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Mao J, Atwa Y, Wu Z, McNeill D, Shakeel H. Identification of Different Classes of VOCs Based on Optical Emission Spectra Using a Dielectric Barrier Helium Plasma Coupled with a Mini Spectrometer. ACS MEASUREMENT SCIENCE AU 2024; 4:201-212. [PMID: 38645576 PMCID: PMC11027204 DOI: 10.1021/acsmeasuresciau.3c00066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 12/21/2023] [Accepted: 12/21/2023] [Indexed: 04/23/2024]
Abstract
In this study, a micro helium dielectric barrier discharge (μHDBD) plasma device fabricated using 3D printing and molding techniques was coupled with a mini spectrometer to detect and identify different classes of volatile organic compounds (VOCs) using optical emission spectrometry (OES). We tested 11 VOCs belonging to three different classes (straight-chain alkanes, aromatics, and polar organic compounds). Our results clearly demonstrate that the optical emission spectra of different classes of VOCs show clear differences, and therefore, can be used for identification. Additionally, the emission spectra of VOCs with a similar structure (such as n-pentane, n-hexane, n-heptane, n-octane, and n-nonane) have similar optical emission spectrum shape. Acetone and ethanol also have similar emission wavelengths, but they show different line intensities for the same concentrations. We also found that the side-chain group of aromatics will also affect the emission spectra even though they have a similar structure (all have a benzene ring). Moreover, our μHDBD-OES system can also identify multiple compounds in VOC mixtures. Our work also demonstrates the possibility of identifying different classes of VOCs by the OES shape.
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Affiliation(s)
- Jingqin Mao
- School
of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast BT7 1NN, United Kingdom
| | - Yahya Atwa
- School
of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast BT7 1NN, United Kingdom
| | - Zhenxun Wu
- Queen’s
Business School, Queen’s University
Belfast, Belfast BT7 1NN, United Kingdom
| | - David McNeill
- School
of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast BT7 1NN, United Kingdom
| | - Hamza Shakeel
- School
of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast BT7 1NN, United Kingdom
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Zang W, Huang X, Sharma R, Fan X. 1D-Guided Differential Rescaling of a Contour Plot in Comprehensive 2D Gas Chromatography. Anal Chem 2024; 96:3960-3969. [PMID: 38386846 PMCID: PMC10919281 DOI: 10.1021/acs.analchem.4c00202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 02/07/2024] [Accepted: 02/08/2024] [Indexed: 02/24/2024]
Abstract
A 1D-guided differential rescaling algorithm for a contour plot is developed based on our recently proposed comprehensive two-dimensional gas chromatography (GC × GC) system with a first-dimensional (1D) detector added. Chromatograms obtained from 1D and second-dimensional (2D) detectors are both incorporated during the data processing. As compared to the conventional contour plot methods using only 2D data, our algorithm can significantly improve precision and consistency of GC × GC results in terms of retention times, peak widths, and peak areas or volumes, regardless of modulation time selection, modulation phase shift fluctuations, and modulation duty cycle. The peak identification, quantification, and capacity can therefore be enhanced. Furthermore, the 1D-guided differential rescaling method is shown to better handle the coelution and missing peak issues often encountered in the conventional methods. Finally, the new method exhibits high versatility in 1D and 2D detector selection, which greatly broadens GC × GC utility. Our method can easily be adapted to other two-dimensional chromatography systems that have direct access to 1D chromatograms.
