganic perovskites via Bayesian optimization
    Herbol, Henry C., Hu, Weici, Frazier, Peter, Clancy, Paulette, Poloczek, Matthias · 2018 · npj Computational Materials
  191. Prediction of transition metal‐binding sites from apo protein structures
    Mariana Babor, Sergey Gerzon, Barak Raveh, V. M. Sobolev, Marvin Edelman · 2007 · Proteins Structure Function and Bioinformatics
  192. Valence bond concepts applied to the molecular mechanics description of molecular shapes. 1. Application to nonhypervalent molecules of the P-block
    Daniel M. Root, Clark R. Landis, Thomas Cleveland · 1993 · Journal of the American Chemical Society
  193. Kinetic Isotope Effect Determination Probes the Spin of the Transition State, Its Stereochemistry, and Its Ligand Sphere in Hydrogen Abstraction Reactions of Oxoiron(IV) Complexes
    Debasish Mandal, Dibyendu Mallick, Sason S. Shaik · 2018 · Accounts of Chemical Research
  194. Structural Systematics. 6. 1 Apparent Flexibility of Metal Complexes in Crystals
    Antonio Martı́n, A. Guy Orpen · 1996 · Journal of the American Chemical Society
  195. Double-substitution-based diagnostics for coupled-cluster and Møller–Plesset perturbation theory
    Ida M. B. Nielsen, Curtis L. Janssen · 1999 · Chemical Physics Letters
  196. Construction and Characterization of Structure Models of Crystalline Porous Polymers
    Martin, Richard Luis, Haranczyk, Maciej · 2014 · Crystal Growth &amp; Design
  197. Structure Optimisation of Large Transition‐Metal Complexes with Extended Tight‐Binding Methods
    Markus Bursch, Hagen Neugebauer, Stefan Grimme · 2019 · Angewandte Chemie International Edition
  198. Assessment of density functional theory for iron(II) molecules across the spin-crossover transition
    Andrea Droghetti, Dario Alfè, Stefano Sanvito · 2012 · The Journal of Chemical Physics
  199. Near-infrared electrochromic materials for optical attenuation based on transition-metal coordination complexes
    Michael D. Ward · 2005 · Journal of Solid State Electrochemistry
  200. Theoretical p K a calculations with continuum model solvents, alternative protocols to thermodynamic cycles
    Rodrigo Casasnovas, Joaquín Ortega‐Castro, Juan Frau, Josefa Donoso, Francisco Muñoz · 2014 · International Journal of Quantum Chemistry