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  4. Multidimensional sorting of microparticles in electrically switchable dielectrophoretic filters
 
Zitierlink DOI
10.26092/elib/2692

Multidimensional sorting of microparticles in electrically switchable dielectrophoretic filters

Veröffentlichungsdatum
2023-10-02
Autoren
Weirauch, Laura  
Betreuer
Thöming, Jorg  
Gutachter
Hussong, Jeanette  
Zusammenfassung
The sorting of nano- and microparticles according to different properties is an industrially highly relevant but partly unsolved problem. This thesis investigates whether dielectrophoretic filtration facilitates the sorting of microparticles based on multiple properties. Dielectrophoresis (DEP) is the movement of polarizable particles in an inhomogeneous electric field. The DEP force can be used to immobilize (trap) particles at field maxima located at the surface of a filter medium. To sort particles based on multiple properties, a selective trapping step and several subsequent selective remobilization steps are combined into a batchwise sorting process. Such a complex sorting process is made possible by the increased selectivity of the filter design. Regular filter structures (meshes) are used with pores several orders of magnitude larger than the target particles, so that the particles are trapped solely by the action of positive dielectrophoresis. Compared to other high-throughput DEP filters with irregular porous filter media, a higher selectivity to positive dielectrophoresis was demonstrated. Polystyrene particles could be sorted according to their size, shape, and surface coating in one pass of a DEP filter. The proposed method is therefore a promising technique to efficiently create highly specific particle systems in the future.
Schlagwörter
Dielectrophoresis

; 

Filtration

; 

Selective separation

; 

Multidimensional

; 

High-throughput

; 

Microparticles

; 

Analytical Chemistry
Institution
Universität Bremen  
Fachbereich
Fachbereich 04: Produktionstechnik, Maschinenbau & Verfahrenstechnik (FB 04)  
Dokumenttyp
Dissertation
Lizenz
https://creativecommons.org/licenses/by/4.0/
Sprache
Englisch
Dateien
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Vorschaubild
Name

Dissertation_Weirauch.pdf

Size

54.76 MB

Format

Adobe PDF

Checksum

(MD5):14d59859b20815a16d9a7a3be225af46

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