{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/121544"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/121544","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"A Fast-Response Odor Chromatographic Sniffer (FOX)","abstract":"This thesis in microscale gas chromatography (μGC) creates a paradigm shift in rapidly analyzing chemicals in the environment or analytes. We are looking for unexpected chemical changes that have been added purposefully or unintentionally. The work examines various aspects of μGC technology, including the optimization of ionic liquid stationary phase coatings for microfabricated columns, achieving up to 8300 theoretical plates per meter for naphthalene using 1-butylpyridinum bis(trifluoromethylsulfonyl)imide [BPY][NTf2] at 240°C. The development of portable systems for fuel adulteration detection is demonstrated, capable of discriminating 5% kerosene adulterated diesel fuel with four seconds of chromatogram analysis. The research also presents a novel parallel column configuration using three ionic liquid-coated semi-packed columns, each 1 m long and 240 μm deep, for complex gas analysis of up to 46 compounds. Key innovations discussed include optimized coating procedure of GC separation columns and implementation of GC based miniaturized electronic nose with the integration of machine learning algorithms. An evaluation of a prototype modular electric and fluidic μGC was evaluated and validated for benzene toluene, ethylbenzene, and xylene (BTEX). This research highlights the versatility of μGCs in applications ranging from environmental monitoring to quality control in the fuel industry, showcasing their potential as powerful tools for on-site chemical analysis with improved selectivity, resolution, and portability.","abstract_html":"This thesis in microscale gas chromatography (μGC) creates a paradigm shift in rapidly analyzing chemicals in the environment or analytes. We are looking for unexpected chemical changes that have been added purposefully or unintentionally. The work examines various aspects of μGC technology, including the optimization of ionic liquid stationary phase coatings for microfabricated columns, achieving up to 8300 theoretical plates per meter for naphthalene using 1-butylpyridinum bis(trifluoromethylsulfonyl)imide [BPY][NTf2] at 240°C. The development of portable systems for fuel adulteration detection is demonstrated, capable of discriminating 5% kerosene adulterated diesel fuel with four seconds of chromatogram analysis. The research also presents a novel parallel column configuration using three ionic liquid-coated semi-packed columns, each 1 m long and 240 μm deep, for complex gas analysis of up to 46 compounds. Key innovations discussed include optimized coating procedure of GC separation columns and implementation of GC based miniaturized electronic nose with the integration of machine learning algorithms. An evaluation of a prototype modular electric and fluidic μGC was evaluated and validated for benzene toluene, ethylbenzene, and xylene (BTEX). This research highlights the versatility of μGCs in applications ranging from environmental monitoring to quality control in the fuel industry, showcasing their potential as powerful tools for on-site chemical analysis with improved selectivity, resolution, and portability.","abstract_has_math":false,"creators":["Chowdhury, Mustahsin"],"institution":"Virginia Tech","degree_name":"Doctor of Philosophy","degree_level":"doctoral","degree_discipline":"Electrical Engineering","degree_department":"Electrical Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Agah, Masoud"],"committee_members":["Zhang, Yuhao","Xia, Kang","Lind, Elena Spinei","Centeno, Virgilio A."],"year":2024,"date_issued":"2024-11-04","date_published":"2024-11-04","updated_at":"2026-07-22T22:20:25Z","subjects":["Micro gas chromatography","Separation column coating optimization","Virtual sensor array","System integration","Rapid prototyping"],"languages":["en"],"rights":["Creative Commons Attribution 4.0 International"],"rights_urls":["http://creativecommons.org/licenses/by/4.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:41635"],"render_values":[{"text":"vt_gsexam:41635","href":null,"code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/10919/121544","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Agah, Masoud"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Zhang, Yuhao","Xia, Kang","Lind, Elena Spinei","Centeno, Virgilio A."]},{"key":"dc:contributor.department","label":"Department","values":["Electrical Engineering"]},{"key":"dc:creator","label":"Author","values":["Chowdhury, Mustahsin"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2024-11-05T09:00:11Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2024-11-05T09:00:11Z"]},{"key":"dc:date.issued","label":"Date","values":["2024-11-04"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Micro gas chromatography","Separation column coating optimization","Virtual sensor array","System integration","Rapid prototyping"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Creative Commons Attribution 4.0 International"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://creativecommons.org/licenses/by/4.