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Detection of microplastics in water using electrical impedance spectroscopy and support vector machines

Title data

Bifano, Luca ; Meiler, Valentin ; Peter, Ronny ; Fischerauer, Gerhard:
Detection of microplastics in water using electrical impedance spectroscopy and support vector machines.
In: Reindl, Leonhard ; Wöllenstein, Jürgen , Informationstechnische Gesellschaft im VDE (VDE ITG); VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik (VDE GMA); AMA Verband für Sensorik und Messtechnik e. V. (ed.): Sensoren und Messsysteme : Beiträge der 21. ITG/GMA-Fachtagung 10. – 11. Mai 2022 in Nürnberg. - Berlin ; Offenbach : VDI Verlag , 2022 . - pp. 356-359 . - (ITG-Fachbericht ; 303 )
ISBN 978-3-8007-5836-4

Abstract in another language

The detection of microplastics in water currently requires a series of processes (sample collection, purification, and preparation) until a sample can be analyzed in the laboratory. To shorten this process chain, we are investigating whether electrical impedance spectroscopy (EIS) enhanced by a classifier based on support vector machines (SVM) can be applied to the problem of microplastics detection. Results with suspensions of polypropylene (PP) and polyolefin (PO) in deionized water proved promising: The relative permittivities extracted from measured impedances agree with literature data. The subsequent classification of measured impedances by SVM shows that the three classes “no plastic”, “PP”, and “PO” can be distinguished securely and that the microplastics concentration can be estimated quantitatively. We conclude that machine-learning-enhanced EIS (MLEIS) appears to be a promising approach for in-situ microplastics detection and certainly warrants more research activities.

Further data

Item Type: Article in a book
Refereed: No
Institutions of the University: Faculties > Faculty of Engineering Science
Faculties > Faculty of Engineering Science > Chair Measurement and Control Technology
Faculties > Faculty of Engineering Science > Chair Measurement and Control Technology > Chair Measurement and Control Technology - Univ.-Prof. Dr.-Ing. Gerhard Fischerauer
Faculties
Result of work at the UBT: Yes
DDC Subjects: 600 Technology, medicine, applied sciences > 620 Engineering
Date Deposited: 13 May 2022 05:57
Last Modified: 13 May 2022 05:57
URI: https://eref.uni-bayreuth.de/id/eprint/69570