Prediction of diffusivity and conversion of n-decane and CO in coated Pt/γ-Al2O3 catalyst depending on porous layer morphology

Abstract

The conversion in monolith reactors for automotive exhaust gas aftertreatment can be limited by diffusion in the catalytic layer. This is particularly important for monolith reactors with multiple coated layers. In this paper, we present detailed modeling methodology for prediction of effective diffusivity based on the actual structure of a porous coating (particle and pore size distributions). We demonstrate the approach on diffusion and oxidation of n-decane and CO in Pt/γ-Al2O3 layers typically used in diesel oxidation catalysts. To validate the model predictions experimentally, several layers were coated with uniform thickness on flat metal foils, and their macroporous structure was controlled by alumina particle size distribution, pore templates and compaction techniques. A multi-scale modelling approach was then applied to predict effective diffusivity and impact of the internal diffusion limitations on the achieved conversions. Diffusion of CO and n-decane was simulated on a micro-scale together with oxidation reactions in a 3D digitally reconstructed porous layer structure. The results were combined with a macroscopic 1D plug-flow model to calculate the reactor outlet conversions. Good agreement was achieved between the predicted and the measured conversions both for n-decane and CO oxidation. The predicted effective diffusion coefficients Deff through the tested Pt/γ-Al2O3 layers were 1.4, 3.6 and 6.4×10−6m2s−1 for CO at T=298K in compact, standard and macropore-templated sample, respectively. The corresponding diffusivities for n-decane were 0.53, 1.2 and 2.0×10−6m2s−1, respectively. The model quantified relative contributions of volume and Knudsen diffusion regimes to overall transport as well as temperature dependence of Deff.