A case study on a challenging industrial crystallization is presented.  The crystallization under investigation was prone to oiling-out, which led to agglomeration and crystallization stalling.  A semi-automated crystallizer—designed and built iteratively as the crystallization needs changed—was used to study the crystallization and identify the failure modes.  Turbidity, <i>in situ</i> video microscopy images (Mettler Toledo EasyViewer) and mother liquor information (automated sampler combined with offline HPLC) were collected during crystallization. Turbidity was monitored to detect the agglomeration event caused by oiling-out and was subsequently used as a feedback mechanism to change the temperature profile to reverse oiling-out and resume crystal growth. The automated sampler, coupled with off-line HPLC analysis, provided valuable insight about the behavior of impurities during oiling-out and identified a specific impurity that influenced the formation of the second liquid phase and crystallization rate. The data-rich experimentation allowed for the expedient optimization of crystallization parameters, such as temperature profile, seed loading and cycle time.  The final crystallization was robust, predictable, and capable of self-correction, should a potential failure mode be encountered.

Application of a semi-automated crystallizer to study oiling-out and agglomeration events—A case study in industrial crystallization optimization

ACS Fall 2021

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