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Open AccessArticle

Hybrid Modeling Method for a DEP Based Particle Manipulation

Polytechnique Montreal, 2900 Edouard-Montpetit, Montreal, QC H3T 1J4, Canada
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Sensors 2013, 13(2), 1730-1753; https://doi.org/10.3390/s130201730
Received: 11 November 2012 / Revised: 20 December 2012 / Accepted: 9 January 2013 / Published: 30 January 2013
(This article belongs to the Special Issue BioMEMS and Advanced Analytical Sensors for Biological Applications)
In this paper, a new modeling approach for Dielectrophoresis (DEP) based particle manipulation is presented. The proposed method fulfills missing links in finite element modeling between the multiphysic simulation and the biological behavior. This technique is amongst the first steps to develop a more complex platform covering several types of manipulations such as magnetophoresis and optics. The modeling approach is based on a hybrid interface using both ANSYS and MATLAB to link the propagation of the electrical field in the micro-channel to the particle motion. ANSYS is used to simulate the electrical propagation while MATLAB interprets the results to calculate cell displacement and send the new information to ANSYS for another turn. The beta version of the proposed technique takes into account particle shape, weight and its electrical properties. First obtained results are coherent with experimental results. View Full-Text
Keywords: hybrid modeling; microfluidics; BioMEMS; particle manipulation hybrid modeling; microfluidics; BioMEMS; particle manipulation
MDPI and ACS Style

Miled, M.A.; Gagne, A.; Sawan, M. Hybrid Modeling Method for a DEP Based Particle Manipulation. Sensors 2013, 13, 1730-1753. https://doi.org/10.3390/s130201730

AMA Style

Miled MA, Gagne A, Sawan M. Hybrid Modeling Method for a DEP Based Particle Manipulation. Sensors. 2013; 13(2):1730-1753. https://doi.org/10.3390/s130201730

Chicago/Turabian Style

Miled, Mohamed A.; Gagne, Antoine; Sawan, Mohamad. 2013. "Hybrid Modeling Method for a DEP Based Particle Manipulation" Sensors 13, no. 2: 1730-1753. https://doi.org/10.3390/s130201730

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