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Affiliation(s)
- Wenzhe Zang
- Department
of Biomedical Engineering, University of
Michigan, Ann Arbor, Michigan 48109, United States
- Center
for Wireless Integrated MicroSensing and Systems (WIMS), University of Michigan, Ann Arbor, Michigan 48109, United States
- Max
Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Xiaheng Huang
- Department
of Biomedical Engineering, University of
Michigan, Ann Arbor, Michigan 48109, United States
- Center
for Wireless Integrated MicroSensing and Systems (WIMS), University of Michigan, Ann Arbor, Michigan 48109, United States
- Max
Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor, Michigan 48109, United States
- Department
of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Ruchi Sharma
- Department
of Biomedical Engineering, University of
Michigan, Ann Arbor, Michigan 48109, United States
- Center
for Wireless Integrated MicroSensing and Systems (WIMS), University of Michigan, Ann Arbor, Michigan 48109, United States
- Max
Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Xudong Fan
- Department
of Biomedical Engineering, University of
Michigan, Ann Arbor, Michigan 48109, United States
- Center
for Wireless Integrated MicroSensing and Systems (WIMS), University of Michigan, Ann Arbor, Michigan 48109, United States
- Max
Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor, Michigan 48109, United States
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Xu Q, Zhao X, Qin Y, Gianchandani YB. Control Software Design for a Multisensing Multicellular Microscale Gas Chromatography System. MICROMACHINES 2023; 15:95. [PMID: 38258214 PMCID: PMC10818470 DOI: 10.3390/mi15010095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 12/12/2023] [Accepted: 12/20/2023] [Indexed: 01/24/2024]
Abstract
Microscale gas chromatography (μGC) systems are miniaturized instruments that typically incorporate one or several microfabricated fluidic elements; such systems are generally well suited for the automated sampling and analysis of gas-phase chemicals. Advanced μGC systems may incorporate more than 15 elements and operate these elements in different coordinated sequences to execute complex operations. In particular, the control software must manage the sampling and analysis operations of the μGC system in a time-sensitive manner; while operating multiple control loops, it must also manage error conditions, data acquisition, and user interactions when necessary. To address these challenges, this work describes the investigation of multithreaded control software and its evaluation with a representative μGC system. The μGC system is based on a progressive cellular architecture that uses multiple μGC cells to efficiently broaden the range of chemical analytes, with each cell incorporating multiple detectors. Implemented in Python language version 3.7.3 and executed by an embedded single-board computer, the control software enables the concurrent control of heaters, pumps, and valves while also gathering data from thermistors, pressure sensors, capacitive detectors, and photoionization detectors. A graphical user interface (UI) that operates on a laptop provides visualization of control parameters in real time. In experimental evaluations, the control software provided successful operation and readout for all the components, including eight sets of thermistors and heaters that form temperature feedback loops, two sets of pressure sensors and tunable gas pumps that form pressure head feedback loops, six capacitive detectors, three photoionization detectors, six valves, and an additional fixed-flow gas pump. A typical run analyzing 18 chemicals is presented. Although the operating system does not guarantee real-time operation, the relative standard deviations of the control loop timings were <0.5%. The control software successfully supported >1000 μGC runs that analyzed various chemical mixtures.
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Affiliation(s)
- Qu Xu
- Center for Wireless Integrated MicroSensing and Systems (WIMS), University of Michigan, Ann Arbor, MI 48109, USA; (Q.X.); (X.Z.)
- Department of Integrative Systems + Design, University of Michigan, Ann Arbor, MI 48109, USA
| | - Xiangyu Zhao
- Center for Wireless Integrated MicroSensing and Systems (WIMS), University of Michigan, Ann Arbor, MI 48109, USA; (Q.X.); (X.Z.)
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA
| | - Yutao Qin
- Center for Wireless Integrated MicroSensing and Systems (WIMS), University of Michigan, Ann Arbor, MI 48109, USA; (Q.X.); (X.Z.)
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA
| | - Yogesh B. Gianchandani
- Center for Wireless Integrated MicroSensing and Systems (WIMS), University of Michigan, Ann Arbor, MI 48109, USA; (Q.X.); (X.Z.)
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA
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Mao J, Liu L, Atwa Y, Hou J, Wu Z, Shakeel H. Colorimetric Signal Readout for the Detection of Volatile Organic Compounds Using a Printable Glass-Based Dielectric Barrier Discharge-Type Helium Plasma Detector. ACS MEASUREMENT SCIENCE AU 2023; 3:287-300. [PMID: 37600462 PMCID: PMC10436375 DOI: 10.1021/acsmeasuresciau.3c00012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 05/18/2023] [Accepted: 05/18/2023] [Indexed: 08/22/2023]
Abstract
In this paper, we report on a printable glass-based manufacturing method and a new proof-of-concept colorimetric signal readout scheme for a dielectric barrier discharge (DBD)-type helium plasma photoionization detector. The sensor consists of a millimeter-sized glass chamber manufactured using a printable glass suspension. Plasma inside the chip is generated using a custom-built power supply (900 V and 83.6 kHz), and the detector uses ∼5 W of power. Our new detection scheme is based on detecting the change in the color of plasma after the introduction of target gases. The change in color is first captured by a smartphone camera as a video output. The recorded video is then processed and converted to an image light intensity vs retention time plot (gas chromatogram) using three standard color space models (red, green, blue (RGB), hue, saturation, lightness (HSL), and hue, saturation, value (HSV)) with RGB performing the best among the three models. We successfully detected three different categories of volatile organic compounds using our new detection scheme and a 30-m-long gas chromatography column: (1) straight-chain alkanes (n-pentane, n-hexane, n-heptane, n-octane, and n-nonane), (2) aromatics (benzene, toluene, and ethylbenzene), and (3) polar compounds (acetone, ethanol, and dichloromethane). The best limit of detection of 10 ng was achieved for benzene at room temperature. Additionally, the device showed excellent performance for different types of sample mixtures consisting of three and five compounds. Our new detector readout method combined with our ability to print complex glass structures provides a new research avenue to analyze complex gas mixtures and their components.
