Applying Crystallization Modeling to Improve the Understanding of a Batch Cooling Process of An Agrochemical Active Ingredient

The current production process of a Syngenta active ingredient isolates the batch by a cooling crystallization process. A major bottleneck of this process is the isolation time of the product after crystallization, which can vary significantly between batches. From observation, the key variable that dictates the isolation time of the product is the width of the particle size distribution of the crystals obtained; the wider the particle size distribution, the slower the filtration time observed. Typically for this product, two distinct environments of fine particles and large single crystals are observed within a single batch. In this work an experimental scale-down study was carried out to replicate the plant process and to assess whether the filtration properties could be improved by modifying the conditions in the crystallizer. Seeding the batch with different quantities of seed with a narrow particle size and modification of the cooling profile where carried out, with limited success in narrowing the particle size distribution significantly. Crystallization modeling using gCRYSTAL was employed to rationalize the experimental observations and to identify the key crystallization phenomena that are dominant in the process. It was observed that the controlling phenomena for this crystallization where the favorable kinetics for crystal growth and also attrition of the crystals, once attaining crystals that had grown to a critical size. Having identified this from the modeling, it was then possible to devise additional experiments to reduce the width of the particle size distribution of this material with the potential to improve plant operations.