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:41635"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10919/121544"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This thesis in microscale gas chromatography (μGC) creates a paradigm shift in rapidly analyzing chemicals in the environment or analytes. We are looking for unexpected chemical changes that have been added purposefully or unintentionally. The work examines various aspects of μGC technology, including the optimization of ionic liquid stationary phase coatings for microfabricated columns, achieving up to 8300 theoretical plates per meter for naphthalene using 1-butylpyridinum bis(trifluoromethylsulfonyl)imide [BPY][NTf2] at 240°C. The development of portable systems for fuel adulteration detection is demonstrated, capable of discriminating 5% kerosene adulterated diesel fuel with four seconds of chromatogram analysis. The research also presents a novel parallel column configuration using three ionic liquid-coated semi-packed columns, each 1 m long and 240 μm deep, for complex gas analysis of up to 46 compounds. Key innovations discussed include optimized coating procedure of GC separation columns and implementation of GC based miniaturized electronic nose with the integration of machine learning algorithms. An evaluation of a prototype modular electric and fluidic μGC was evaluated and validated for benzene toluene, ethylbenzene, and xylene (BTEX). This research highlights the versatility of μGCs in applications ranging from environmental monitoring to quality control in the fuel industry, showcasing their potential as powerful tools for on-site chemical analysis with improved selectivity, resolution, and portability."]},{"key":"dc:description.abstractgeneral","label":"General Abstract","values":["This thesis advances the development of miniature chemical analytical systems, specifically gas chromatography, which is the gold standard for detecting volatile organic compounds in the environment. The work encompasses comprehensive improvements to these systems, from optimizing fabrication and coating of separation columns for better chemical separation to developing rapid prototyping methods for both hardware and software components. Through the integration of machine learning and innovative system designs, the thesis demonstrates significant improvements in detection capabilities, including identifying fuel tampering within seconds and monitoring harmful air pollutants at parts-per-billion levels over extended periods. These advances pave the way for making sophisticated chemical analysis accessible outside of traditional laboratories, enabling direct testing at locations where immediate results are crucial for safety and quality control."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Doctor of Philosophy"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:title","label":"Title","values":["A Fast-Response Odor Chromatographic Sniffer (FOX)"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Agah, Masoud"],"dc:contributor.committeemember":["Zhang, Yuhao","Xia, Kang","Lind, Elena Spinei","Centeno, Virgilio A."],"dc:contributor.department":["Electrical Engineering"],"dc:creator":["Chowdhury, Mustahsin"],"dc:date.accessioned":["2024-11-05T09:00:11Z"],"dc:date.available":["2024-11-05T09:00:11Z"],"dc:date.issued":["2024-11-04"],"dc:description.abstract":["This thesis in microscale gas chromatography (μGC) creates a paradigm shift in rapidly analyzing chemicals in the environment or analytes. 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An evaluation of a prototype modular electric and fluidic μGC was evaluated and validated for benzene toluene, ethylbenzene, and xylene (BTEX). This research highlights the versatility of μGCs in applications ranging from environmental monitoring to quality control in the fuel industry, showcasing their potential as powerful tools for on-site chemical analysis with improved selectivity, resolution, and portability."],"dc:description.abstractgeneral":["This thesis advances the development of miniature chemical analytical systems, specifically gas chromatography, which is the gold standard for detecting volatile organic compounds in the environment. The work encompasses comprehensive improvements to these systems, from optimizing fabrication and coating of separation columns for better chemical separation to developing rapid prototyping methods for both hardware and software components. Through the integration of machine learning and innovative system designs, the thesis demonstrates significant improvements in detection capabilities, including identifying fuel tampering within seconds and monitoring harmful air pollutants at parts-per-billion levels over extended periods. These advances pave the way for making sophisticated chemical analysis accessible outside of traditional laboratories, enabling direct testing at locations where immediate results are crucial for safety and quality control."],"dc:description.degree":["Doctor of Philosophy"],"dc:format.medium":["ETD"],"dc:identifier.other":["vt_gsexam:41635"],"dc:identifier.uri":["https://hdl.handle.net/10919/121544"],"dc:language.iso":["en"],"dc:publisher":["Virginia Tech"],"dc:rights":["Creative Commons Attribution 4.0 International"],"dc:rights.uri":["http://creativecommons.org/licenses/by/4.0/"],"dc:subject":["Micro gas chromatography","Separation column coating optimization","Virtual sensor array","System integration","Rapid prototyping"],"dc:title":["A Fast-Response Odor Chromatographic Sniffer (FOX)"],"dc:type":["Dissertation"],"thesis:degree_discipline":["Electrical Engineering"],"thesis:degree_level":["doctoral"],"thesis:degree_name":["Doctor of Philosophy"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:20:25Z"}