Browse by author
Lookup NU author(s): Dr Fernando Russo AbegaoORCiD
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
Spatially-resolved and unresolved magnetic resonance measurements are used in combination with a partial least squares regression (PLSR) method to measure chemical composition within catalyst pellets during the 1-octene hydrogenation reaction occurring in a fixed bed of 0.3 wt% Pd/Al2O3 catalyst pellets. The PLSR method is used to discriminate between chemical species within and external to the void space of the catalyst pellets. The spatially-resolved data show that the hydrogenation and isomerisation reactions are dominant in the upper and lower region of the reactor, respectively. The local intra-pellet compositions also show product accumulation inside catalyst pellets consistent with reaction occurring under conditions of mass transfer limitation. An average measure of the intra-pellet composition within the whole bed was then used to estimate the liquid-solid mass transfer coefficient during the course of the reaction. The values of kLSkLS obtained from the NMR measurements were in the range 0.15 × 10-5 m s-1 < kLSkLS < 0.25 × 10-5 m s-1, for reactor operating conditions characterised by gas and liquid Reynolds numbers 0.2 < ReLReL < 0.6 and 0.1< ReGReG <0.3; these values are shown to be consistent with those predicted by existing literature correlations. Closest agreement was found with values predicted from dissolution experiments performed under similar hydrodynamic conditions in trickle flow. In addition to introducing a method for the direct measurement of kLSkLS, the data presented also confirm that estimates of kLSkLS are more accurate when performed in an environment in which the hydrodynamics and fluid-solid contacting conditions are representative of the system of interest.
Author(s): Zheng Q, Russo Abegão FJ, Sederman A, Gladden LF
Publication type: Article
Publication status: Published
Journal: Chemical Engineering Science
Year: 2017
Volume: 171
Pages: 614-624
Print publication date: 02/11/2017
Online publication date: 02/05/2017
Acceptance date: 29/04/2017
Date deposited: 12/11/2019
ISSN (print): 0009-2509
ISSN (electronic): 1873-4405
Publisher: Elsevier
URL: http://doi.org/10.1016/j.ces.2017.04.051
DOI: 10.1016/j.ces.2017.04.051
Altmetrics provided by Altmetric