In this paper we present a detailed antisolvent crystallization model. A population balance approach is adopted to describe the dynamic change of particle size in crystallization processes under the effect of antisolvent addition. The sodium chloride-water-ethanol is used as a model system. Maximum likelihood method is used to identify the nucleation and growth kinetic models for sodium chloride from data derived from controlled experiments. A number of growth and nucleation kinetic models are investigated in the estimation step to identify one with better prediction. The model is then validated under a new ethanol (antisolvent) addition profile showing to be in good agreement. The resulting model is then exploited in model-based optimization to readily develop optimal antisolvent feeding recipes. Two objective functions are used related to the control of particle size. Different feeding profiles are readily determined for different end-product particle size targets. The dynamic optimization results are successfully validated experimentally showing very close agreement. The approach presented here is rapid and repeatable and thus attractive for pharmaceutical and fine chemicals antisolvent crystallization operations aimed at control of particle size.

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