Cross Reference Logo
Citations to this article as recorded by CrossRef and RSC Journals (13 citations).

A comprehensive review on MoSe2 nanostructures with an overview of machine learning techniques for supercapacitor applications
Robertson B, Sapna R, Vinod Hegde and Hareesh K
RSC Adv., 2024, 14, 37644
DOI: 10.1039/D4RA06114D

Internally Catalyzed Hydrogen Atom Transfer (I-CHAT)—A New Class of Reactions in Combustion Chemistry
Rubik Asatryan, Jason Hudzik, Venus Amiri and Mark T. Swihart
Molecules, 2025, 30, 524
DOI: 10.3390/molecules30030524

Machine Learning for Experimental Reactivity of a Set of Metal Clusters toward C–H Activation
Xi-Guan Zhao, Qi Yang, Ying Xu, Qing-Yu Liu, Zi-Yu Li, Xiao-Xiao Liu, Yan-Xia Zhao and Sheng-Gui He
J. Am. Chem. Soc., 2024, 146, 12485
DOI: 10.1021/jacs.4c00501

Hybridised mechanistic and machine learning digital twins for modelling and optimising chemical processes in flow: A comparative analysis of parallel and series-based hybridisation
Nur Aliya Nasruddin, Nazrul Islam, Sergio Vernuccio and John Oyekan
Chemical Engineering Journal Advances, 2025, 23, 100775
DOI: 10.1016/j.ceja.2025.100775

Perspective on automated predictive kinetics using estimates derived from large datasets
William H. Green
Int J of Chemical Kinetics, 2024
DOI: 10.1002/kin.21744

Enhancing the Predictive Kinetics of Intramolecular H-Migration Reactions of Ether Peroxy Radicals by Integrating Machine Learning with Quantum Chemistry: A Comparative Study of Generic Rate Rules and Machine Learning Techniques
Jingwei Zhang, Siyu Chen, Haisheng Ren and Zerong Li
Ind. Eng. Chem. Res., 2025, 64, 9900
DOI: 10.1021/acs.iecr.5c00041

Machine learning-guided strategies for reaction conditions design and optimization
Lung-Yi Chen and Yi-Pei Li
Beilstein J. Org. Chem., 2024, 20, 2476
DOI: 10.3762/bjoc.20.212

Kinetic and Mechanistic Study of Polycarbodiimide Formation from 4,4′-Methylenediphenyl Diisocyanate
Marcell D. Csécsi, R. Zsanett Boros, Péter Tóth, László Farkas and Béla Viskolcz
IJMS, 2025, 26, 8570
DOI: 10.3390/ijms26178570

Machine learning applications for thermochemical and kinetic property prediction
Lowie Tomme, Yannick Ureel, Maarten R. Dobbelaere, István Lengyel, Florence H. Vermeire, Christian V. Stevens and Kevin M. Van Geem
Reviews in Chemical Engineering, 2025, 41, 419
DOI: 10.1515/revce-2024-0027

Predicting Rate Constants of Hydrogen Abstraction Reactions between OH/HO2 and Alkanes by Machine Learning Models
Min Xia, Yu Zhang, Hongwei Song, Ya Jia and Minghui Yang
J. Phys. Chem. A, 2025, 129, 309
DOI: 10.1021/acs.jpca.4c07426

Resolving the Coverage Dependence of Surface Reaction Kinetics with Machine Learning and Automated Quantum Chemistry Workflows
Matthew S. Johnson, David H. Bross and Judit Zádor
J. Phys. Chem. C, 2025, 129, 3469
DOI: 10.1021/acs.jpcc.4c06636

Machine Learning for Chemical Looping: Recent Advances and Prospects
Yiwen Song, Shenglong Teng, Diyan Fang, Yingjie Lu, Zehua Chen, Rui Xiao and Dewang Zeng
Energy Fuels, 2024, 38, 11541
DOI: 10.1021/acs.energyfuels.4c02110

Machine Learning Study of Methane Activation by Gas-Phase Species
Ying Xu, Zi-Yu Li, Qi Yang, Xi-Guan Zhao, Qian Li and Sheng-Gui He
J. Phys. Chem. A, 2025, 129, 1941
DOI: 10.1021/acs.jpca.4c06602