BetaCitation Atlas

RESEARCH PAPER · Chemical Reviews · 2021

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

Aditya Nandy, Chenru Duan, Michael G. Taylor, Fang Liu, Adam H. Steeves, Heather J. Kulik

Read original paper ↗

See where this research leads.

353 direct citing papers in this saved network. Explore the next layer with second-order citations.

Open in your workspace →Saved 2026-10-14 · complete coverage
Filter Citing Papers
Press Enter or comma to add · × to remove · searches titles and available abstracts
Journals
All journals
Most represented first · select one or more
Explore Terms In These PapersHide SuggestionsShow Suggestions

Original and current center papers stay visible as anchors.
Numbers show citations received
42 direct citing works

Computational Discovery of Transition-metal Complexes: From High-throughput Screening to Machine LearningOriginalA machine learning approach to predict L-edge x-ray absorption spectra of light transition metal ion compounds3Diversifying databases of metal organic frameworks for high-throughput computational screening0Machine learning for multiscale modeling in computational molecular design25Photoredox Chemistry with Organic Catalysts: Role of Computational Methods16Diversifying Databases of Metal Organic Frameworks for High-Throughput Computational Screening141Audacity of huge: overcoming challenges of data scarcity and data quality for machine learning in computational materials discovery98Best practices in catalysis: A perspective27A benchmark for non-covalent interactions in organometallic crystals4Catalytic properties of the ferryl ion in the solid state: a computational review2Designing 3d metal oxides: selecting optimal density functionals for strongly correlated materials15High-entropy alloy catalysts: high-throughput and machine learning-driven design59OSCAR: an extensive repository of chemically and functionally diverse organocatalysts39Unlocking the computational design of metal–organic cages66Autonomous Reaction Network Exploration in Homogeneous and Heterogeneous Catalysis65Computational Scaling Relationships Predict Experimental Activity and Rate-Limiting Behavior in Homogeneous Water Oxidation9Research update of emergent gold nanoclusters: A reinforced approach towards evolution, synthesis mechanism and application23Iridium- and Palladium-Based Catalysts in the Pharmaceutical Industry19Application and prospect of machine learning in polyolefin catalysts11Working at the interfaces of data science and synthetic electrochemistry21Derivatized phenylbenzothiazole cyclometalating ligands for reverse saturable absorption materials development0Estimating Phosphorescent Emission Energies in IrIII Complexes Using Large‐Scale Quantum Computing Simulations**3Virtual Ligand-Assisted Screening Strategy to Discover Enabling Ligands for Transition Metal Catalysis24Estimating Phosphorescent Emission Energies in Ir III Complexes Using Large‐Scale Quantum Computing Simulations**15Machine Learning for the Discovery, Design, and Engineering of Materials66Discovery of Electronic Structure and Interfacial Interaction Features in Catalytic Activity13Heuristics and Uncertainty Quantification in Rational and Inverse Compound and Catalyst Design3New Strategies for Direct Methane-to-Methanol Conversion from Active Learning Exploration of 16 Million Catalysts74Machine learning of material properties: Predictive and interpretable multilinear models114The 2022 solar fuels roadmap150Selection of Low-Dimensional 3-D Geometric Descriptors for Accurate Enantioselectivity Prediction36Data-Driven Mapping of Inorganic Chemical Space for the Design of Transition Metal Complexes and Metal-Organic Frameworks0Extending the High-Throughput Experimentation (HTE) Approach to Catalytic Olefin Polymerizations: From Catalysts to Materials26Machine Learning Models Predict Calculation Outcomes with the Transferability Necessary for Computational Catalysis18Theoretical Perspectives in Organocatalysis20A Look Inside the Black Box of Machine Learning Photodynamics Simulations54Exploiting Ligand Additivity for Transferable Machine Learning of Multireference Character across Known Transition Metal Complex Ligands18Using Computational Chemistry To Reveal Nature’s Blueprints for Single-Site Catalysis of C–H Activation45Earth Abundant Transition Metal Catalysts for Activation and Functionalization of Light Hydrocarbons0In silico reaction screening with difluorocarbene for N-difluoroalkylative dearomatization of pyridines36An Efficient High-Throughput Screening of High Gentamicin-Producing Mutants Based on Titer Determination Using an Integrated Computer-Aided Vision Technology and Machine Learning10Quantum chemical calculations predict multicomponent reactions0OSCAR: An Extensive Repository of Chemically and Functionally Diverse Organocatalysts1Neural network potentials8SELFIES and the future of molecular string representations261Untitled work2Computational design of magnetic molecules and their environment using quantum chemistry, machine learning and multiscale simulations88Quantum Chemical Roots of Machine-Learning