The solid–liquid hydrodynamics in a novel tower crystallizer consisting of seven vertically stacked spherical mixed-suspension, mixed-product removal crystallizers is reported. Mixing in spherical geometries remains underexplored. Therefore, computational fluid dynamics (CFD) simulations (Eulerian–Eulerian multiphase approach with Reynolds-Averaged Navier–Stokes closure at steady state) were performed to systematically assess in silico the impact of stirring rate, impeller type, blade geometry and number, dual-impeller configurations, and baffles on the mixing performance. Results demonstrate the best suspension mixing for representative pharmaceutical crystals (100 μm, 20% solids loading) using an axial-flow pitched blade impeller (four blades, 30° blade angle). Adding baffles further improves mixing, achieving homogeneity (relative standard deviation, σ < 0.2). While mixing is often overlooked in lab-scale crystallizers, possibly due to their small volumes (≤100 mL), this study highlights the critical role of mixing as a fundamental parameter for achieving suspension uniformity, which significantly alters the crystallization performance. The developed and generalizable framework provides mechanistic insights into the solid–liquid mixing, offering a data-driven foundation toward the rational design and scale-up of crystallizers. Ultimately, integrating these CFD findings with population balance modeling in future work will contribute to model-predictive crystallizers, bridging the gap from the lab to industrial scale.

Computational Fluid Dynamic Study in a Multistage Small-Scale Tower Crystallizer

Albertazzi J.;Busini V.;Rota R.;
2026-01-01

Abstract

The solid–liquid hydrodynamics in a novel tower crystallizer consisting of seven vertically stacked spherical mixed-suspension, mixed-product removal crystallizers is reported. Mixing in spherical geometries remains underexplored. Therefore, computational fluid dynamics (CFD) simulations (Eulerian–Eulerian multiphase approach with Reynolds-Averaged Navier–Stokes closure at steady state) were performed to systematically assess in silico the impact of stirring rate, impeller type, blade geometry and number, dual-impeller configurations, and baffles on the mixing performance. Results demonstrate the best suspension mixing for representative pharmaceutical crystals (100 μm, 20% solids loading) using an axial-flow pitched blade impeller (four blades, 30° blade angle). Adding baffles further improves mixing, achieving homogeneity (relative standard deviation, σ < 0.2). While mixing is often overlooked in lab-scale crystallizers, possibly due to their small volumes (≤100 mL), this study highlights the critical role of mixing as a fundamental parameter for achieving suspension uniformity, which significantly alters the crystallization performance. The developed and generalizable framework provides mechanistic insights into the solid–liquid mixing, offering a data-driven foundation toward the rational design and scale-up of crystallizers. Ultimately, integrating these CFD findings with population balance modeling in future work will contribute to model-predictive crystallizers, bridging the gap from the lab to industrial scale.
2026
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1307305
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