Papers citing Prediction of Major Regio‐, Site‐, and Diastereoisomers in Diels–Alder Reactions by Using Machine‐Learning: The Importance of Physically Meaningful Descriptors
Active learning guides discovery of a champion four-metal perovskite oxide for oxygen evolution electrocatalysis
Nature Materials · 2023
Junseok Moon, Wiktor Beker, Marta Siek, Jiheon Kim, Hyeon Seok Lee, Taeghwan Hyeon, Bartosz A. Grzybowski
Read original paper ↗ ·Extraction yield prediction for the large-scale recovery of cannabinoids
Digital Discovery · 2023
Hart Plommer, Isaiah O. Betinol, Tom Dupree, Markus Roggen, Jolene P. Reid
Read original paper ↗ ·A machine learning approach for predicting the reactivity power of hypervalent iodine compounds
Artificial Intelligence Chemistry · 2023
Vaneet Saini, Ramesh Kataria, Shruti Rajput
Read original paper ↗ ·Mechanisms and origins of stereoselectivity in the NHC-catalyzed oxidative reaction of enals and pyrroles: a density functional theory study
Physical Chemistry Chemical Physics · 2024
Yan Li, Mingchao Zhang, Zhiqiang Zhang
Read original paper ↗ ·Repurposing quantum chemical descriptor datasets for on-the-fly generation of informative reaction representations: application to hydrogen atom transfer reactions
Digital Discovery · 2024
Javier Emilio Alfonso Ramos, Rebecca M. Neeser, Thijs Stuyver
Read original paper ↗ ·Machine learning enables the prediction of amide bond synthesis based on small datasets
Acta Physico-Chimica Sinica · 2024
Xinghai Li, Zhisen Wu, Lijing Zhang, Shengyang Tao
Read original paper ↗ ·Bi-directional prediction of hydrothermal carbonization characteristics of agroforestry and livestock wastes with variable components: Graph learning model-aided waste recycle
Journal of Cleaner Production · 2024
Zi-Kai Lin, Chao-Sheng Li, Rong-Rong Cai, Yan-Qiu Long
Read original paper ↗ ·Towards universal substituent constants: Parameterizing bond critical point properties with electronegativity descriptors
International Journal of Quantum Chemistry · 2024
Kevin M. Lefrancois‐Gagnon, Robert C. Mawhinney
Read original paper ↗ ·Artificial Intelligence for Retrosynthetic Planning Needs Both Data and Expert Knowledge
Journal of the American Chemical Society · 2024
Felix Strieth‐Kalthoff, Sara Szymkuć, Karol Molga, Alán Aspuru‐Guzik, Frank Glorius, Bartosz A. Grzybowski
Read original paper ↗ ·Computational synthesis design for controlled degradation and revalorization
Nature Synthesis · 2024
Anna Żądło‐Dobrowolska, Karol Molga, Olga O. Kolodiazhna, Sara Szymkuć, Martyna Moskal, Rafał Roszak, Bartosz A. Grzybowski
Read original paper ↗ ·Modern Automation in Organic Synthesis Laboratories
Elsevier eBooks · 2024
Pascal Miéville, Florian de Nanteuil
Read original paper ↗ ·Efficiency-optimized Diels-Alder reactions based on random forest
Molecular Catalysis · 2024
Lei Zhang, Hang Dong, An Lin, Rui Lu, Xuhai Zhu, Min Zhang, Fang Lü
Read original paper ↗ ·Data-Efficient, Chemistry-Aware Machine Learning Predictions of Diels–Alder Reaction Outcomes
Journal of the American Chemical Society · 2024
Angus B. Keto, Taicheng Guo, Morgan Underdue, Thijs Stuyver, Connor W. Coley, Xiangliang Zhang, Elizabeth H. Krenske, Olaf Wiest
Read original paper ↗ ·Developing deep learning-based large-scale organic reaction classification model via sigma-profiles
Green Chemical Engineering · 2024
Wenlong Wang, Chenyang Xu, Jian Du, Lei Zhang
Read original paper ↗ ·AI for organic and polymer synthesis
Science China Chemistry · 2024
Xin Hong, Qi Yang, Kuangbiao Liao, Jianfeng Pei, Mao Chen, Fanyang Mo, Hua Lu, Wen-Bin Zhang, Haisen Zhou, Jiaxiao Chen, Lebin Su, Shuo‐Qing Zhang, Siyuan Liu, Xu Huang, Yizhou Sun, Yuxiang Wang, Zexi Zhang, Zhunzhun Yu, Sanzhong Luo, Xuefeng Fu, Shu‐Li You
Read original paper ↗ ·Harnessing Electro-Descriptors for Mechanistic and Machine Learning Analysis of Photocatalytic Organic Reactions
Journal of the American Chemical Society · 2024
Luhan Dai, Yulong Fu, Mengran Wei, Fangyuan Wang, Bailin Tian, Guoqiang Wang, Shuhua Li, Mengning Ding
Read original paper ↗ ·When Do Quantum Mechanical Descriptors Help Graph Neural Networks to Predict Chemical Properties?
