Author, as appears in the article.: Sabadell-Rendón, A; Kazmierczak, K; Morandi, S; Euzenat, F; Curulla-Ferré, D; López, N
Department: Química Física i Inorgànica
URV's Author/s: Lopez Alonso, Nuria / Morandi, Santiago / Sabadell Rendón, Albert
Keywords: Mechanism Mass-transfer Kinetics Fixed-bed reactors Chemistry Cfd
Abstract: Multiscale techniques integrating detailed atomistic information on materials and reactions to predict the performance of heterogeneous catalytic full-scale reactors have been suggested but lack seamless implementation. The largest challenges in the multiscale modeling of reactors can be grouped into two main categories: catalytic complexity and the difference between time and length scales of chemical and transport phenomena. Here we introduce the Automated MUltiscale Simulation Environment AMUSE, a workflow that starts from Density Functional Theory (DFT) data, automates the analysis of the reaction networks through graph theory, prepares it for microkinetic modeling, and subsequently integrates the results into a standard open-source Computational Fluid Dynamics (CFD) code. We demonstrate the capabilities of AMUSE by applying it to the unimolecular iso-propanol dehydrogenation reaction and then, increasing the complexity, to the pre-commercial Pd/In2O3 catalyst employed for the CO2 hydrogenation to methanol. The results show that AMUSE allows the computational investigation of heterogeneous catalytic reactions in a comprehensive way, providing essential information for catalyst design from the atomistic to the reactor scale level. AMUSE is a multiscale framework integrating detailed atomistic information on materials and reactions to predict the performance of heterogeneous catalytic full-scale reactors.
Thematic Areas: Computer science, interdisciplinary applications Chemistry, multidisciplinary Chemistry (miscellaneous)
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: nuria.lopez@urv.cat santiago.morandi@estudiants.urv.cat albert.sabadell@estudiants.urv.cat
Record's date: 2024-08-03
Papper version: info:eu-repo/semantics/publishedVersion
Link to the original source: https://pubs.rsc.org/en/content/articlelanding/2023/dd/d3dd00163f
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Digital Discovery. 2 (6): 1721-1732
APA: Sabadell-Rendón, A; Kazmierczak, K; Morandi, S; Euzenat, F; Curulla-Ferré, D; López, N (2023). Automated MUltiscale simulation environment. Digital Discovery, 2(6), 1721-1732. DOI: 10.1039/d3dd00163f
Article's DOI: 10.1039/d3dd00163f
Entity: Universitat Rovira i Virgili
Journal publication year: 2023
Publication Type: Journal Publications