(587a) Optimization of Batch Crystallization-Filtration Processes Using the Discrete Element Method

Batch crystallization is widely used in the chemical, pharmaceutical and related industries to separate crystalline products from solution. Compared to continuous crystallization, batch crystallization offers greater flexibility and is better suited for achieving narrow product crystal size distributions (CSD). The product CSD significantly impacts filterability and downstream processes. In order to properly optimize batch crystallization processes it is necessary to understand the relationship between CSD and cake filterability. However, such estimation is challenging, and studies on optimizing cake filterability in batch crystallization are rare.

Fang et al. [1] proposed an efficient method for estimating cake filterability based on a specified product CSD. Their method combines the Kozeny-Carman equation [2], as modified by Borcier et al. [3] with the discrete element method (DEM) [4]. In their method a crystallizer model is used to predict a product crystal size distribution based on crystallizer properties such as residence time and crystal growth rate. Then the crystal cake structure and porosity are predicted using the discrete element method. Next, the Kozeny-Carman equation, modified by Borcier et al. so that it can be applied to crystal cakes with size dispersity, is used to predict the filter cake resistance. Finally, the filter cake resistance is used to design the filter and the total cost of the combined system can be estimated. The method was further applied to continuous crystallizers with fines dissolution and product classification by Tan et al. [5].

In the present study, this method is applied to evaluate the filterability of crystalline products from a batch crystallizer under various operating conditions with the goal of determining the optimal recipe for batch crystallizer operation. The effect of three important crystallizer operating variables are studied: seed loading, batch time, and cooling trajectory. The results suggest that that cake resistance is relatively insensitive to seed loading and cooling trajectory. The linear cooling trajectory and quadratic cooling trajectory are found to produce crystalline product with a similar CSD. Results further suggest that while seed loading primarily affects the size of large crystals, cake resistance is predominantly determined by the CSD of small crystals, which remains nearly the same for different seed loadings. Among the three operating variables, the most significant factor is batch time. Extending the batch time reduces supersaturation and nucleation rates, leading to larger crystals and improved cake filterability. A parametric analysis was also conducted to study the effect of different nucleation and growth rates on the results.

Keywords: Cake Filterability; Optimization; Batch Crystallizer; Crystallization.

References:

1. Fang, M.-C.; Tan, P. J.; Ward, J. D. Efficient estimation of crystal filterability using the discrete element method and the Kozeny-Carman equation. Powder Technology 2024, 441, 119820
2. Carman, P. C. Fluid flow through granular beds. Trans. Inst. Chem. Eng. London 1937, 15, 150-156
3. Bourcier, D.; Feraud, J. P.; Colson, D.; Mandrick, K.; Ode, D.; Brackx, E.; Puel, E. Influence of particle size and shape properties on cake resistance and compressibility during pressure filtration. Chem. Eng. Sci. 2016, 144, 176-187
4. Zhu, H. P.; Zhou, Z. Y.; Yang, R. Y.; Yu, A. B. Discrete particle simulation of particulate systems: Theoretical developments. Chem. Eng. Sci. 2007, 62 (13), 3378-3396
5. Tan, P. J. F., M. C. ; Lai, Bo-Zun; Ward, J. D. Optimal Design of Continuous Integrated Crystallization-Filtration Processes. Powder Technology 2025, in review.