Publication Date
Summer 2021
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Biomedical Engineering
Advisor
Anand Ramasubramanian
Keywords
Microfluidics, PIV, RBCs, Simulation, Thrombosis, Venous Valve
Subject Areas
Biomedical engineering; Bioengineering; Cellular biology
Abstract
In this work, particle image velocimetry (PIV) was used for fluid flow visualization in both continuous and segmented-flow microfluidics. Droplet microfluidics is known for its precise and consistent volume dispersion between microliters and picoliters in volume for application ranging from molecular synthesis, drug discover, and diagnostics. But the influence of junction geometry on the process of drop formation has not been investigated. In this study, µ-PIV was used to study the internal flow during the drop formation process in flow-focus microfluidic device with and without constriction. It was found that in case of flow-focus with constriction, the shear force on the drop predominantly initiated break-off, whereas for the device without constriction pressure from the mainstream starts the drop formation but the continuous phase hinders the growth creating recirculating zones. This affected the system’s ability to produce drop of consistent volume. For continuous flow, a device was designed to mimic the venous valve of the circulatory system, where flow is known to greatly influence thrombus formation, but the biophysical mechanisms are not well understood. Solutions with varying hematocrit concentrations were used to understand its effects and the results were compared with both COMSOL simulations. At low Re of 0.6, there were vortexes present that propelled incoming particles and at higher values, flow segregation was observed created a stagnation point. These flow patterns may partly explain the distribution of red blood cells in the venous valves with implications in deep vein thrombosis.
Recommended Citation
Vijayananda, Vignesha, "Examination of Flow Patterns During Droplet Formation and in Venous Valve Mimic Using μ-PIV" (2021). Master's Theses. 5219.
DOI: https://doi.org/10.31979/etd.f95t-8uez
https://scholarworks.sjsu.edu/etd_theses/5219