Combining computational fluid dynamics, photon fate simulation and machine learning to optimize continuous-flow photocatalytic systems-Reference-Cited by-同舟云学术

Combining computational fluid dynamics, photon fate simulation and machine learning to optimize continuous-flow photocatalytic systems

Published:2023 Issue:9 Volume:8 Page:2119-2133
ISSN:2058-9883
Container-title:Reaction Chemistry & Engineering
language:en
Short-container-title:React. Chem. Eng.

Author:

de Oliveira Gabriela X.¹^ORCID,Kuhn Simon²^ORCID,Riella Humberto G.¹,Soares Cíntia¹,Padoin Natan¹^ORCID

Affiliation:

1. Laboratory of Materials and Scientific Computing (LabMAC), Department of Chemical and Food Engineering, Federal University of Santa Catarina, Campus Universitário Reitor João David Ferreira Lima, 88040-900, Florianópolis, Santa Catarina, Brazil

2. Department of Chemical Engineering, KU Leuven, Celestijnenlaan 200F, 3001 Leuven, Belgium

Abstract

Photoredox catalysis is a thriving field in chemistry. Microfluidics bring advantages for light-mediated reactions. CFD, ray-tracing, and machine learning hold promise in advancing microflow techniques.

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

Royal Society of Chemistry (RSC)

Subject

Fluid Flow and Transfer Processes,Process Chemistry and Technology,Chemical Engineering (miscellaneous),Chemistry (miscellaneous),Catalysis

Link

http://pubs.rsc.org/en/content/articlepdf/2023/RE/D3RE00239J

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