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Quantifying Particle Motion Under Force Fields in Microfluidic Systems by Image Tracking Methods

Chen, Andrew
Format
Thesis/Dissertation; Online
Author
Chen, Andrew
Advisor
Swami, Nathan
Abstract
Micro-engineered devices for selective cell separation and analysis are of great importance in biomedical research. Dielectrophoresis (DEP), which enables the frequency-selective translation of particles under spatially non-uniform fields based on their distinctive impedance characteristics, is an effective technique for cell sorting and quantification. It has been used for selective manipulation and identification of microorganisms and cells. Particle translation towards or away from localized regions of high field occurs, respectively, under positive DEP (p-DEP) or negative DEP (n-DEP). In this manner, based on differences in polarization between different cells and the surrounding medium, non-destructive and label-free cell separations can be accomplished. This work is focused on using image analysis methods to quantify the translation of particles under spatially non-uniform fields to determine the DEP force spectrum versus frequency, within two different device designs. The first is based on a constricted microfluidic channel, wherein image tracking is used to directly identify particle translation, to quantify the DEP frequency spectra with single-particle sensitivity. The second is a set of microfluidic wells with ring electrodes, wherein the focus is on rapid quantification of DEP spectra, based on spatio-temporal analysis of light scattering due to particle translation. These techniques are applied to three kinds of bioparticles, Cryptosporidium parvum, Clostridium difficile and Human Embryonic Kidney (HEK) cell as subjects to validate a model for particles of different sizes and shapes. These methods could serve as useful tools to study cellular subpopulations, which is of fundamental importance in biomedical sciences.
Language
English
Published
University of Virginia, Department of Electrical Engineering, MS (Master of Science), 2016
Published Date
2016-08-01
Degree
MS (Master of Science)
Rights
CC-BY (permitting free use with proper attribution)
Collection
Libra ETD Repository

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