Date of Award

Winter 12-2-2021

Level of Access Assigned by Author

Open-Access Thesis

Degree Name

Master of Science (MS)


Biological Engineering


Caitlin Howell

Second Committee Member

Richard Corey

Third Committee Member

Amy Blakeley


The spread of the SARS-CoV-2 virus has underlined the importance of monitoring surface contamination of infectious elements on commonly used surfaces. Current monitoring methods of surfaces are both lengthy and expensive. The work in this project took advantage of the optical phenomenon of structural color to develop a rapid, low-cost, and contactless method of surface contamination detection. To accomplish this, a mass-produced material imprinted with a nanostructured pattern capable of exhibiting this structural color phenomenon was used. Structural color, or the bands of color that appear as different wavelengths of light reflect off a textured surface, can vary as a surface becomes contaminated. The diffraction patterns of this material creating these structural color effects were studied, where manual analytical techniques were developed to show quantitative differences in these effects when surface contamination was present. The developed techniques focused on three main features of interest in the diffraction patterns: light intensity, diffraction pattern length, and color presence. Light intensity was found to be the greatest indicator of surface contamination presence. Yet, with all three techniques, it was possible to detect surface contamination down to at least a volume of 1 x 10 -1 μL/ 64 cm 2 . Manual detection of contamination was supplemented with machine learning technology as a proof-of-concept. Preliminary results showed the machine learning network’s ability in rapid classification of clean and contaminated diffraction patterns, with a 99% success rate. This work lays the foundation for the development of a rapid, low-cost, and contactless method of surface contamination detection that could play a role in preventing the spread of infectious pathogens and other infectious materials.

Available for download on Saturday, December 10, 2022