Molecular Similarity Descriptors18Computational discovery of Metal–Organic Frameworks for sustainable energy systems: Open challenges9Text‐based representations with interpretable machine learning reveal structure–property relationships of polybenzenoid hydrocarbons18Redox‐active ligands as a challenge for electronic structure methods6Computational screening of transition metal-doped CdS for photocatalytic hydrogen production53High-Throughput Experimentation for Resource-Efficient Discovery of Methane Functionalization Catalysts1Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery138Comparison of LANL2DZ and SBKJC Basis Sets, over DFT Calculations of a Typical Half-Sandwich Ruthenium Complex6Unraveling the Contributions to Spin–Lattice Relaxation in Kramers Single-Molecule Magnets93Mean Value Ensemble Hubbard-U Correction for Spin-Crossover Molecules11A transferable recommender approach for selecting the best density functional approximations in chemical discovery31Data-Driven Multi-Objective Optimization Tactics for Catalytic Asymmetric Reactions Using Bisphosphine Ligands110An Introduction to Machine Learning in Molecular Sciences0Cyclic iron tetra N-heterocyclic carbenes: synthesis, properties, reactivity, and catalysis37Deep learning metal complex properties with natural quantum graphs59Highly chemoselective ligands for Suzuki–Miyaura cross-coupling reaction based on virtual ligand-assisted screening15Machine learning methods in photochemistry and photophysics10Overview of outer-sphere electron transfer mediators for electrosynthesis13Quantum chemical calculations for reaction prediction in the development of synthetic methodologies47Spin-Phonon Relaxation in Magnetic Molecules: Theory, Predictions and Insights42Using a single complex to predict the reaction energy profile: a case study of Pd/Ni-catalyzed ethylene polymerization1Δ-Machine learning for quantum chemistry prediction of solution-phase molecular properties at the ground and excited states26Pyridine derivatives complexes of Co(II) and Ni(II) 3‐bromobenzoates: Crystal structure, in silico anti‐SARS‐CoV‐2 potential, serum albumin binding properties and cytotoxicity4Automated Library Generation and Serendipity Quantification Enables Diverse Discovery in Coordination Chemistry12Generating, Managing, and Mining Big Data in Zeolite Simulations5Using AI to navigate through the DFA zoo2High-throughput ab initio reaction mechanism exploration in the cloud with automated multi-reference validation27RETRACTED: Machine learning modelling of removal of reactive orange RO16 by chemical activated carbon in textile wastewater4Computational Modeling of 4d and 5d Transition Metal Catalysts0Genetic Algorithms for the Discovery of Homogeneous Catalysts14On the Crystal Chemistry of RE2Si2O7: Revisited Structures, Group–Subgroup Relationship, and Insights of Ce3+-Activated Radioluminescence19Self-adaptive bulk/surface engineering of Bi O Br towards enhanced photocatalysis: Current status and future challenges22Sulfonamide derived Schiff base Mn (II), Co (II), and Ni (II) complexes: Crystal structures, density functional theory and Hirshfeld surface analysis28First-principles calculations on the micro-solvation of 3d-transition metal ions: solvation versus splitting water4An overview of advancement of organoruthenium(II) complexes as prospective anticancer agents80Data-driven-aided strategies in battery lifecycle management: Prediction, monitoring, and optimization87Synthesis optimization and adsorption modeling of biochar for pollutant removal via machine learning120Density Functional Theory‐Based Protocol to Calculate the Redox Potentials of First‐row Transition Metal Complexes for Aqueous Redox Targeting Flow Batteries18Challenges for Kinetics Predictions via Neural Network Potentials: A Wilkinson’s Catalyst Case16High‐Throughput Exploration of Triple‐Cation Perovskites via All‐in‐One Compositionally‐Graded Films12Evolutionary Multiobjective Optimization of Multiligand Metal Complexes in Diverse and Vast Chemical Spaces1Spectrophotometric Investigation and Computational Studies of Zirconium(IV)-3-hydroxy-2-[1'-phenyl-3'-(p-methoxyphenyl)-4'-pyrazolyl]-4H-chromen-4-one Complex15High‐throughput screening of spin states for transition metal complexes with spin‐polarized extended tight‐binding methods27Sorption Thermal Energy Storage Performance of Nanoporous Metal–Organic Frameworks and Covalent Organic Frameworks by Grand Canonical Monte Carlo Simulations8Open-Source Machine Learning in Computational Chemistry59Density Matrix-Based Features as Descriptors for Oxygen Reduction and Evolution Catalysts9Reversible trans-alkylation mechanisms at homogeneous catalytic systems investigated by a combined DFT and ASM-NEDA approach10Photodynamics With Neural Networks and Kernel Ridge Regression0ReaLigands: A Ligand Library Cultivated from Experiment and Intended for Molecular Computational Catalyst Design2Computational Chemistry for Photochemical Reactions2Bioinspired Catalyst Design Principles: Progress in Emulating Properties of Enzymes in Synthetic Catalysts44Machine learning accelerated