Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/37716
Title: Kinetic optimization of multilayered photocatalytic reactors
Authors: Claes, T
Fransen, S
Degreve, J
Van Gerven, T
LEBLEBICI, Mumin enis 
Issue Date: 2021
Publisher: ELSEVIER SCIENCE SA
Source: Chemical engineering journal (1996. Print), 421 (Art N° 127794)
Abstract: Translucent structured reactors have proven to be an effective design to scale up microreactors. By generating surface area, this flexible reactor design allows to increase the catalyst loading without increasing the catalyst layer thickness, which is beneficial in tackling diffusion limitations in single-channel reactors. However, adding more depth to such a structure by replicating the channels increases the number of scattering boundaries which leads to energy losses. As a result, there is a design problem which seeks to define the optimal catalyst layer thickness and optimal number of repeating boundaries on a light path. Most of the models are numerically solved and very specific to the reactor type being modeled. In this work, a catalyst layer mass balance model is used to construct a model of a translucent structured reactor which takes into account internal mass transfer effects and which can be used to design an optimal structure. The model is simplified to obtain a graphical tool and an analytical model which is validated to estimate the overall reactor kinetics as a function of dimensionless groups. For a conventional range of parameters, the optimal catalyst layer thickness and optimal number of structural layers was equal to 2 mu m and 4, respectively. The presented tools in this work are a step forward in the fabrication of design methods for photocatalytic reactor structures. This way, the designer can easily estimate the design outcome without any complex calculations.
Keywords: Photocatalysis;Structured reactors;Kinetic optimization;Design correlations;Graphical tool;Dimensionless numbers
Document URI: http://hdl.handle.net/1942/37716
ISSN: 1385-8947
e-ISSN: 1873-3212
DOI: 10.1016/j.cej.2020.127794
ISI #: 000663677900003
Category: A1
Type: Journal Contribution
Appears in Collections:Research publications

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