(572f) Numerical and Experimental Investigation of a Lab Scale Wurster Coating Process | AIChE

(572f) Numerical and Experimental Investigation of a Lab Scale Wurster Coating Process


Forgber, T., RCPE
Salar-Behzadi, S., Research Center Pharmaceutical Engineering GmbH
Sarkar, A., Worldwide Research and Development, Pfizer Inc.
Jajcevic, D., RCPE
Khinast, J. G., Research Center Pharmaceutical Engineering
Contreras, L., Worldwide Research and Development, Pfizer Inc., Sandwich, Kent, UK

Numerical and Experimental
Investigation of a Lab Scale Wurster Coating Process

Martina Trogrlic1,
Thomas Forgber1, Sharareh Salar Behzadi1, Johannes
Khinast1,3, Avik Sarkar2, Dalibor Jajcevic1

text-align:center">1 Research Center Pharmaceutical Engineering,
Inffeldgasse 13, 8010 Graz, Austria

text-align:center">2 Worldwide Research and Development, Pfizer Inc.
Groton CT, USA

text-align:center">3 Institute of Process and Particle Engineering,
Inffeldgasse 13/III, 8010, Graz, Austria

is one of the essential processes in the pharmaceutical, chemical, food and
other industries. In the pharmaceutical industry the Wurster coater application
is commonly used because of its wide range of application: e.g. coating,
drying, pelletizing and granulating. The typical path of a particle begins in
the Wurster tube, where the particles get accelerated upwards and enter the
spray zone. After spraying, the particles move into the fountain region, and
subsequently fall into the down bed region where they are fluidized. The liquid
part of the deposited droplets evaporates from the particle surface either in
the fountain or in the down bed region. From the down bed region the particles
eventually get drawn back in the tube again, repeating the cycle.

coating layer is formed by two events: depositing the spray droplets on the
particles in the spray zone, and the evaporation of the liquid part of the deposited
droplets. The formation and quality of the coating film are influenced by the
conditions the particle was exposed to in the process equipment, and the time
it was exposed to those conditions. As [1]
showed in their experimental study, there are large regional differences in the
coater with respect to temperature and relative humidity (RH).  Furthermore
these differences vary with the operating conditions, i.e. batch size, spray
rate and fluidization air flow. However, the data obtained from the experiments
is restricted with respect to spatial resolution, and it is very difficult to
get the picture of the entire coating process relying only on this information. 

the fully coupled  (i.e. mass, energy and momentum) CFD-DEM model we are able
to resolve the hydrodynamics of very large number of particles [2].
With the numerical model, not only can we extract trajectories, residence and
cycle times in specific zones, but also individual particle temperatures,
environment conditions and the rate of evaporation. 

this work we consider four different cases, where the fluidization air rate and
the inlet temperature are varied. We validate our numerical model against the
experimental data, and investigate the influence of the varied inlet parameters
on the spray deposition and evaporation rate. We attempt to identify zones with
specific environment conditions (i.e. temperature and humidity) and show how
their size varies with the process parameters and investigate the residence
time of particles in those zones.  

investigation is important because the environment conditions in the Wurster
coater have an effect on the formation of the coating layer. This study attempts
to investigate the particle history in the coater, to gain a better
understanding of the Wurster coating process itself.

normal;text-autospace:none">[1]         S. J. Maronga and P. Wnukowski, “The
use of humidity and temperature profiles in optimizing the size of fluidized
bed in a coating process,” Chem. Eng. Process. Process Intensif., vol.
37, no. 5, pp. 423–432, 1998.

normal;text-autospace:none">[2]         D. Jajcevic, E. Siegmann, C. Radeke,
and J. G. Khinast, “Large-scale CFD-DEM simulations of fluidized granular
systems,” Chem. Eng. Sci., vol. 98, pp. 298–310, 2013.