photodynamics simulations31AABBA: Atom–Atom Bond–Bond Bond–Atom Graph Kernel for Machine Learning on Molecules and Materials0A Joint Semi-Supervised Variational Autoencoder and Transfer Learning Model for Designing Molecular Transition Metal Complexes3A Joint Semi-Supervised Variational Autoencoder and Transfer Learning Model for Designing Molecular Transition Metal Complexes2Evolutionary Algorithms and Workflows for De Novo Catalyst Design1Prediction of Reaction Orthogonality using Machine Learning1A Joint Semi-Supervised Variational Autoencoder and Transfer Learning Model for Designing Molecular Transition Metal Complexes0MatGPT: A Vane of Materials Informatics from Past, Present, to Future74Machine Learning-Assisted Low-Dimensional Electrocatalysts Design for Hydrogen Evolution Reaction207Substituent group tuned structural dimensionalities and magnetic properties of V-shaped bis-pyridyl ligands based Fe(II) coordination polymers5CO2 Hydrogenation to Methanol and Ethanol on In2O3-Based Single-Atom Catalysts and a New Scaling Relation12Unlocking the predictive power of quantum-inspired representations for intermolecular properties in machine learning3ReaLigands: A Ligand Library Cultivated from Experiment and Intended for Molecular Computational Catalyst Design21Stability Trends in disubstituted Cobaltocenium Based on the Analysis of the Machine Learning Models1Complex Formation in Hyperalkaline Solutions0Fine-tuning GPT-3 for machine learning electronic and functional properties of organic molecules47Automated prediction of ground state spin for transition metal complexes13Combining Hammett σ constants for Δ-machine learning and catalyst discovery4Metal–insulator–semiconductor photoelectrodes for enhanced photoelectrochemical water splitting76Multioxide combinatorial libraries: fusing synthetic approaches and additive technologies for highly orthogonal electronic noses4OM-Diff: inverse-design of organometallic catalysts with guided equivariant denoising diffusion19Performance of quantum chemistry methods for a benchmark set of spin-state energetics derived from experimental data of 17 transition metal complexes (SSE17)31Precision-engineered metal–organic frameworks: fine-tuning reverse topological structure prediction and design16Probing machine learning models based on high throughput experimentation data for the discovery of asymmetric hydrogenation catalysts26Automated Transition Metal Catalysts Discovery and Optimisation with AI and Machine Learning27Overview of Transition Metal Catalyzed Multicomponent Reactions Based on Trapping of Allylic Electrophiles13Applying graph neural network models to molecular property prediction using high-quality experimental data16The prediction of single-molecule magnet properties via deep learning9Paving the road towards automated homogeneous catalyst design32Mixtures Recomposition by Neural Nets: A Multidisciplinary Overview14Synthesis, supramolecular insight, Hirshfeld surface analyses and optical properties of Fe(II) and Cu(II) complexes of flexible imidazole tethered 1,8-naphthalimide10Comparison of dimensionality reduction techniques for the visualisation of chemical space in organometallic catalysis17Modeling Fe(II) Complexes Using Neural Networks14Derivatized phenylbenzothiazole cyclometalating ligands for reverse saturable absorption materials development0Revisiting Stereoselective Propene Polymerization Mechanisms: Insights through the Activation Strain Model12Ligand-Based Principal Component Analysis Followed by Ridge Regression: Application to an Asymmetric Negishi Reaction18Automated Prediction of Ground State Spin for Transition Metal Complexes0Directional multiobjective optimization of metal complexes at the billion-system scale42Hidden descriptors: Using statistical treatments to generate better descriptor sets3Machine learning for CO 2 capture and conversion: A review60Computer-assisted design of CGC catalysts for ethylene/1-octene copolymerization: A combined DFT and artificial neural network approach7Quantum chemical DFT-based adsorption mechanism of Pb(II) on a modified biochar17Discovering metal complexes in vast chemical spaces0Promises and Perils of Big Data: Philosophical Constraints on Chemical Ontologies6Interoperable workflows by exchanging grid-based data between quantum-chemical program packages7Impact of Model Selection and Conformational Effects on the Descriptors for In Silico Screening Campaigns: A Case Study of Rh-Catalyzed Acrylate Hydrogenation9Leveraging natural language processing to curate the tmCAT, tmPHOTO, tmBIO, and tmSCO datasets of functional transition metal complexes1Coatings Intelligence: Data-driven Automation for Chemistry 4.05Generative Foundation Model for On-demand Reverse Polymer Design0Insights into coordination and ligand trends of lanthanide complexes from the Cambridge Structural Database49Learning Design Rules for Catalysts Through Computational Chemistry and Machine Learning1Deep Generative Model for the Dual-Objective Inverse Design of Metal Complexes2A data-driven approach for the guided regulation of exposed facets in nanoparticles28

