Multiobjective optimization of an unseeded batch cooling crystallizer for shape and size manipulation
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Abstract
The optimization of unseeded batch cooling crystallization systems is studied in a multiobjective framework. The length mean size and target aspect ratio (AR) of final crystals were considered as objectives, which give rise to a set of optimal solutions known as Pareto-optimal solutions. Two model compounds were considered: paracetamol and potassium dyhidrogen phosphate (KDP), nucleation and growth dominated systems, respectively. The optimization of KDP showed a dependence between the optimal profile and the target objectives weights. The optimal profile for paracetamol did not vary from a cubic cooling profile due to the low sensitivity of the AR to temperature changes. Furthermore, the longer batch time has a greater impact on the optimal AR that could be achieved due to the variation in supersaturation dependence. Moreover, it was shown that there is a relation between the classification of crystallization kinetics based on growth and nucleation mechanisms and the set of optimal cooling profiles for shape and size optimization.
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- Purdue University, Department of Chemical Engineering
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Classification Areas
- Control
- Modeling