High-Sensitivity Micro-Gas Chromatograph-Photoionization Detector for Trace Vapor Detection
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2021/06/25
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Description:Rapid in situ detection and analysis of trace vapor concentrations at a sub-parts per billion to parts per trillion level remains a challenge for many applications such as indoor air-quality analysis and detection of explosives and narcotics. Micro-gas chromatography (µGC) together with a micro-photoionization detector (µPID) is a prominent method for portable analysis of complex vapor mixtures, but current µPID technology demonstrates poor detection performance compared to benchtop flame ionization detectors (FIDs). This work demonstrates the development of a significantly improved µPID with a sub-picogram detection limit (as low as approx. 0.2 pg) comparable to or exceeding that of a benchtop FID, with a large linear dynamic range (>4 orders of magnitude) and robustness (high stability over 200 h of plasma activation). Based on this µPID, a complete µGC-PID system was built and tested on standard sample chromatograms in a laboratory setting to show the system's analytical capabilities and the detection limit down to sub-parts per trillion concentrations (as low as 0.14 ppt). Practical in-field chromatograms on breath and car exhaust were also generated to demonstrate applicability for in situ experimentation. This work shows that µGC-PID systems can be competitive with traditional GC-FID methods and thus opens a door to rapid trace vapor analysis in the field. [Description provided by NIOSH]
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ISSN:2379-3694
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Volume:6
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Issue:6
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NIOSHTIC Number:nn:20063069
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Citation:ACS Sens 2021 Jun; 6(6):2348-2355
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Contact Point Address:Xudong Fan, Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States
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Email:xsfan@umich.edu
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Federal Fiscal Year:2021
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Performing Organization:University of Michigan at Ann Arbor
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Peer Reviewed:True
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Start Date:20180901
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Source Full Name:ACS Sensors
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End Date:20220831
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Main Document Checksum:urn:sha-512:1fda8c3a15378c39c676b3e4c63e739ff76533f166eecfacfa2d83dcd614436e17251e30d60224ce5b839d98e8bf7c556adae1b4d313d29fd2b31dd729f6f414
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