Arrows point to the paper being cited. Selecting a paper shows its incoming citations and its known path back to the original paper.

Drag to pan · Use + / − to zoom · Escape to close43 nodes / 53 citation links
Browse Matching Papers

Papers that cite this work

353 direct citing papers saved. Showing the first 50 here; use Browse Matching Papers in the map for all loaded papers.

  1. A machine learning approach to predict L-edge x-ray absorption spectra of light transition metal ion compounds

    arXiv (Cornell University) · 2021-07-28

    Johann Lüder

    Read original paper ↗ ·

  2. Diversifying databases of metal organic frameworks for high-throughput computational screening

    Unknown journal · 2021-09-28

    Sauradeep Majumdar, Seyed Mohamad Moosavi, Kevin Maik Jablonka, Daniele Ongari, Berend Smit

    Read original paper ↗ ·

  3. Machine learning for multiscale modeling in computational molecular design

    Current Opinion in Chemical Engineering · 2021-10-25

    Abdulelah S. Alshehri, Fengqi You

    Read original paper ↗ ·

  4. Photoredox Chemistry with Organic Catalysts: Role of Computational Methods

    ACS Omega · 2021-12-03

    Kareesa J. Kron, Andres Rodriguez-Katakura, Rachelle Elhessen, Shaama Mallikarjun Sharada

    Read original paper ↗ ·

  5. Diversifying Databases of Metal Organic Frameworks for High-Throughput Computational Screening

    ACS Applied Materials & Interfaces · 2021-12-15

    Sauradeep Majumdar, Seyed Mohamad Moosavi, Kevin Maik Jablonka, Daniele Ongari, Berend Smit

    Read original paper ↗ ·

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

    Current Opinion in Chemical Engineering · 2021-12-17

    Aditya Nandy, Chenru Duan, Heather J. Kulik

    Read original paper ↗ ·

  7. Best practices in catalysis: A perspective

    Journal of Catalysis · 2021-12-20

    Aditya Bhan, W. Nicholas Delgass

    Read original paper ↗ ·

  8. A benchmark for non-covalent interactions in organometallic crystals

    Physical Chemistry Chemical Physics · 2022-01-01

    José Eduardo Zamudio Díaz Mirón, Matthias Stein

    Read original paper ↗ ·

  9. Catalytic properties of the ferryl ion in the solid state: a computational review

    Catalysis Science & Technology · 2022-01-01

    Fernán Saiz, Leonardo Bernasconi

    Read original paper ↗ ·

  10. Designing 3d metal oxides: selecting optimal density functionals for strongly correlated materials

    Physical Chemistry Chemical Physics · 2022-01-01

    Ina Østrøm, Md. Anower Hossain, Patrick A. Burr, Judy Nancy Hart, Bram Hoex

    Read original paper ↗ ·

  11. High-entropy alloy catalysts: high-throughput and machine learning-driven design

    Journal of Materials Informatics · 2022-01-01

    Lixin Chen, Zhiwen Chen, Xue Yao, Baoxian Su, Weijian Chen, Xin Pang, Keun-Su Kim, Chandra Veer Singh, Yu Zou

