Themed collection Digital Catalysis
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The design and optimization of heterogeneous catalysts using computational methods
Computational design of catalytic materials is a high dimensional structure optimization problem that is limited by the bottleneck of expensive quantum computation tools. An illustration of interaction of different factors involved in the design and optimization of a catalyst.
Catal. Sci. Technol., 2024,14, 515-532
https://doi.org/10.1039/D3CY01160G
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Diffusion mechanisms and preferential dynamics of promoter molecules in ZSM-5 zeolite
Molecular 3-point turns are seen in molecular dynamics simulations of methanol and promoters of the CH3OH to CH3OCH3 reaction. The more catalytically active aromatic aldehydes limit methanol diffusion less than other promoters.
Catal. Sci. Technol., 2024,14, 3674-3681
https://doi.org/10.1039/D4CY00506F
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Influence of temperatures and loadings on olefin diffusion in MFI-type zeolites in one- to three-dimensions
A detailed understanding of the molecular diffusion in zeolite frameworks is crucial for analysing the factors controlling their catalytic performance in alkenes.
Catal. Sci. Technol., 2024,14, 1902-1910
https://doi.org/10.1039/D3CY01590D
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Kinetic modelling of cobalt-catalyzed propene hydroformylation: a combined ab initio and experimental fitting protocol
The mechanism of propene hydroformylation is studied with quantum chemistry and kinetic modelling. This yields detailed insight into mechanisms, and reveals the essential role of a complex between hydridocobalttricabonyl and toluene.
Catal. Sci. Technol., 2024,14, 961-972
https://doi.org/10.1039/D3CY01625K
About this collection
This themed collection of Catalysis Science & Technology, Guest Edited by Wei-Xue Li (0000-0002-5043-3088) (University of Science and Technology of China), Núria López (0000-0001-9150-5941) (ICIQ, Spain) & Evgeny Pidko (0000-0001-9242-9901) (TU Delft, The Netherlands) showcases cross-disciplinary cutting-edge advances in the application of advanced data techniques to catalysis science, including artificial intelligence, machine learning, high-throughput computational methods and other data science approaches and methodologies.