Investigating particle-level dynamics to understand bulk behavior in a lab-scale Agitated Filter Dryer (AFD) using Discrete Element Method (DEM)

摘要

Agitated filter drying (AFD) is a complex physical-thermal separation process which involves isolating solutes from its mother liquor. In agro-chemical and pharmaceutical industry, filter-dryers are used for sequestering active ingredients (AIs) and key intermediates from the wet cake after the crystallization step. During the agitated drying phase, the mechanical agitation of the wet cake, implemented to enhance heat and mass transport, has been commonly observed to result in formation of undesired agglomerates that require further processing. Only relatively few experimental and computational studies of the effects of operating parameters and material properties on the drying and agglomeration growth kinetics have been described in the literature. In absence of robust predictive models, the go-to solution in order to avoid the agglomeration behavior of AIs has been to use minimal agitation which is not only suboptimal but also significantly increases the drying times.