    Read original paper ↗ ·

  12. OSCAR: an extensive repository of chemically and functionally diverse organocatalysts

    Chemical Science · 2022-01-01

    Simone Gallarati, Puck van Gerwen, Rubén Laplaza, Sergi Vela, Alberto Fabrizio, Clémence Corminbœuf

    Read original paper ↗ ·

  13. Unlocking the computational design of metal–organic cages

    Chemical Communications · 2022-01-01

    Andrew Tarzia, Kim E. Jelfs

    Read original paper ↗ ·

  14. Autonomous Reaction Network Exploration in Homogeneous and Heterogeneous Catalysis

    Topics in Catalysis · 2022-01-13

    Miguel Steiner, Markus Reiher

    Read original paper ↗ ·

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

    Inorganic Chemistry · 2022-01-17

    Daniel R. Harper, Heather J. Kulik

    Read original paper ↗ ·

  16. Research update of emergent gold nanoclusters: A reinforced approach towards evolution, synthesis mechanism and application

    Talanta · 2022-01-17

    Imran Mahmood Khan, Sobia Niazi, Lin Yue, Yin Zhang, Imran Pasha, Muhammad Kashif Iqbal Khan, Wasim Akhtar, Ali Mohsin, Muhammad Farhan Jahangir Chughati, Zhouping Wang

    Read original paper ↗ ·

  17. Iridium- and Palladium-Based Catalysts in the Pharmaceutical Industry

    Catalysts · 2022-01-28

    Óscar López, José M. Padrón

    Read original paper ↗ ·

  18. Application and prospect of machine learning in polyolefin catalysts

    Chinese Science Bulletin (Chinese Version) · 2022-02-18

    Wenhong Yang, Wen‐Hua Sun

    Read original paper ↗ ·

  19. Working at the interfaces of data science and synthetic electrochemistry

    Tetrahedron Chem · 2022-03-01

    Jesus I. Martinez Alvarado, Jonathan M. Meinhardt, Song Lin

    Read original paper ↗ ·

  20. Derivatized phenylbenzothiazole cyclometalating ligands for reverse saturable absorption materials development

    Unknown journal · 2022-03-07

    Victor A. Jaffett, Ryan M. O’Donnell, Thomas N. Rohrabaugh, Jack M. Harrison, Nanki Verma, Chi K. Nguyen, William M. Shensky

    Read original paper ↗ ·

  21. Estimating Phosphorescent Emission Energies in IrIII Complexes Using Large‐Scale Quantum Computing Simulations**

    Angewandte Chemie · 2022-03-10

    Scott N. Genin, Ilya G. Ryabinkin, Nathan R. Paisley, Sarah O. Whelan, Michael G. Helander, Zachary M. Hudson

    Read original paper ↗ ·

  22. Virtual Ligand-Assisted Screening Strategy to Discover Enabling Ligands for Transition Metal Catalysis

    ACS Catalysis · 2022-03-13

    Wataru Matsuoka, Yu Harabuchi, Satoshi Maeda

    Read original paper ↗ ·

  23. Estimating Phosphorescent Emission Energies in Ir III Complexes Using Large‐Scale Quantum Computing Simulations**

    Angewandte Chemie International Edition · 2022-03-14

    Scott N. Genin, Ilya G. Ryabinkin, Nathan R. Paisley, Sarah O. Whelan, Michael G. Helander, Zachary M. Hudson

