individual
What campus are you from?
Daytona Beach
Authors' Class Standing
Alyssa Vega, Junior
Lead Presenter's Name
Alyssa Vega
Faculty Mentor Name
Raghavan
Abstract
Lunar regolith poses significant risks to exploration machinery and equipment due to its highly abrasive, fine, angular, and electrostatic nature, as observed during the Apollo missions. A promising approach to mitigate these effects is the use of bio-inspired, or biomimetic, surfaces. These surfaces replicate natural micro and nanoscale textures to achieve functional properties such as reduced adhesion and enhanced durability. This study aims to quantify the correlation between surface morphology, surface energy, and adhesion in engineered biomimetic samples. Additively manufactured samples were investigated using optical profilometry to quantify surface roughness and topography, enabling correlation of morphology with adhesion and wettability models. It is expected that surfaces with hierarchical roughness patterns will exhibit lower surface energy and greater hydrophobicity, similar to naturally self-cleaning surfaces. These findings could guide the development of advanced aerospace materials with improved resistance to contamination and wear under extreme environmental conditions.
Did this research project receive funding support from the Office of Undergraduate Research.
No
Reduction of Lunar Dust Adhesion via Biomimetic Surfaces
Lunar regolith poses significant risks to exploration machinery and equipment due to its highly abrasive, fine, angular, and electrostatic nature, as observed during the Apollo missions. A promising approach to mitigate these effects is the use of bio-inspired, or biomimetic, surfaces. These surfaces replicate natural micro and nanoscale textures to achieve functional properties such as reduced adhesion and enhanced durability. This study aims to quantify the correlation between surface morphology, surface energy, and adhesion in engineered biomimetic samples. Additively manufactured samples were investigated using optical profilometry to quantify surface roughness and topography, enabling correlation of morphology with adhesion and wettability models. It is expected that surfaces with hierarchical roughness patterns will exhibit lower surface energy and greater hydrophobicity, similar to naturally self-cleaning surfaces. These findings could guide the development of advanced aerospace materials with improved resistance to contamination and wear under extreme environmental conditions.