Morphological modelling and simulation of crystallization processes

The shape of crystals is an important property that has a great impact on their physical behavior. Examples are flowability, dissolution, and growth kinetics. Still, crystals are often described by a single size parameter. One reason is, that today shape information is still hard to measure. Additionally, only few modeling techniques exist that are able to describe the shape of crystals. In this chapter, these issues are addressed by accurately describing crystals with mathematical models, making the full morphological structure of crystals and their agglomerates accessible by stereoscopic and three-dimensional (3D) imaging techniques and using these methods to model crystallization while considering the complex shape of the crystals. In addition, artificial neural networks (ANN) are used to classify whether projections of crystals show single crystals or agglomerates. As a final step, a case study of a model of a mixed suspension mixed product removal (MSMPR) crystallizer and a hydrocyclone are integrated into the software platform Dyssol and used to dynamically simulate a crystallization process with recycling stream.