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This study simulates batch cooling crystallization of L-glutamic acid using computational fluid dynamics (CFD) and population balance equations (PBE). Higher impeller speeds and agitation rates lead to smaller crystal sizes due to increased turbulence and supersaturation.

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Area of Science:

  • Chemical Engineering
  • Crystallization Science
  • Pharmaceutical Manufacturing

Background:

  • Batch cooling crystallization is crucial for pharmaceutical ingredient production.
  • Controlling crystal size distribution (CSD) is vital for product quality and downstream processing.
  • Understanding hydrodynamics and kinetics interplay is key to optimizing crystallization.

Purpose of the Study:

  • To simulate and analyze the batch cooling crystallization of L-glutamic acid.
  • To investigate the impact of hydrodynamics and process kinetics on crystal size distribution.
  • To validate the predictive capability of a coupled CFD-PBE model.

Main Methods:

  • Multiphase computational fluid dynamics (CFD) model coupled with a one-dimensional population balance equation (PBE).
  • Simulation of a 20 L pharmaceutical batch crystallizer for the alpha polymorphic form of L-glutamic acid.
  • Comparison of simulation results with published experimental data.

Main Results:

  • The CFD-PBE model accurately predicts final crystal size distributions.
  • Increased impeller speed and agitation rates result in smaller crystal sizes.
  • Significant spatial and temporal variations in process parameters influence CSD evolution, especially at earlier stages.

Conclusions:

  • The coupled CFD-PBE model provides high-fidelity insights into crystallization processes.
  • Hydrodynamics, particularly turbulence and supersaturation, significantly impact CSD.
  • Accurate crystallization kinetics data are essential for reliable simulation outcomes.