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Artificial micro-swimming at low Reynolds number

Year: 2023

Presenter Name: Ruba Alraqibah

Recent advances in microrobots have shown great promise for a wide range of biomedical applications with the potential of enabling new aspects of medicine ranging from targeted drug delivery to minimally invasive surgery. However, locomotion represents a significant challenge for robots at the microscale. Swimming at the microscale is challenging due to differences in the fundamental physics between the microscale and macroscale. At the microscale, fluid dynamics are characterized by a low Reynolds number (Re < 0.1) where motions are dominated by viscous forces rather than the inertial forces that dominate macroscale fluid dynamics. In nature, microorganisms have evolved swimming strategies to achieve locomotion in their low Re environment. Extensive development has focused on artificial biomimetic microswimming techniques such as the corkscrew and flexible oar methods. The flexible oar method is advantageous because of its simple design and actuation scheme - consisting of a flexible appendage whose oscillation produces propulsion. Here we explore the flexible oar approach of micro-swimmer designs at low Reynolds number. The work investigates propulsive characteristics of the micro-swimmer by experimentally evaluating the swimming of novel designs in a centimeter-scale setup in high viscosity oil that replicates the low Re environment. Experimental objectives include altering swimmer geometry to enhance locomotion characteristics, such as enabling reconfiguration in confined spaces and simplified actuation schemes, which could enable promising applications and technologies in healthcare. Ultimately, we anticipate that the development of low Re locomotion techniques for microrobots will have a significant impact in the field of medicine by enabling robots to navigate through highly confined and complex regions of the human body to perform medical tasks that address unmet clinical needs.
University / Institution: University of Utah
Type: Poster
Format: In Person
Presentation #B2
SESSION B (10:45AM-12:15PM)
Area of Research: Engineering
Faculty Mentor: Yong Lin Kong