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RESEARCH PAPER · Organometallics · 2022

Advancing Base Metal Catalysis through Data Science: Insight and Predictive Models for Ni-Catalyzed Borylation through Supervised Machine Learning

Jason M. Stevens, Jun Li, Eric M. Simmons, Steven R. Wisniewski, Stacey DiSomma, Kenneth J. Fraunhoffer, Peng Geng, Bo Nan Hao, Erika W. Jackson

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

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42 direct citing works

Advancing Base Metal Catalysis through Data Science: Insight and Predictive Models for Ni-Catalyzed Borylation through Supervised Machine LearningOriginalTetrahydroxydiboron (Bis‐boric Acid): a Versatile Reagent for Borylation, Hydrogenation, Catalysis, Radical Reactions and H2 Generation17Collaboration as a Key to Advance Capabilities for Earth-Abundant Metal Catalysis70Catalyst- and additive-free chemoselective reduction of sulfoxides into sulfides using B2(OH)4 as a deoxygenative agent6Machine Learning Prediction of High-Yield Cobalt- and Nickel-Catalyzed Borylations10Rapid planning and analysis of high-throughput experiment arrays for reaction discovery83Identifying general reaction conditions by bandit optimization72Machine Learning-Based Yield Prediction for First-Row Transition Metal Catalyzed Cross-Coupling Reactions0Bridging the information gap in organic chemical reactions28Computer‐Aided Synthesis Planning (CASP) and Machine Learning: Optimizing Chemical Reaction Conditions15Multi‐Threshold Analysis for Chemical Space Mapping of Ni‐Catalyzed Suzuki‐Miyaura Couplings13Machine learning-guided strategies for reaction conditions design and optimization49Active learning high coverage sets of complementary reaction conditions4Recommending reaction conditions with label ranking6Accelerating the Development of Sustainable Catalytic Processes through Data Science7High‐throughput Experimentation Enables the Development of a Nickel‐catalyzed Cyanation Platform for (Hetero)aryl Halides4Tetrahydroxydiboron0Nickel-Catalyzed Aryl Borylations: Opportunities and Challenges for Innovation13Integration of Proximal Alkoxide and Lewis Acidic Cations To Boost Nickel-Catalyzed Borylation1Yield Prediction of Organic Reactions in Biased Data Sets via Positive-Unlabeled Learning3Precision orientation of hydrogen evolution performance of iron-based electrocatalysts empowered by machine learning: From electronic structure regulation to rational construction0Data driven reveals the upgrading mechanism of waste PET electrolysis: Research progress of machine learning in collaborative production of high-value chemicals and green hydrogen energy0Structured HTE Data and Integrated Bayesian Optimization Accelerate Scalable Amidation Process Development0Machine Learning for Synthetic Organic Chemistry: Methods, Applications, and Best Practices0Nickel as a Competitive Drop-In Alternative to Palladium in Thermal C–O Cross-Couplings of Aliphatic Alcohols with Heteroaryl Halides: A High-Throughput Experimentation Study0

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  1. Tetrahydroxydiboron (Bis‐boric Acid): a Versatile Reagent for Borylation, Hydrogenation, Catalysis, Radical Reactions and H2 Generation

    European Journal of Inorganic Chemistry · 2023-02-24

    Qiuxia Zhao, Xiang Liu, Didier Astruc

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  2. Collaboration as a Key to Advance Capabilities for Earth-Abundant Metal Catalysis

    Organic Process Research & Development · 2023-03-20

    Paul J. Chirik, Keary M. Engle, Eric M. Simmons, Steven R. Wisniewski

    Read original paper ↗ ·

  3. Catalyst- and additive-free chemoselective reduction of sulfoxides into sulfides using B2(OH)4 as a deoxygenative agent

    Tetrahedron · 2023-04-11

    Jixia Fan, Yifan Du, Rongrong Zhao, Qixing Liu, Haifeng Zhou

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  4. Machine Learning Prediction of High-Yield Cobalt- and Nickel-Catalyzed Borylations

    The Journal of Physical Chemistry C · 2023-07-03

    Alfredo Pereira, Oleksandra S. Trofymchuk

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  5. Rapid planning and analysis of high-throughput experiment arrays for reaction discovery

    Nature Communications · 2023-07-03

    Babak A. Mahjour, Rui Zhang, Yuning Shen, Andrew McGrath, Ruheng Zhao, Osama G. Mohamed, Yingfu Lin, Zirong Zhang, James L. Douthwaite, Ashootosh Tripathi, Tim Cernak

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  6. Identifying general reaction conditions by bandit optimization

    Nature · 2024-02-28

    Jason Y. Wang, Jason M. Stevens, Stavros K. Kariofillis, Mai-Jan Tom, Dung L. Golden, Jun Li, José E. Tábora, Marvin Parasram, Benjamin J. Shields, David N. Primer, Bo Nan Hao, David Del Valle, Stacey DiSomma, Ariel Furman, Greg Zipp, Sergey Melnikov, James L. Paulson, Abigail G. Doyle

    Read original paper ↗ ·

  7. Machine Learning-Based Yield Prediction for First-Row Transition Metal Catalyzed Cross-Coupling Reactions

    Research Square · 2024-03-25

    C. Rajalakshmi, Vivek Vijay, Abhirami Vijayakumar, Parvathi Santhoshkumar, John B Kottooran, Ann Miriam Abraham, Krishnaveni G, C. S. Anjanakutty, Binuja Varghese, Vibin Ipe Thomas

