A multi-scale study of 3D printed Co-Al2O3 catalyst monoliths versus spheres
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Author(s)
Type
Journal Article
Abstract
This study demonstrates the characteristics of two model packing configurations: 3D printed (3DP) catalyst monoliths on the one hand, and their conventional counterparts, packed beds of spheres, on the other. Cobalt deposited on alumina is selected as a convenient model system for this work, due to its wide spread use in many catalytic reactions. 3DP constructs were produced from alumina powder impregnated with cobalt nitrate while the alumina spheres were directly impregnated with the same cobalt nitrate precursor. The form of the catalyst, the impregnation process, as well as the thermal history, were found to have a significant effect on the resulting cobalt phases. Probing the catalyst bodies in situ by XRD-CT indicated that the level of dispersion of identified Co phases (Co3O4 reduced to CoO) across the support is maintained under reduction conditions. The packed bed of spheres exhibits a non-uniform distribution of cobalt phases, including a core-shell morphology with an average crystallite size of 10–14 nm across the sphere, while the 3DP monolith exhibits a uniform distribution of cobalt phases with an average crystallite size of 5–12 nm upon reduction from Co3O4 to CoO. Computational Fluid Dynamics (CFD) modelling was carried out to develop digital twins and assess the effect of the geometry of both configurations on the pressure drop and velocity profiles. Finally, the activity of both Cobalt-based catalyst geometries was assessed in terms of their conversion, selectivity and turn over frequencies under model multiphase (selective oxidation) reaction conditions, which showed that the desired 3D printed monolithic geometries can offer distinct advantages to the reactor design.
Date Issued
2023-11-15
Date Acceptance
2023-07-01
Citation
Chemical Engineering Journal Advances, 2023, 16, pp.1-5
ISSN
2666-8211
Publisher
Elsevier
Start Page
1
End Page
5
Journal / Book Title
Chemical Engineering Journal Advances
Volume
16
Copyright Statement
© 2023 Vlaamse Instelling voor Technologisch Onderzoek NV (VITO). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND
license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Identifier
http://dx.doi.org/10.1016/j.ceja.2023.100538
Publication Status
Published
Article Number
100538
Date Publish Online
2023-07-26