OPTIMIZING ENANTIOMER SEPARATION PROCESSES: A MATHEMATICAL MODELING APPROACH IN CONTINUOUS FLUIDIZED BEDS

This study centers on the optimization of a purification process aimed at separating enantiomers, specifically focusing on the extraction of asparagine monohydrate from its racemic mixture. The ability to efficiently separate enantiomers is critical in various industries, particularly pharmaceuticals, where the purity of compounds can significantly influence the effectiveness and safety of drugs. A validated mathematical model based on population balance equations serves as the foundation for this research. By employing numerical optimization techniques, this work identifies a set of operational parameters that enhance product purity while maintaining contamination levels below specified limits. The results presented in this paper were obtained as part of the author's work in the group of Professor Andreas Seidel-Morgenstern at the Max Planck Institute for Dynamics of Complex Technical Systems, in cooperation with the Technical University of Applied Sciences in Bingen. Keywords: Continuous Crystallization, Population Balance Equations, Mathematical Optimization, Genetic Algorithms, Parallel Computing.