    Read original paper ↗ ·

  24. Machine Learning for the Discovery, Design, and Engineering of Materials

    Annual Review of Chemical and Biomolecular Engineering · 2022-03-23

    Chenru Duan, Aditya Nandy, Heather J. Kulik

    Read original paper ↗ ·

  25. Discovery of Electronic Structure and Interfacial Interaction Features in Catalytic Activity

    Langmuir · 2022-03-25

    Qin Zhu, Yuming Gu, Xinzhu Wang, Chenyang Zhang, Jing Ma

    Read original paper ↗ ·

  26. Heuristics and Uncertainty Quantification in Rational and Inverse Compound and Catalyst Design

    Elsevier eBooks · 2022-04-13

    Thomas Weymuth, Markus Reiher

    Read original paper ↗ ·

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

    JACS Au · 2022-04-27

    Aditya Nandy, Chenru Duan, Conrad Goffinet, Heather J. Kulik

    Read original paper ↗ ·

  28. Machine learning of material properties: Predictive and interpretable multilinear models

    Science Advances · 2022-05-06

    Alice E. A. Allen, Alexandre Tkatchenko

    Read original paper ↗ ·

  29. The 2022 solar fuels roadmap

    Journal of Physics D Applied Physics · 2022-05-13

    Gideon Segev, Jakob Kibsgaard, Christopher Hahn, Zhichuan Jason Xu, Wen-Hui Sophia Cheng, Todd Gregory Deutsch, Chengxiang Xiang, Jenny Zhang, Leif Hammarström, Daniel G. Nocera, Adam Z. Weber, Peter Agbo, Takashi Hisatomi, Frank E. Osterloh, Kazunari Domen, Fatwa F. Abdi, Sophia Haussener, Daniel J. Miller, Shane Ardo, Paul C. McIntyre, Thomas Hannappel, Shu Hu, Harry Albert Atwater, John M. Gregoire, Mehmed Z. Ertem, Ian D. Sharp, Kyoung‐Shin Choi, Jae Sung Lee, Osamu Ishitani, Joel W. Ager, Rajiv Ramanujam Prabhakar, Alexis T. Bell, Shannon Wachter Boettcher, Kylie A. Vincent, Kazuhiro Takanabe, Vincent Artero, R.W. Napier, Beatriz Roldán Cuenya, Marc T. M. Koper, Roel van de Krol, Frances A. Houle

    Read original paper ↗ ·

  30. Selection of Low-Dimensional 3-D Geometric Descriptors for Accurate Enantioselectivity Prediction

    ACS Catalysis · 2022-05-31

    Giuseppe Antinucci, Büşra Dereli, Antonio Vittoria, Peter H. M. Budzelaar, Roberta Cipullo, Georgy P. Goryunov, Pavel S. Kulyabin, Dmitry V. Uborsky, Luigi Cavallo, Christian Ehm, Alexander Z. Voskoboynikov, Vincenzo Busico

    Read original paper ↗ ·

  31. Data-Driven Mapping of Inorganic Chemical Space for the Design of Transition Metal Complexes and Metal-Organic Frameworks

    ACS symposium series · 2022-06-14

    Jon Paul Janet

    Read original paper ↗ ·

  32. Extending the High-Throughput Experimentation (HTE) Approach to Catalytic Olefin Polymerizations: From Catalysts to Materials

    Macromolecules · 2022-06-16

    Antonio Vittoria, Gaia Urciuoli, Salvatore Costanzo, Daniele Tammaro, Felicia Daniela Cannavacciuolo, Rossana Pasquino, Roberta Cipullo, Finizia Auriemma, Nino Grizzuti, Pier Luca Maffettone, Vincenzo Busico

    Read original paper ↗ ·

  33. Machine Learning Models Predict Calculation Outcomes with the Transferability Necessary for Computational Catalysis

    Journal of Chemical Theory and Computation · 2022-06-23

    Chenru Duan, Aditya Nandy, Husain Adamji, Yuriy Román‐Leshkov, Heather J. Kulik

    Read original paper ↗ ·

  34. Theoretical Perspectives in Organocatalysis

    Chemistry - A European Journal · 2022-07-06

    Nika Melnyk, Íñigo Iribarren, Eric Mates‐Torres, Cristina Trujillo

    Read original paper ↗ ·

  35. A Look Inside the Black Box of Machine Learning Photodynamics Simulations

    Accounts of Chemical Research · 2022-07-07

    Jingbai Li, Steven A. Lopez

    Read original paper ↗ ·

  36. Exploiting Ligand Additivity for Transferable Machine Learning of Multireference Character across Known Transition Metal Complex Ligands

    Journal of Chemical Theory and Computation · 2022-07-14

    Chenru Duan, Adriana Ladera, Julian C. -L. Liu, Michael G. Taylor, Isuru Rangana Ariyarathna, Heather J. Kulik