Journal of the American Chemical Society · 2024
Shih‐Cheng Li, Haoyang Wu, Angiras Menon, Kevin Spiekermann, Yi‐Pei Li, William H. Green
Read original paper ↗ ·6‐Hydroxy Picolinohydrazides Promoted Cu(I)‐Catalyzed Hydroxylation Reaction in Water: Machine‐Learning Accelerated Ligands Design and Reaction Optimization
Angewandte Chemie · 2024
Lanting Xu, Jiazhou Zhu, Xiaodong Shen, Jialei Chai, Lei Shi, Bing Wu, Wei Li, Dawei Ma
Read original paper ↗ ·6‐Hydroxy Picolinohydrazides Promoted Cu(I)‐Catalyzed Hydroxylation Reaction in Water: Machine‐Learning Accelerated Ligands Design and Reaction Optimization
Angewandte Chemie International Edition · 2024
Lanting Xu, Lanting Xu, Jiazhou Zhu, Xiaodong Shen, Jialei Chai, Lei Shi, Bin Wu, Wei Li, Wei Li, Dawei Ma
Read original paper ↗ ·Machine learning-guided strategies for reaction conditions design and optimization
Beilstein Journal of Organic Chemistry · 2024
Lung-Yi Chen, Yi‐Pei Li
Read original paper ↗ ·Alkylation process intensification
Elsevier eBooks · 2025
Weizhen Sun, Weizhong Zheng, Ling Zhao, Jinzhu Li, Huanxin Gao
Read original paper ↗ ·Computational tools for the prediction of site- and regioselectivity of organic reactions
Chemical Science · 2025
Lukas M. Sigmund, Michele Assante, Magnus J. Johansson, Per‐Ola Norrby, Kjell Jorner, Mikhail Kabeshov
Read original paper ↗ ·Molecular Machine Learning Approach to Enantioselective C–H Bond Activation Reactions: From Generative AI to Experimental Validation
Chemical Science · 2025
Ajnabiul Hoque, Taiwei Chang, Jin‐Quan Yu, Raghavan B. Sunoj
Read original paper ↗ ·C–H Aminoalkylation of 5-Membered Heterocycles: Influence of Descriptors, Data Set Size, and Data Quality on the Predictiveness of Machine Learning Models and Expansion of the Substrate Space Beyond 1,3-Azoles
The Journal of Organic Chemistry · 2025
Stephanie Felten, Cyndi Qixin He, Marion H. Emmert
Read original paper ↗ ·Quantum mechanical and machine learning prediction of rotational energy barriers in halogenated aromatic alcohols
Journal of Molecular Modeling · 2025
Steven T. Cerabona, Gordon G. Brown, Leah B. Casabianca
Read original paper ↗ ·Integrating a multitask graph neural network with DFT calculations for site-selectivity prediction of arenes and mechanistic knowledge generation
Nature Synthesis · 2025
Xinran Chen, Zijing Zhang, Xin Hong, Lutz Ackermann
Read original paper ↗ ·Stabilities and Limitations in the Reactivity of Phosphorus Ylide‐Based Aluminum– and Gallium–Carbon Ambiphiles: A Combined Experimental and Computational Approach
European Journal of Inorganic Chemistry · 2025
Felix Krämer, Pascal Weisenburger, Israel Fernández, Frank Breher
Read original paper ↗ ·Machine learning predictions for regioselectivity of hydroformylation reactions: leveraging limited data for high-precision results
Pure and Applied Chemistry · 2025
Jiaqi Wu, Ye Liu, Xue‐Qing Gong
Read original paper ↗ ·Computational Investigation of a CO2 Conversion Strategy via Diels–Alder Reaction in a Carbon Capture Solvent
ACS Omega · 2025
Difan Zhang, Melissa T. Manetsch, Sarah I. Allec, Loukas Kollias, Roger J. Rousseau, David J. Heldebrant, Vassiliki‐Alexandra Glezakou
Read original paper ↗ ·Predicting Reactivity with Machine Learning
Venue not supplied by source · 2025
Lauriane Jacot‐Descombes, Kjell Jorner
Read original paper ↗ ·Sustainable production of chemicals by algorithm-assisted (bio)synthesis
Nature Reviews Bioengineering · 2025
