A Monte-Carlo-based sensitivity analysis of multicomponent diffusion in porous catalysts. (10th August 2018) - Donaubauer, Philipp J.; Hinrichsen, Olaf
Graphical abstract: Highlights: Monte-Carlo-based sensitivity analysis of three multicomponent diffusion models. Application to heterogeneously catalyzed gas-phase reaction-diffusion problems. High influence of pellet porosity, pore diameter and tortuosity factor. Binary friction model recommended as solely consistently derived method. Abstract: Molar fluxes inside porous catalysts can be calculated by means of multicomponent diffusion models. The state-of-the-art dusty-gas model competes with several alternatives, best-known the mean-transport pore model and the binary friction model. All three approaches combine Maxwell-Stefan-based transport with Knudsen diffusion and viscous Darcy flow. However, the models have not yet been compared theoretically, when applied to actual diffusion-reaction problems. Here we successively show that these diffusion models result in very similar behavior when applied to CO2 methanation, methanol synthesis and oxidative dehydrogenation of ethane. By comparing molar fractions, temperature and pressure profiles, latter revealed the most striking deviations between the models. Monte-Carlo-based, global sensitivity analyses on the catalyst effectiveness factors exhibit significant impact of catalyst properties, even at low uncertainties. At equal uncertainty levels, highest sensitivity was observed for the pellet porosity, followed by the tortuosity factor and the pore diameter. Overall, the choice of the diffusion model appears to have low influence on the regarded reaction-diffusion models. Hence, we recommend the binary friction model as most reliable, since both other approaches suffer from inconsistencies in the treatment of the viscous flux terms. These findings can be used as valuable basis for modeling multicomponent diffusion inside porous catalysts employed in heterogeneously-catalyzed gas-phase reactions. This work has been selected by the Editors as a Featured Cover Article for this issue.