(335b) Breakage of Elongated Crystals in an Agitated Filter Dryer
AIChE Annual Meeting
2022
2022 Annual Meeting
Particle Technology Forum
Pharmaceutical Powder and Particulate Systems
Tuesday, November 15, 2022 - 12:48pm to 1:06pm
In this study, a shear cell is built in DEM and mimics the stress environment experienced by particles in dryers using moving parallel walls and periodic boundaries. Elongated rigid particles are modeled with clumped spheres and experience stress due to the shear application in the box. The particles interactions are governed by Hertz-Midlin contact model with no cohesion to simulate a dry system. The internal stress of individual particles is calculated using Euler equation of motion and a particle internal stress distribution is obtained for different stress conditions (normal and shear) and particle physical properties. The Youngâs modulus and yield stress of a sample of Beta-Glutamic Acid (β-LGA) crystals are experimentally assessed with a novel 2-point cantilever bending method using Atomic Force Microscopy [4].
The particle internal stress distributions obtained from simulation are coupled with the experimental breakage strength distribution of the β-LGA sample to predict the breakage rate of the particles within the bed during the shearing phase. This breakage rate is shown to increase exponentially with both the normal stress acting on the shear layer and the particle elongation.
To predict the evolution of the shape and size distribution of dry particle in an agitated filter dryer estimates of normal stress in a dryer were used, along with the estimated breakage rates, in a simple population balance model. The results are compared to size and shape measurements from lab-scale agitated drying experiments on the studied sample of β-LGA crystals and show that the model captures the trends seen experimentally. The use of these approaches gives key insights on the causes of particle breakage and through their generalisation in the pharmaceutical industry they are expected to allow the optimisation of product quality during scale-up, while reducing the actual application of resource-consuming try-and-see methods.
[1] M. Boton et al., Physical Review E 87 (2013) 032206.
[2] Y. Guo et al., Physics of Fluids 25 (2013) 063304.
[3] B. Remy et al., AIChE Journal 61 (2015) 407-418.
[4] F.S. Hallac et al., CrystEngComm 21 (2019) 5738-5748.