Neutron imaging to inform multi-scale simulations of catalytic reactors

Large-scale simulations of chemical reactions and processes are invaluable for optimising product yields, lowering energetic and financial costs, and ensuring the safe operation of a catalytic process. As such simulations, such as Computational Fluid Dynamics (CFD), are vital for developing more sustainable chemical processes. In this proposal we will use neutron imaging to give unique experimental insights into the diffusion of propane within a packed bed of a SAPO-34 catalyst to create unique multiscale reactor models.
Optimising catalytic industrial processes, and accelerating scale up of emerging technologies, relies heavily on in silico predictions and simulations, the precision of which depends on the accuracy of computational models. In particular, computational fluid dynamics (CFD) predicts variations in local flows and temperatures, within a catalytic fixed bed reactor, over a wide length scale (mm to m), while simultaneously kinetic models predict product and reagent concentrations. Systems involving impenetrable particles, considering surface reactions only, are facile to model. Porous catalysts require an extra level of complexity, as both bulk mass-transfer and pore-diffusion must be considered. Very few techniques can give this level of detail, making it an ideal method for validating, testing, and training CFD simulations for greater accuracy.