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RESEARCH PAPER · Angewandte Chemie · 2019

Autonome Entdeckung in den chemischen Wissenschaften, Teil I: Fortschritt

Connor W. Coley, Natalie S. Eyke, Klavs F. Jensen

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

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Autonome Entdeckung in den chemischen Wissenschaften, Teil I: FortschrittOriginalOrganic Superbases in Recent Synthetic Methodology Research116autodE: Automated Calculation of Reaction Energy Profiles— Application to Organic and Organometallic Reactions123Towards Data‐Driven Design of Asymmetric Hydrogenation of Olefins: Database and Hierarchical Learning78Towards Data‐Driven Design of Asymmetric Hydrogenation of Olefins: Database and Hierarchical Learning6Failure‐Experiment‐Supported Optimization of Poorly Reproducible Synthetic Conditions for Novel Lanthanide Metal‐Organic Frameworks with Two‐Dimensional Secondary Building Units**12Machine Learning for Chemical Reactivity: The Importance of Failed Experiments218Maschinelles Lernen zur Vorhersage chemischer Reaktivität: Die Bedeutung “gescheiterter” Experimente8Computer‐Assisted Design of Sustainable Syntheses of Pharmaceuticals and Agrochemicals from Industrial Wastes0Bridging Chemical Knowledge and Machine Learning for Performance Prediction of Organic Synthesis51Machine‐Learning Classification for the Prediction of Catalytic Activity of Organic Photosensitizers in the Nickel(II)‐Salt‐Induced Synthesis of Phenols39Machine‐Learning Classification for the Prediction of Catalytic Activity of Organic Photosensitizers in the Nickel(II)‐Salt‐Induced Synthesis of Phenols1Physics‐informed Transfer Learning for Out‐of‐sample Vapor Pressure Predictions19

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  1. Organic Superbases in Recent Synthetic Methodology Research

    Chemistry - A European Journal · 2020-08-26

    Thomas R. Puleo, Stephen J. Sujansky, Shawn E. Wright, Jeffrey S. Bandar

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  2. autodE: Automated Calculation of Reaction Energy Profiles— Application to Organic and Organometallic Reactions

    Angewandte Chemie International Edition · 2020-10-27

    Tom A. Young, Joseph J. Silcock, Alistair J. Sterling, Fernanda Duarte

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  3. Towards Data‐Driven Design of Asymmetric Hydrogenation of Olefins: Database and Hierarchical Learning

    Angewandte Chemie International Edition · 2021-08-09

    Li‐Cheng Xu, Shuo‐Qing Zhang, Xin Li, Miao‐Jiong Tang, Pei‐Pei Xie, Xin Hong

    Read original paper ↗ ·

  4. Towards Data‐Driven Design of Asymmetric Hydrogenation of Olefins: Database and Hierarchical Learning

    Angewandte Chemie · 2021-08-09

    Li‐Cheng Xu, Shuo‐Qing Zhang, Xin Li, Miao‐Jiong Tang, Pei‐Pei Xie, Xin Hong

    Read original paper ↗ ·

  5. Failure‐Experiment‐Supported Optimization of Poorly Reproducible Synthetic Conditions for Novel Lanthanide Metal‐Organic Frameworks with Two‐Dimensional Secondary Building Units**

    Chemistry - A European Journal · 2021-10-09

    Yu Kitamura, Emi Terado, Zechen Zhang, Hirofumi Yoshikawa, Tomoko Inose, Hiroshi Uji‐i, Masaharu Tanimizu, Akihiro Inokuchi, Yoshinobu Kamakura, Daisuke Tanaka

    Read original paper ↗ ·

  6. Machine Learning for Chemical Reactivity: The Importance of Failed Experiments

    Angewandte Chemie International Edition · 2022-05-05

    Felix Strieth‐Kalthoff, Frederik Sandfort, Marius Kühnemund, Felix R. Schäfer, Herbert Kuchen, Frank Glorius

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  7. Maschinelles Lernen zur Vorhersage chemischer Reaktivität: Die Bedeutung “gescheiterter” Experimente

    Angewandte Chemie · 2022-05-05

    Felix Strieth‐Kalthoff, Frederik Sandfort, Marius Kühnemund, Felix R. Schäfer, Herbert Kuchen, Frank Glorius

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  8. Computer‐Assisted Design of Sustainable Syntheses of Pharmaceuticals and Agrochemicals from Industrial Wastes

    ChemSusChem · 2022-07-27

    Pierre Le Pogam, Nicolas Papon, Mehdi A. Beniddir, Vincent Courdavault

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  9. Bridging Chemical Knowledge and Machine Learning for Performance Prediction of Organic Synthesis

    Chemistry - A European Journal · 2022-10-07

    Shuo‐Qing Zhang, Li‐Cheng Xu, Shu‐Wen Li, João C. A. Oliveira, Xin Li, Lutz Ackermann, Xin Hong

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  10. Machine‐Learning Classification for the Prediction of Catalytic Activity of Organic Photosensitizers in the Nickel(II)‐Salt‐Induced Synthesis of Phenols

    Angewandte Chemie International Edition · 2023-01-16

    Naoki Noto, Akira Yada, Takeshi Yanai, Susumu Saito

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  11. Machine‐Learning Classification for the Prediction of Catalytic Activity of Organic Photosensitizers in the Nickel(II)‐Salt‐Induced Synthesis of Phenols

    Angewandte Chemie · 2023-01-16

    Naoki Noto, Akira Yada, Takeshi Yanai, Susumu Saito

    Read original paper ↗ ·

  12. Physics‐informed Transfer Learning for Out‐of‐sample Vapor Pressure Predictions

    Propellants Explosives Pyrotechnics · 2023-02-04

    Joshua L. Lansford, Klavs F. Jensen, Brian C. Barnes

    Read original paper ↗ ·
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