Abstract
By employing multi-scale random models of γ -alumina, we have studied the influence of porosity, grain aspect ratio and aggregation state on the effective diffusion coefficient. Multi-scale Boolean models of platelets were used to produce digital volumes reproducing the alumina porous space. Iterative fast Fourier transform numerical simulation of Fick’s diffusion were performed on the volume to obtain the effective diffusion coefficient. The tortuosity factors of the various simulated models show a simple dependence with pore volume fraction with an exponent guided by the platelet aspect ratio and the aggregation state. Comparisons with proton pulsed-field gradient nuclear magnetic resonance spectrometry show a satisfactory agreement.
Highlights
Porous c-alumina is a widely used support for heterogeneous catalysts in the refining and petrochemical industry
By employing multi-scale random models of c-alumina, we have studied the influence of porosity, grain aspect ratio and aggregation state on the effective diffusion coefficient
The aim of this paper is to explore the influence of platelet morphology and aggregation state on the transport properties of c-alumina with the help of random sets models
Summary
Porous c-alumina is a widely used support for heterogeneous catalysts in the refining and petrochemical industry. Among important industrial processes under internal diffusional limitation, one finds hydrodemetalation of vacuum residues [1], fixed-bed Fischer-Tropsch synthesis [2] and selective hydrogenation of unsaturated hydrocarbons [3, 4]. For these processes, diffusion at the catalyst pellet’s scale occurs at a lower pace than the chemical reaction, leading to internal diffusional limitations. Increasing the diffusion efficiency may lead to increased catalyst efficiency and overall process conversion
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