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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01d217qs59c
Title: Large-Area Sensing for Smart Microfluidic Devices
Authors: Hennebury, Michaela
Advisors: Sturm, James C.
Department: Electrical Engineering
Certificate Program: Materials Science and Engineering Program
Class Year: 2021
Abstract: Microfluidics has become a field of great interest in biology and medicine since its inception in the mid-twentieth century, but microfluidic technologies remain limited in use by fabrication inconsistencies, complex observation techniques, and inflexible application requirements. For example, the performance of a deterministic lateral displacement (DLD) device for blood cell separation can only be monitored with an inverted microscope setup and cannot be changed post-fabrication to account for different target particle sizes. For these devices to have practical use outside of a laboratory setting, they must become “smart,” possessing the ability to gather data about flow patterns and adjust them accordingly without the need for specialized equipment. Two components are required to meet this objective: fabricated sensors to detect particle flow information and a tuning system that can alter the flow in response. In this project, photosensitive amorphous silicon thin-film transistors (TFTs) will be used to determine particle flow rates in the microfluidic channels and an adjustable pressure gradient technique will allow for tunability. This thesis focuses on the TFT sensors and their fabrication, operation, modeling, and experimental application in a microfluidic particle sensing system. An updated TFT fabrication process is presented along with a characterization of the device behavior, and a TFT circuit model is then developed that captures the device photosensitivity. Finally, these components are synthesized in an experiment design that consolidates the sensing and fluidic aspects of the mission to construct smart microfluidic devices.
URI: http://arks.princeton.edu/ark:/88435/dsp01d217qs59c
Type of Material: Princeton University Senior Theses
Language: en
Appears in Collections:Electrical and Computer Engineering, 1932-2023

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