Capacitive droplet sensing system for a microdialysis neural probe
Licudine, Alyssa
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/109150
Description
Title
Capacitive droplet sensing system for a microdialysis neural probe
Author(s)
Licudine, Alyssa
Contributor(s)
Vlasov, Yurii
Issue Date
2020-12
Keyword(s)
Microfluidics
Microdialysis
Neural probe
Interdigitated electrodes
Capacitive sensing
Relaxation oscillator
Abstract
This thesis presents the construction and design choices behind an on-chip capacitive droplet-counting
and content-sensing system that will enhance temporal and spatial resolution of
neurochemical sensing of a silicon microdialysis neural probe. The parameters of a coplanar
interdigitated capacitor system were optimized to the microfluidic channel design of the probe
through theoretical analysis, simulations via finite element analysis, and testing of the fabricated
designs. The performance of these designs was assessed by the differential capacitance measured
between water and oil droplets; a larger differential allows for more accurate distinction between the
two liquids as they pass through the sensor. The use of a relaxation oscillator circuit as a method
of measurement for sufficient resolution of sub-picofarad differentials, along with techniques for de-embedding
shunt and stray capacitance contributions, are explored. The resulting droplet counting
system achieves 0.01 pF resolution within one second and enables facile, on-line, on-chip droplet
detection, consequently improving temporal, spatial, and chemical resolution when analyzing the
samples with various options for sensing modalities, including capacitance, electrochemistry, and
mass spectrometry.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.