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  8. Bridging the information gap in organic chemical reactions

    Nature Chemistry · 2024-03-28

    Malte L. Schrader, Felix R. Schäfer, Felix Schäfers, Frank Glorius

    Read original paper ↗ ·

  9. Computer‐Aided Synthesis Planning (CASP) and Machine Learning: Optimizing Chemical Reaction Conditions

    Chemistry - A European Journal · 2024-07-31

    Han Yu, Mingjing Deng, Ke Liu, Jia Chen, Yuting Wang, Yongsong Xu, Longyang Dian

    Read original paper ↗ ·

  10. Multi‐Threshold Analysis for Chemical Space Mapping of Ni‐Catalyzed Suzuki‐Miyaura Couplings

    European Journal of Organic Chemistry · 2024-09-11

    Austin K. LeSueur, Nari Tao, Abigail G. Doyle, Matthew S. Sigman

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  11. Machine learning-guided strategies for reaction conditions design and optimization

    Beilstein Journal of Organic Chemistry · 2024-10-04

    Lung-Yi Chen, Yi‐Pei Li

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  12. Active learning high coverage sets of complementary reaction conditions

    Digital Discovery · 2025-01-01

    Sofia Sivilotti, David Friday, Nicholas E. Jackson

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  13. Recommending reaction conditions with label ranking

    Chemical Science · 2025-01-01

    Eunjae Shim, Ambuj Tewari, Tim Cernak, Paul M. Zimmerman

    Read original paper ↗ ·

  14. Accelerating the Development of Sustainable Catalytic Processes through Data Science

    Organic Process Research & Development · 2025-01-02

    Jason M. Stevens, Jacob M. Ganley, Matthew J. Goldfogel, Ariel Furman, Steven R. Wisniewski

    Read original paper ↗ ·

  15. High‐throughput Experimentation Enables the Development of a Nickel‐catalyzed Cyanation Platform for (Hetero)aryl Halides

    Chemistry - A European Journal · 2025-01-14

    Vincent Porte, Philipp Kollmus, Eloísa Serrano, Marco Santagostino

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  16. Tetrahydroxydiboron

    Encyclopedia of Reagents for Organic Synthesis · 2025-07-01

    Sarah Little, Jane Trice, Steven M. F. Kennedy, Benjamin J. Stokes

    Read original paper ↗ ·

  17. Nickel-Catalyzed Aryl Borylations: Opportunities and Challenges for Innovation

    Journal of the American Chemical Society · 2026-01-02

    Joshua B. McManus, Grace P. Ahlqvist, Colton R. Davis, Louis de Lescure, Vaishnavi N. Nair, Andreas R. Rötheli, Brenda J. Burke, Jason S. Tedrow

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  18. Integration of Proximal Alkoxide and Lewis Acidic Cations To Boost Nickel-Catalyzed Borylation

    Organic Letters · 2026-01-19

    Benjamin S. Grills, Jennifer A. Garden, Benjamin N. Bhawal

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  19. Yield Prediction of Organic Reactions in Biased Data Sets via Positive-Unlabeled Learning

    Journal of the American Chemical Society · 2026-04-01

    Florian Boser, Jan C. Spies, Frank Glorius

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  20. Precision orientation of hydrogen evolution performance of iron-based electrocatalysts empowered by machine learning: From electronic structure regulation to rational construction

    Composites Science and Technology · 2026-05-07

    Yan Hu, Senlin Tian, Yingjie Li

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  21. Data driven reveals the upgrading mechanism of waste PET electrolysis: Research progress of machine learning in collaborative production of high-value chemicals and green hydrogen energy

    Renewable and Sustainable Energy Reviews · 2026-07-31

    Jun Deng, Xuejun Zhu, Yuanchuan Ren, Cheng Wang, Nanqi Ren

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  22. Structured HTE Data and Integrated Bayesian Optimization Accelerate Scalable Amidation Process Development

    ACS Organic & Inorganic Au · 2026-08-17

    Jason M. Stevens, Dung L. Golden, Nikki Dare, Shubhangi Aggarwal, David Del Valle, Stacey DiSomma, Michael C. Eng, A.H. Furman, Lauren Grant, Diane Hendrix, Bilal Hoblos, Jiajie Huo, Mikalai Malashchonak, Ketleine Miller, Emily Mumford, Cheng Peng, Lingxiang Lu, Donggeon Nam, F. E. ROBERTS, Victor W. Rosso, Eric M. Saurer, Sushant Singh, Dmitriy Snetkov, Anton Terekh, Alexander E. Waked, Michael Williams, Chengmin Zhang

    Read original paper ↗ ·

  23. Machine Learning for Synthetic Organic Chemistry: Methods, Applications, and Best Practices

    Angewandte Chemie Novit · 2026-08-28

    Niklas Hölter, Felix Katzenburg, Florian Boser, Frank Glorius

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  24. Nickel as a Competitive Drop-In Alternative to Palladium in Thermal C–O Cross-Couplings of Aliphatic Alcohols with Heteroaryl Halides: A High-Throughput Experimentation Study

    Organic Process Research & Development · 2026-09-23

    Kathleen M. Morrison, Emily C. Jackson, Alexis Lavallée, Faral Akhtar, Martin Priester, Devin Deussen, Philipp M. Holstein, Mark Stradiotto

    Read original paper ↗ ·
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