(104c) Experiments and Simulations on Particle Impregnation By Metal Solutions for Industrial Catalysts: From Fundamentals to Scale up | AIChE

(104c) Experiments and Simulations on Particle Impregnation By Metal Solutions for Industrial Catalysts: From Fundamentals to Scale up

Authors 

Tommassone, M. - Presenter, Rutgers University
Shen, Y., Rutgers University
Borghard, W., Rutgers University
Impregnation of active metals onto a porous support is a crucial step in the preparation of industrial heterogeneous catalysts. The process is typically performed in rotating vessels with a spray-nozzle to distribute the liquid until the pore volume is reached. The inter-particle variability of the impregnated liquids inside the particles can significantly affects the activity and selectivity of the resulting catalyst. Current scale-up practices lead to poor fluid distribution and inhomogeneity in metal content. The aim of this work is to understand the dynamic behavior of the particles under the spray nozzle, which is essential to achieve a desired content uniformity and to develop a scale-up model for the catalyst impregnation process. In this work, impregnation was explored by applying Discrete Element Method simulation techniques in conjunction with experimentation. The simulations were validated by experiments utilizing both a geometrically identical double cone and a cylindrical blender fixed with a single nozzle impregnator. In addition, we developed a novel fluid transfer model of metal solutions from the nozzle to the particles and between particles in the bed. Results obtained from our model show good agreement with experiments in the particle metal content along the axis of rotation. We also studied spheres and cylinders of different sizes and aspect ratios. Axial mixing analysis and liquid distributions are used to investigate the propagation of the fluid throughout the particle bed with the goal of understanding the effect of operational and material parameters and ultimately to improve fluid content uniformity in systems with particles of different morphologies. The fluid content uniformity is characterized by the relative standard deviation (RSD) of the liquid content from all the particles in the system. Our results show that cylinders always take less time to physically mix than spheres of the same diameter and mixing times are also shorter for cylinders of higher aspect ratios when compared to cylinders of smaller aspect ratio. Likewise, the times to reach good fluid content uniformity are shorter for cylinders with higher aspect ratios as compared with cylinders with lower aspect ratios. We found a strong linear correlation between the times to achieve good axial mixing and the times to achieve good fluid content uniformity in the entire particle bed, which suggests that mixing in the axial direction controls fluid uniformity in the entire particle bed. Lastly, we performed scale up studies on the impregnation process using two dimensionless numbers to characterize the system: Froude number (Fr) and flow rate number (CQ). In general, smaller flow rate numbers tend to give more homogeneous liquid distribution during and after the total liquid is sprayed; however, the there is a limit on how small a Froude number can be. We found optimal values for Froude and flow rate numbers. An optimal Fr number value is found when the RSD is minimal, which gives the best mixing performance. Using larger CQ numbers the spraying can be completed in shorter times, but the particles show greater inhomogeneity of the fluid content in the particle bed. An optimal value for the flow rate number CQ allows the impregnation process to finish in an acceptable time frame, and the final product to have a uniform distribution of metal. The ability to control catalyst impregnation and establish effective models for large batches can significantly reduce the amount of time required per batch while simultaneously achieving a more homogeneous liquid distribution.

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