Electrical impedance spectroscopy

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Artikelnummer
03654_2021_08_05

Machine learning in crystallization processes

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The electrical impedance measurement of a suspension is a valid method to monitor crystallization processes. Since it allows measurement of conductivity and permittivity it enables the characterization of non-conductive suspensions. The results obtained show that the concentration of an organic compound of interest can be determined by evaluating its electrical and thermal properties. As the analytical analysis of independent process parameters is a challenging task, a machine learning approach is investigated to extract essential parameter dependency for automated process control purposes.

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Autoren

Nicholas Karsch, Stephan Westerdick, Thomas Musch, Ruhr University Bochum; Lars Kaufhold, Marc Dittmann, Merck; Malte Mallach, Jan Tebrügge, Jan Förster, Michael Vogt, Krohne

Erscheinungsdatum 20.08.2021
Format PDF
Verlag Vulkan-Verlag GmbH
Sprache Deutsch
Seitenzahl 9
Titel Electrical impedance spectroscopy
Untertitel

Machine learning in crystallization processes

Beschreibung

The electrical impedance measurement of a suspension is a valid method to monitor crystallization processes. Since it allows measurement of conductivity and permittivity it enables the characterization of non-conductive suspensions. The results obtained show that the concentration of an organic compound of interest can be determined by evaluating its electrical and thermal properties. As the analytical analysis of independent process parameters is a challenging task, a machine learning approach is investigated to extract essential parameter dependency for automated process control purposes.

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