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Systematic model identification and optimization-based active polymorphic control of crystallization processes

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journal contribution
posted on 2018-11-21, 09:27 authored by Elena Simone, Botond Szilagyi, Zoltan NagyZoltan Nagy
Polymorphism is an important issue in industrial crystallization, since polymorphs of the same compound can present very different properties, such as solubility, melting point or density, influencing considerably the manufacturability and bioavailability of the final product. This work proposes a model-based active polymorphic control strategy that allows obtaining large crystals of the stable polymorph at the end of a batch crystallization process, even in the case of erroneous seeding or in situ nucleation of a mixture of both the stable and metastable forms. A novel systematic experimental design was applied to estimate the kinetic parameters of dissolution, growth and secondary nucleation of the stable and metastable polymorphs of the model compound (ortho-aminobenzoic acid, OABA). Such experimental approach allows the determination of the studied kinetics without any correlation between parameters during the estimation, and without the need of off-line measurements of the crystal size distribution during the experiments. The estimated kinetic parameters were used to build a population balance model for the calculation of the optimal temperature profile needed, during a batch cooling crystallization process, for the (i) elimination of the metastable form crystals nucleated in situ or erroneously seeded and the (ii) maximisation of the size of the crystals of the stable polymorph obtained at the end of the batch process.

Funding

Financial support provided by the European Research Council grant no. [280106-CrySys] is acknowledged.

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Chemical Engineering

Published in

Chemical Engineering Science

Volume

174

Pages

374 - 386

Citation

SIMONE, E., SZILAGYI, B. and NAGY, Z.K., 2017. Systematic model identification and optimization-based active polymorphic control of crystallization processes. Chemical Engineering Science, 174, pp.374-386.

Publisher

© Elsevier

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

2017-09-16

Publication date

2017

Notes

This paper was published in the journal Chemical Engineering Science and the definitive published version is available at https://doi.org/10.1016/j.ces.2017.09.034.

ISSN

0009-2509

Language

  • en