Bartosz A. Grzybowski, Anna Żądło‐Dobrowolska, Natalia R. Onishchenko, Eric S. Larsen
Read original paper ↗ ·Deconvoluting the Effects of Substituents on Reaction Barriers through Machine Learning: The Case of Brønsted Acid-Mediated Nazarov Cyclizations
The Journal of Organic Chemistry · 2025
Angus B. Keto, Elizabeth H. Krenske
Read original paper ↗ ·Conformation Dependent Features of Bisphosphine Ligands
The Journal of Organic Chemistry · 2025
Brock A. Stenfors, Jamie A. Cadge, Santeri Aikonen, Guilian Luchini, Jessica Wahlers, Kevin Koh, Mikko Muuronen, Maximilian Menche, Mark Pfeifle, Angus B. Keto, Robert S. Paton, Matthew S. Sigman, Olaf Wiest
Read original paper ↗ ·Freedom Space 3.0: ML-Assisted Selection of Synthetically Accessible Small Molecules
Journal of Chemical Information and Modeling · 2025
Anna Kapeliukha, Serhii Hlotov, Mykola Protopopov, Igor Dziuba, Maryna Vasylchuk, Dmitriy M. Panov, Olga O. Tarkhanova, Yurii S. Moroz
Read original paper ↗ ·Anticipating the Selectivity of Intramolecular Cyclization Reaction Pathways with Neural Network Potentials
Journal of Chemical Theory and Computation · 2025
Nicholas Casetti, Dylan M. Anstine, Olexandr Isayev, Connor W. Coley
Read original paper ↗ ·Conceptual DFT Meets Machine Learning: A New Route to Enhanced Diels–Alder Reactivity
Journal of Computational Chemistry · 2025
Michiel Jacobs, Lise Vermeersch, Freija De Vleeschouwer
Read original paper ↗ ·Reaction Performance Prediction and Reaction Condition Optimization
Springer eBooks · 2025
Mingyue Zheng
Read original paper ↗ ·Physics-informed conformal prediction of aromatic C–H site selectivity: guaranteed coverage prediction sets for electrophilic aromatic substitution
Physical Chemistry Chemical Physics · 2026
Ali A. Khairbek, Abdullah Yahya Abdullah Alzahrani, Sana Ben Moussa, Thangaiyan Pooventhiran, Renjith Thomas
Read original paper ↗ ·Reaction mechanism and origins of stereoselectivity of an NHC-catalyzed reaction between 2-bromoenals and 3-aminoindoles
Catalysis Science & Technology · 2026
Xinyi Sun, Yuxuan Song, Xiaoyue Men, YJ Li, Zhiqiang Zhang
Read original paper ↗ ·A Machine Learning-Guided Study of Structure–Reactivity Relationships in Diels–Alder Cycloadditions
The Journal of Organic Chemistry · 2026
Amir Mahdian, Kaveh Farshadfar, Kari E. Laasonen
Read original paper ↗ ·Automated DFT-Machine Learning Integration Enables Data-Efficient and Generalizable Feasibility Predictions in Metallaphotoredox sp 2 –sp 3 Cross-Coupling Reactions
ACS Catalysis · 2026
Michele Assante, Sara Pahlén, Brenda Pijper, Lili Cao, Ole Specht, Nadja A. Simeth, Alexei A. Lapkin, Clive Green, Ola Engkvist, Giulia Bergonzini, Mikhail Kabeshov
Read original paper ↗ ·Staged Diversity‐Constrained Machine Learning for High‐Dimensional Reaction Condition Optimization
Angewandte Chemie International Edition · 2026
Shu‐Wen Li, Shan Chen, João C. A. Oliveira, Shimin Zhang, Lutz Ackermann, Xin Hong
Read original paper ↗ ·Yield Prediction of Organic Reactions in Biased Data Sets via Positive-Unlabeled Learning
Journal of the American Chemical Society · 2026
Florian Boser, Jan C. Spies, Frank Glorius
Read original paper ↗ ·Robots and Minimal, Physics‐Informed Features: A Hybrid Framework for Enzyme Catalysis
Advanced Science · 2026
Natalia R. Onishchenko, Eric S. Larsen, Govind Paneru, Kisung Lee, Diana V. Kolygina, Yankai Jia, Elizabeth Maria Clarissa, Wai‐Shing Wong, Bartosz A. Grzybowski
Read original paper ↗ ·