    Read original paper ↗ ·

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

    ACS Catalysis · 2022-07-15

    Aditya Nandy, Husain Adamji, David W. Kastner, Vyshnavi Vennelakanti, Azadeh Nazemi, Mingjie Liu, Heather J. Kulik

    Read original paper ↗ ·

  38. Earth Abundant Transition Metal Catalysts for Activation and Functionalization of Light Hydrocarbons

    Unknown journal · 2022-08-01

    William M. Grumbles

    Read original paper ↗ ·

  39. In silico reaction screening with difluorocarbene for N-difluoroalkylative dearomatization of pyridines

    Nature Synthesis · 2022-08-08

    Hiroki Hayashi, Hitomi Katsuyama, Hideaki Takano, Yu Harabuchi, Satoshi Maeda, Tsuyoshi Mita

    Read original paper ↗ ·

  40. An Efficient High-Throughput Screening of High Gentamicin-Producing Mutants Based on Titer Determination Using an Integrated Computer-Aided Vision Technology and Machine Learning

    Analytical Chemistry · 2022-08-09

    Xiao‐Feng Zhu, Congcong Du, Ali Mohsin, Qian Yin, Feng Xu, Zebo Liu, Zejian Wang, Yingping Zhuang, Ju Chu, Meijin Guo, Xiwei Tian

    Read original paper ↗ ·

  41. Quantum chemical calculations predict multicomponent reactions

    Nature Synthesis · 2022-08-10

    Read original paper ↗ ·

  42. OSCAR: An Extensive Repository of Chemically and Functionally Diverse Organocatalysts

    ChemRxiv · 2022-08-29

    Simone Gallarati, Puck van Gerwen, Rubén Laplaza, Sergi Vela, Alberto Fabrizio, Clémence Corminbœuf

    Read original paper ↗ ·

  43. Neural network potentials

    Elsevier eBooks · 2022-09-23

    Jinzhe Zeng, Liqun Cao, Tong Zhu

    Read original paper ↗ ·

  44. SELFIES and the future of molecular string representations

    Patterns · 2022-10-01

    Mario Krenn, Qianxiang Ai, Senja Barthel, Nessa Carson, Angelo Frei, Nathan C. Frey, Pascal Friederich, Théophile Gaudin, Alberto Alexander Gayle, Kevin Maik Jablonka, Rafael F. Lameiro, Dominik Lemm, Alston Lo, Seyed Mohamad Moosavi, José Manuel Nápoles-Duarte, AkshatKumar Nigam, Robert Pollice, Kohulan Rajan, Ulrich Schatzschneider, Philippe Schwaller, Marta Skreta, Berend Smit, Felix Strieth‐Kalthoff, Chong Sun, Gary Tom, Guido Falk von Rudorff, Andrew Wang, Andrew Dickson White, Adamo Young, Rose Yu, Alán Aspuru‐Guzik

    Read original paper ↗ ·

  45. Untitled work

    Journal of Medicinal and Chemical Sciences · 2022-10-08

    Zahraa Mahdi, M. F. A. Alias

    Read original paper ↗ ·

  46. Computational design of magnetic molecules and their environment using quantum chemistry, machine learning and multiscale simulations

    Nature Reviews Chemistry · 2022-10-10

    Alessandro Lunghi, Stefano Sanvito

    Read original paper ↗ ·

  47. Quantum Chemical Roots of Machine-Learning Molecular Similarity Descriptors

    Journal of Chemical Theory and Computation · 2022-10-11

    Stefan Gugler, Markus Reiher

    Read original paper ↗ ·

  48. Computational discovery of Metal–Organic Frameworks for sustainable energy systems: Open challenges

    Computers & Chemical Engineering · 2022-10-14

    Xiangyu Yin, Chrysanthos E. Gounaris

    Read original paper ↗ ·

  49. Text‐based representations with interpretable machine learning reveal structure–property relationships of polybenzenoid hydrocarbons

    Journal of Physical Organic Chemistry · 2022-10-17

    Shachar Fite, Alexandra Wahab, Eno Paenurk, Zeev Gross, Renana Gershoni‐Poranne

    Read original paper ↗ ·

  50. Redox‐active ligands as a challenge for electronic structure methods

    Journal of Computational Chemistry · 2022-11-03

    Ursula Rastetter, Axel Jacobi von Wangelin, Carmen Herrmann

    Read original paper ↗ ·
More citing papers →
Citation Atlas · A map of research, not a ranking.