281775 Improved Mixing in Dry Catalyst Impregnation Using a Double Cone Blender: An Experimental and Computational Approach

Tuesday, October 30, 2012: 8:30 AM
Conference B (Omni )
Yangyang Shen, Rutgers University, Piscataway, NJ and M. Silvina Tomassone, Chemical and Biochemical Engineering, Rutgers University, Piscataway, NJ

In the manufacture of heterogeneous catalysts, the impregnation of active metals onto a porous catalyst support is a crucial preparation step that may significantly affect the activity and selectivity of the resulting catalysts. In a typical dry impregnation (pore filling or incipient wetness impregnation) process, metal solutions are sprayed over a powder bed in a mixing vessel until the pore volume is reached. Traditionally, these systems are studied experimentally, but such experiments can be difficult to examine quantitatively, and the analysis is often inaccurate due to frequent disturbance to the powder bed. In this work, Discrete Element Method (DEM) simulations coupled with a novel algorithm allowing the transfer of fluid to and between particles were used in combination with geometrically equivalent experiments to model dry catalyst impregnation with the goal of improving the mixing and content uniformity of the resulting catalyst powder. While the developed model and corresponding algorithm have previously shown excellent agreement with matching experiments, the double cone blender itself does not establish an optimal content uniformity alone. As a result various improvements were simulated and subsequently analyzed within the system including baffle and nozzle configurations. In this study, it is shown that the use of both two and four baffles significantly reduced the mixing time for a double cone blender, thus increasing overall content uniformity while maintaining other important process parameters. No noticeable difference was evident between two and four baffles. Additionally, matching one-to-one experiments with baffles were also conducted at three distinct fill levels to validate that the addition of as little as two baffles can significantly improve mixing and content uniformity, as discovered in the DEM simulations. In addition, particle tracking techniques unique to the simulations have better quantified the poor axial mixing in the double cone, and further established the improved mixing generated by adding baffles. The culmination of this work has been the development of simulations capable of analyzing dry catalyst impregnation in limitless parameters, geometries, and conditions for improving overall mixing, content uniformity, and product quality.

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See more of this Session: Dynamics and Modeling of Particulate Systems
See more of this Group/Topical: Particle Technology Forum