Influence of Flow Characteristics on the Kinetics of Spherical Agglomeration: An Experimental and Computational Analysis

The spherical agglomeration process is gaining increasing interest in the pharmaceutical industry as it has the ability to transform needle-like crystals into dense agglomerates that are spherical in shape. The formed agglomerates have improved micromeritic properties, improving the ease of handling and reducing the number of downstream processing steps. Spherical agglomerates are formed by suspending particles in a solvent and adding an antisolvent to induce crystallisation. An immiscible bridging liquid is then added to the crystal suspension to form spherical agglomerates.
As the success of spherical agglomeration is determined by the composition of the solvent system, this has been the subject of the majority of spherical agglomeration research. However, there is limited consistency in the apparatus used for the various investigations. Spherical agglomeration is a process that occurs in suspension; therefore, the mixing profile will affect the contact between the bridging liquid and particles. In a stirred tank, the impeller conditions are the main factor that influences flow and mixing. This work studied the influence of flow characteristics and mixing on the formation of spherical agglomerates. For this investigation, experiments were performed with different impeller geometries, speeds and clearances. A computational fluid dynamics (CFD) study with corresponding impeller characteristics was also produced.
This work demonstrates that the impeller geometry, clearance, and speed have an enormous influence on the particle size distribution and sphericity of agglomerates formed. The CFD study demonstrates that the impeller clearance influences the flow profile and the mixing between the particles and the bridging liquid. For increased impeller clearances, the circulation loop induced by the impeller covers a greater portion of the liquid height for the pitched blade and propeller impellers. As the flow in the tank greatly influences agglomerate characteristics, it is crucial that the impeller geometry and clearance are accurately included in a population balance model (PBM) for spherical agglomeration.
A PBM has previously been developed by Ahmed et al., 2023 which incorporated the various nucleation mechanisms to predict agglomerate size. Whilst this model did consider impeller diameter and speed, it did not include impeller geometry and clearance. In this work, the PBM by Ahmed et al., 2023 was modified to include different impeller geometries and clearances due to the CFD and experimental study showing that these parameters influence spherical agglomeration. To incorporate impeller geometry, the impeller power number was used as the experimental study observed a clear correlation between power number and agglomerate characteristics. It was found that increased power number produced agglomerates that were more consistent in size and sphericity. The velocity magnitude from the CFD simulations was used in the PBM to include the influence of impeller clearance.
The PBM that was developed as part of this work was experimentally validated using an agglomeration in suspension process in which poly(methylmethacrylate) beads were suspended in water, and a bridging liquid was added. As part of the experimental validation, various process parameters, including impeller geometry, impeller clearance, bridging liquid to solid ratio (BSR) and agglomeration time, were altered. In a comparison of the PBM developed in this work, the PBM by Ahmed et al., 2023 and the experimental data, it was found that the PBM developed in this thesis, predicted a d43 value closer to the experimental results than the model by Ahmed et al., 2023 for 56.4 % of the simulations. This is a minimal improvement to the previous model. The predictions for axial impellers were inaccurate, but this PBM was effective at predicting the d43 for agglomerates produced with a Rushton turbine impeller, which was the best performing impeller experimentally.