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Timothy M. Swager. Schroeder, Vera,Ph.D.Massachusetts Institute of Technology. Massachusetts Institute of Technology. Department of Chemistry. Massachusetts Institute of Technology. Department of Chemistry 2019-11-12T17:39:23Z 2019-11-12T17:39:23Z 2019 2019 https://hdl.handle.net/1721.1/122856 1126332892 Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemistry, 2019 Cataloged from PDF version of thesis. Includes bibliographical references (pages 167-183). In this thesis, we introduce approaches to carbon nanotube-based sensing for applications in environmental monitoring, disease diagnostics, and food analysis: In Chapter 1, we introduce carbon nanotube-based sensing. We describe parameters that give rise to the sensing capabilities of CNT-based sensors and discuss important performance parameters of carbon nanotube sensors. In Chapter 2, we demonstrate voltage-activated sensing of carbon monoxide using a sensor comprising iron porphyrin and functionalized single walled carbon nanotubes (F-SWCNTs). Modulation of the gate voltage offers a predicted extra dimension for sensing. Specifically, the sensors show significant increase in sensitivity toward CO when negative gate voltage is applied. In Chapter 3, we describe the design of a sensor for the highly selective detection of acrylates using conditions for the aerobic oxidative Heck reaction. The sensors mirror the catalytic processes and selectively respond to electron deficient alkenes by adapting a catalytic reaction system to modulate the doping levels in carbon nanotubes. In Chapter 4, we introduce sensor arrays consisting of imidazolium-based ILs with different substituents and counterions to provide selective responses for known biomarkers of infectious diseases of the lungs. In Chapter 5, we discuss a sensor array comprised of platform 20 functionalized SWCNT sensing channels for the classification of cheese, liquor, and edible oil samples based on their odor. We classify unknown food samples using a k-nearest neighbors model and a random forest model trained on extracted features. This protocol allows us to accurately differentiate between five cheese and five liquor samples (91% and 78% respectively) and only slightly lower (73%) accuracy for five edible oils. by Vera Schroeder. Ph.D. Ph.D. Massachusetts Institute of Technology, Department of Chemistry 183 pages eng Massachusetts Institute of Technology MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 Chemistry. Carbon nanotube-based chemical sensing Thesis application/pdf 2019-11-12T17:39:19Z Publication Doctoral Chem unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="a3b8680a-01f8-402d-8150-fec9a2954bc5"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Carbon nanotube-based chemical sensing</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2019</PublicationDate> <Authors> <Author> <DisplayName>Schroeder, Vera,Ph.D.Massachusetts Institute of Technology.</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Chemistry.</Keyword> <Abstract>In this thesis, we introduce approaches to carbon nanotube-based sensing for applications in environmental monitoring, disease diagnostics, and food analysis: In Chapter 1, we introduce carbon nanotube-based sensing. We describe parameters that give rise to the sensing capabilities of CNT-based sensors and discuss important performance parameters of carbon nanotube sensors. In Chapter 2, we demonstrate voltage-activated sensing of carbon monoxide using a sensor comprising iron porphyrin and functionalized single walled carbon nanotubes (F-SWCNTs). Modulation of the gate voltage offers a predicted extra dimension for sensing. Specifically, the sensors show significant increase in sensitivity toward CO when negative gate voltage is applied. In Chapter 3, we describe the design of a sensor for the highly selective detection of acrylates using conditions for the aerobic oxidative Heck reaction. The sensors mirror the catalytic processes and selectively respond to electron deficient alkenes by adapting a catalytic reaction system to modulate the doping levels in carbon nanotubes. In Chapter 4, we introduce sensor arrays consisting of imidazolium-based ILs with different substituents and counterions to provide selective responses for known biomarkers of infectious diseases of the lungs. In Chapter 5, we discuss a sensor array comprised of platform 20 functionalized SWCNT sensing channels for the classification of cheese, liquor, and edible oil samples based on their odor. We classify unknown food samples using a k-nearest neighbors model and a random forest model trained on extracted features. This protocol allows us to accurately differentiate between five cheese and five liquor samples (91% and 78% respectively) and only slightly lower (73%) accuracy for five edible oils.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>