Dry catalyst impregnation in a double cone blender: A computational and experimental analysis

Abstract

The dry impregnation of catalysts is widely used in industrial catalyst preparation, however, until recently, it has not been possible to model this system computationally. In this work, a novel algorithm for the spray and inter-particle transfer of fluid onto and within a rotating bed of granular catalyst support was explored using discrete element method (DEM). The simulations were validated by experiments utilizing a geometrically identical double cone blender fixed with a single nozzle impregnator. The effects of liquid flow rate and fill level were explored at a fixed rotation rate of 25rpm. Specifically, three flow rates of 1.5, 2.5 and 5L/h were selected and evaluated at a 30% and 45% fill fraction by volume. Mixing analysis and fluid concentration distributions were used both experimentally and computationally to investigate the propagation of fluid throughout the bed with the goal of modeling and improving industrial content uniformity. It was discovered that low flow rate systems and lower fill fractions resulted in better mixing and content uniformity throughout the bed. Results obtained from our model show good agreement with experiments, and therefore it was demonstrated that a novel fluid transfer algorithm incorporated into DEM could be used to accurately model dry catalyst impregnation, therefore introducing a new tool for optimizing catalyst manufacturing.