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Updated: Oct 6, 2025

Generation and Control of Electrohydrodynamic Flows in Aqueous Electrolyte Solutions
Published on: September 7, 2018
A velocity program using the Kanade-Lucas-Tomasi feature-tracking algorithm with demonstration for pressure and
Jasen Devasagayam1,2, Rick Bosma1,2, Christopher M Collier1
1School of Engineering, University of British Columbia, Kelowna, BC, Canada.
Abstract:
Investigating microfluidic flow profiles is of interest in the microfluidics field for the determination of various characteristics of a lab-on-a-chip system. Microparticle tracking velocimetry uses computational methods upon recording video footage of microfluidic flow to ultimately visualize motion within a microfluidic system across all frames of a video. Current methods are computationally expensive or require extensive instrumentation. A computational method suited to microparticle tracking applications is the robust Kanade-Lucas-Tomasi (KLT) feature-tracking algorithm. This work explores a microparticle tracking velocimetry program using the KLT feature-tracking algorithm. The developed program is demonstrated using pressure-driven and EOF and compared with the respective mathematical fluid flow models. An electrostatics analysis of EOF conditions is performed in the development of the mathematical using a Poisson's Equation solver. This analysis is used to quantify the zeta potential of the electroosmotic system. Overall, the KLT feature-tracking algorithm presented in this work proved to be highly reliable and computationally efficient for investigations of pressure-driven and EOF in a microfluidic system.
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