Multiobjective optimization (MOO) of batch cooling crystallization is carried out for the development of optimal operating recipes for unseeded and seeded crystallization processes. Mean size and coefficient of variation (CV) are the two objectives considered for unseeded batch cooling crystallization of paracetamol, whereas mean size, CV, and nucleated mass are considered as objectives for the seeded batch cooling crystallization of potassium nitrate. In this work, along with finding the optimal temperature trajectories, the effect of choice of objectives on the final achievable Pareto front is analyzed using two different objective functions, namely number mean size and surface-weighted mean size. Further, the capability of MOO is also exploited to determine the feasible ranges of combinations of seed properties like initial seed mass and seed mean size for better crystal size distribution (CSD).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.