Date of Award
1-1-2022
Degree Type
Dissertation
Degree Name
Doctor of Philosophy in Chemical Engineering
Specialization
Materials Science
Department
Chemical Engineering
First Advisor
Otto J. Gregory
Abstract
Like solids and liquids, vapor has long been established as a sensing medium capable of delivering vital information to a number of critical applications such as public safety, security, and healthcare. Yet despite the potential, the implementation of vapor sensing in real-world application is relatively limited. Today canines are still considered state-of-the-art for the identification and location of explosives in airports and other densely populated venues. In healthcare, the standard of diagnosis includes a number of invasive and stagnated technologies that fail to deliver actionable heath information when patients need it most. The next generation of vapor sensing has the potential to revolutionize these application areas and provide a better alternative to the current standards. The focus of this dissertation was to research and develop the next paradigm in sensing, single molecule detection in the vapor phase. Currently, no vapor phase system exists that is capable of demonstrating single molecule detection in real-time. Described within is the evolution of a class of thermodynamic vapor sensors designed to achieve first- of-its-kind sensitivity, selectivity, and responsiveness. Additional validation towards real- time, continuous detection of explosives and explosive-precursors for public safety and security as well as rapid, non-invasive disease diagnosis and monitoring was also investigated. Ultimately, single molecule detection in the vapor phase was confirmed via the differentiation and identification of explosives and proteins. This thermodynamic vapor sensor is ground-breaking technology capable of achieving detection beyond that of any analytical tool culminating in true single molecule detection in the vapor phase.
Recommended Citation
Ricci, Peter Paul, "The Next Paradigm in Vapor Sensing: Single Molecule Detection" (2022). Open Access Dissertations. Paper 1481.
https://digitalcommons.uri.edu/oa_diss/1481
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