Computational Fluid Dynamics (CFD) Modeling of a Continuous Crystallizer

Crystallization is one of the most important separation and purification processes in chemical and especially in pharmaceutical industries. Currently most crystallization processes in the industry are based on batch crystallization; however, due to the variation of product quality per batch, efforts are made to move to continuous processes instead. In this respect, micro and meso scale reactors represents a promising technology due to enhanced heat and mass transfer rates, which, translated to particle generation, provide control of size, morphology, and composition. In this study, a meso-scale continuous crystallizer has been characterized and optimized. A stirred tubular continuous-crystallizer has been characterized and optimized in which the crystallization of active pharmaceutical ingredients (APIs) can be performed under controlled conditions. The crystallizer is formed by two tubes, one for nucleation and the other one for growth, in order to separate different phenomena to control better the process and hence the crystal size distribution. The optimized nucleation tube has a length of 35 cm and a diameter of 3 cm with a long axial blade across the tube with the length of 30 cm and 2.5 cm of diameter. The phenomena of mixing helps to achieve homogeneous supersaturation along the tube to prevent growth during the nucleation and enables narrow residence time distribution of the crystals in the tube with the help of gravity to achieve narrower crystal size distribution. Computational fluid dynamics (CFD) is used to optimize the process. CFD is the application of numerical methods to solve systems of partial differential equations related to fluid dynamics. The continuity and the momentum equations are the most commonly applied equations within CFD, and together they can be used to calculate the velocity and pressure distributions in a fluid.