Product-Property Guided Scale-Up of a Fluidized Bed Spray Granulation Process Using the CFD-DEM Method

In this work, a method to predict the surface structures of particles produced by fluidized bed spray layering granulation using the CFD-DEM method was developed. A simple state-variable/event tracking approach was implemented to capture indirect quantifiers of the progression of structure-forming microprocesses. The state of the droplet at the time of impact on the particle surface, as well as the time required for drying, is correlated to product properties that quantify surface structure morphology such as roughness. A workflow for scale-up of fluidized bed granulation guided by product-property predictors is presented. The approach was tested on a demonstration case from the literature, where a particle core is coated with sodium benzoate solution. The experiment was scaled-up by a factor of eight to pilot-scale using the developed method. Varying the number of nozzles in use in the pilot-scale granulation affected the particle surface roughness due to the differing drying conditions encountered. On this basis, the ability of the tracked-quantity approach to capture the relationship between product properties and geometric feature or process conditions is demonstrated.

Introduction

Fluidized beds consist of a particulate bulk that is vertically permeated by gas that causes the particles to fluidize, inducing mixing and excellent heat and mass transfer. Fluidized bed spray granulation is a process where a solids-containing liquid phase is introduced into such a fluidized bed to facilitate particle growth. Two modes of operations can be distinguished:

Layering granulation, where particles quickly dry and the injected liquid leaves a solid residue that forms a shell or coating, and
agglomeration, where the cohesive forces of the liquid cause the particles to remain in contact, resulting in the formation of larger granules after solidification of the liquid or sintering.

Experimental studies in this area were performed by Hoffmann et al. [1], Rieck et al. [2] and Schmidt et al. [3].

Hoffmann et al. [1] and Rieck et al. [2] studied the deposition of soluble salts (sodium benzoate) on particle cores that are made of either silica glass or alumina (

γ

–

{Al}_{2} O_{3}

). They varied the solution spray rate and fluidization air temperature in batch granulation experiments and analyzed the porosity of the deposited salt layer using micro-computer tomography (

μ

-CT). A linear correlation between the drying potential of the inflowing fluidization air and the resulting layer porosity was identified.

Schmidt et al. [3] performed similar experiments using a suspension of solid fines as a spraying liquid and varied (1) the atomization pressure, (2) the fluidization air temperature and (3) the spray rate.

Diez et al. [4] performed continuous granulation experiments in a pilot-scale fluidized bed spray granulator equipped with a mill-sieve cycle. This allowed for the production of granules whose entire structure was generated using the process conditions in the granulator. They analyzed

the product moisture content,
the area surface roughness as analyzed by confocal microscopy,
the modulus of elasticity using compression testing,
the granule porosity using X-ray micro-computer tomography,
the wetting behavior using the contact angle as given by the sessile drop experiment.

The operating point with respect to gas mass flow rate was kept constant while varying spray rate and air temperature to capture the effect of the drying potential. The overall results fit with the findings of Schmidt et al. and Hoffmann et al.: Granule porosity increases for wetter drying conditions, equating to higher spray rates, lower drying potentials and lower temperatures. As this study considered actual target properties such as compression strength and wetting behavior as well, it is of great interest for this work. All of the relationships between these and the porosity behave as expected—compression strength increases with harsher drying conditions (= high drying potential), wetting behavior improves with wetter drying conditions due to increasing surface roughness/porosity.

Another recent study demonstrating the accuracy of the CFD-DEM method for modeling particulate flows is that of Batista et al. [5] who demonstrated the ability of the method to reproduce the minimum spouting velocity curve of a conical lab-scale spouted bed for Sorghum grains. Of interest with respect to CFD-DEM modeling of agglomeration is the work of Bahramian and Olazar [6] in which they identify cohesion model-normal force model combinations that are able to reproduce agglomerate formation as well as macroscopic process quantifiers such as the pressure drop of a conical lab-scale fluidized bed with titania nanoparticles.

Other studies focus on agglomeration of primary particles into agglomerates—the physics involved there do not apply for layering granulation/coating and are thus not considered here.

First, we will give an overview of the implementation of heat and mass transfer in the CFD-DEM method used for the simulation of spray granulation. The concept of tracked quantities is introduced, as well as the method that is used to correlate the tracked quantities with product properties from the laboratory-scale calibration experiments. The setup for the experiments and the simulations are then outlined and in final content section, and the resulting tracked quantity-product property mapping is presented and applied to the pilot-scale case.

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Material used in the study besides other: Cellets 500 from Ingredientpharm

Kieckhefen, P.; Pietsch-Braune, S.; Heinrich, S. Product-Property Guided Scale-Up of a Fluidized Bed Spray Granulation Process Using the CFD-DEM Method. Processes 2022, 10, 1291. https://doi.org/10.3390/pr10071291

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