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          Institute: MPI für Dynamik komplexer technischer Systeme     Collection: Physical and Chemical Foundations of Process Engineering     Display Documents

ID: 241861.1, MPI für Dynamik komplexer technischer Systeme / Physical and Chemical Foundations of Process Engineering
Numerical Analysis of the Preferential Crystallization of Enantiomers in Complex Flows
Authors:Öncül, A. A.; Elsner, M. P.; Thevenin, D.; Seidel-Morgenstern, A.
Publisher:Martin-Luther-Universität Halle-Wittenberg
Place of Publication:Halle/Saale, Germany
Date of Publication (YYYY-MM-DD):2005
Title of Proceedings:BIWIC 2005 : 12th International Workshop on Industrial Crystallization
Start Page:165
End Page:172
Physical Description:354
Name of Conference/Meeting:BIWIC 2005 : 12th International Workshop on Industrial Crystallization
Place of Conference/Meeting:Halle (Saale), Germany
(Start) Date of Conference/Meeting
End Date of Conference/Meeting 
Review Status:not specified
Audience:Experts Only
Abstract / Description:The preferential crystallization (enantioseparation) represents a suitable alternative to costly separation methods of racemic mixtures, such as chromatographic separation or bio-chemical processes. Therefore, this method becomes increasingly important, especially for the pharmaceutical industry. The preferential crystallization is based on the different crystallization rates of the enantiomers in a supersaturated solution including the seed crystals of the desired enantiomer. In this work, a homogeneous mixture of two threonine (C4H9NO3) enantiomers, L- and D-threonine, dissolved in water has been chosen as a model, which processes in a continuously stirred batch reactor (CSBR). The seed crystals of the desired enantiomer (L-threonine) are injected to this mixture after the appropriate flow field is obtained (Fig. 1), yielding initially an inhomogeneous distribution. A numerical model based on the mass balances has been developed capable to describe the crystallisation of L-threonine, by which not only the concentration changes but also the growth of the seeds and the homogeneous nucleation of new particles can be investigated. This model is coupled with the classical and the extended method of moments (MOM) and a computational fluid dynamics (CFD) code (Fluent® 6.1). With these numerical tools we examine the reconstructed size distribution of the grown seeds and of the nucleated crystals at the end of the process, for different hydrodynamic conditions in the batch crystallizer. The obtained results have been compared and validated with available experimental data and with the exact solution of the population balance equation (PBE) (Fig. 2).
External Publication Status:published
Document Type:Conference-Paper
Communicated by:Andreas Seidel-Morgenstern
Affiliations:MPI für Dynamik komplexer technischer Systeme/Physical and Chemical Foundations of Process Engineering
External Affiliations:Institut für Strömungstechnik und Thermodynamik, Otto-von-Guericke-Universität, Universitätsplatz 2, 39106 Magdeburg, Germany
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