Gas Chromatography (GC) is one of the most important and widely used tools in analytical chemistry. However, they are bulky, have a longer measurement cycle, and consume a high amount of power. Micro-Gas Chromatography (µGC) is portable and energy-efficient, which allows onsite, real-time biological, forensic, and environmental analyses. This thesis presents a ready-to-deploy implementation of microfabricated gas chromatography (µGC) system capable of separating complex samples. We describe robust, modular, and scalable hardware and software architecture based on Real-Time Operating System (RTOS) and Python Graphical User Interface (GUI) integrated with various microfabricated devices to realize a fully functional µGC system. A sample heater for headspace injection, microfabricated separation column (µSC), a Photoionization Detector (PI-D), and a flow controller unit are integrated with the modular hardware and software to realize a fully functional Vacuum Outlet µGC system. We have designed a novel auto-calibration method for temperature calibration of the microfabricated devices which does not require changing the electronic circuitry or reprogramming the device. The vacuum outlet µGC setup is tested with various mixture of analytes. For these experiments, an average relative standard deviation (RSD) for retention time repeatability of 2.5% is achieved. Data processing techniques for raw chromatograms, including baseline correction and peak detection, are implemented on a microcontroller board and tested extensively as a part of this work. A novel algorithm for multidimensional analysis for the identification of co-eluting compounds in complex samples is implemented with a prediction accuracy of 94%. / Master of Science / Toxic volatile organic compounds (VOCs) such as benzene and toluene found in gasoline and xylene used in ink, rubber, and leather industries are of concern as they are present at elevated concentrations due to their higher vapor pressure. Sufficient exposure to these toxicants, even at lower concentrations like 100 parts-per-billion-volume (ppbv), may cause adverse health effects. Gas Chromatography (GC) has been the established method for assessing the presence and concentration of VOCs in the environment. Traditional GC systems are bulky, power-hungry, expensive, and require expert supervision for analysis. Recent research in microelectromechanical systems (MEMS) has reduced the size of the GC components, also called micro-GC (µGC), while improving the performance. The majority of the research and development of µGC is aimed at advancing microfabricated components such as preconcentrators, separation columns, and gas detectors. However, the integration of these different components is an important topic that requires more investigation. In this thesis, we present a robust and scalable software and hardware architecture that can be used to develop a portable and modular µGC system. The thesis discusses different experiments to calibrate various microfabricated devices, which are then used to build a fully modular µGC system. We show the separation capacity of the modular µGC system by passing complex compounds like kerosene and diesel. As the chromatogram from the µGC system has noise, the second part of the thesis explores data analysis techniques such as baseline correction, peak detection. These data analysis tools are used to filter the noise, detect relevant peaks in the chromatograms, and identify the compounds in a complex sample.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/105044 |
| Date | 22 September 2021 |
| Creators | Manurkar, Shaunak Sudhir |
| Contributors | Electrical and Computer Engineering, Nazhandali, Leyla, Abbott, A. Lynn, Agah, Masoud |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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