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Affiliation(s)
- Jingqin Mao
- School
of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast BT7 1NN, U.K.
| | - Longze Liu
- School
of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast BT7 1NN, U.K.
| | - Yahya Atwa
- School
of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast BT7 1NN, U.K.
| | - Junming Hou
- State
Key Laboratory of Millimeter Waves, School of Information Science
and Engineering, Southeast University, Nanjing 210096, China
| | - Zhenxun Wu
- Queen’s
Management School, Queen’s University
Belfast, Belfast BT7 1NN, U.K.
| | - Hamza Shakeel
- School
of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast BT7 1NN, U.K.
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Huang X, Sharma R, Sivakumar AD, Yang S, Fan X. Ultrathin Silica Integration for Enhancing Reliability of Microfluidic Photoionization Detectors. Anal Chem 2023; 95:8496-8504. [PMID: 37278057 DOI: 10.1021/acs.analchem.3c00354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Microfluidic photoionization detectors (μPIDs) based on silicon chips can rapidly and sensitively detect volatile compounds. However, the applications of μPID are limited by the manual assembly process using glue, which may outgas and clog the fluidic channel, and by the short lifetime of the vacuum ultraviolet (VUV) lamps (especially, argon lamps). Here, we developed a gold-gold cold welding-based microfabrication process to integrate ultrathin (10 nm) silica into μPID. The silica coating enables direct bonding of the VUV window to silicon under amicable conditions and works as a moisture and plasma exposure barrier for VUV windows that are susceptible to hygroscopicity and solarization. Detailed characterization of the silica coating was conducted, showing that the 10 nm silica coating allows 40-80% VUV transmission from 8.5 to 11.5 eV. It is further shown that the silica-protected μPID maintained 90% of its original sensitivity after 2200 h of exposure to ambient (dew point = 8.0 ± 1.8 °C), compared to 39% without silica. Furthermore, argon plasma inside an argon VUV lamp was identified as the dominant degradation source for the LiF window with color centers formation in UV-vis and VUV transmission spectra. Ultrathin silica was then also demonstrated effective in protecting the LiF from argon plasma exposure. Lastly, thermal annealing was found to bleach the color centers and restore VUV transmission of degraded LiF windows effectively, which will lead to future development of a new type of VUV lamp and the corresponding μPID (and PID in general) that can be mass produced with a high yield, a longer lifetime, and better regenerability.
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Affiliation(s)
- Xiaheng Huang
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan 48109, United States
- Center for Wireless Integrated MicroSensing and Systems (WIMS2), University of Michigan, Ann Arbor, Michigan 48109, United States
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Ruchi Sharma
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States
- Center for Wireless Integrated MicroSensing and Systems (WIMS2), University of Michigan, Ann Arbor, Michigan 48109, United States
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Anjali Devi Sivakumar
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan 48109, United States
- Center for Wireless Integrated MicroSensing and Systems (WIMS2), University of Michigan, Ann Arbor, Michigan 48109, United States
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Shuo Yang
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States
- Center for Wireless Integrated MicroSensing and Systems (WIMS2), University of Michigan, Ann Arbor, Michigan 48109, United States
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Xudong Fan
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States
- Center for Wireless Integrated MicroSensing and Systems (WIMS2), University of Michigan, Ann Arbor, Michigan 48109, United States
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor, Michigan 48109, United States
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Franceschelli L, Ciricugno C, Di Lorenzo M, Romani A, Berardinelli A, Tartagni M, Correale R. Real-time gas mass spectroscopy by multivariate analysis. Sci Rep 2023; 13:6059. [PMID: 37055471 PMCID: PMC10101983 DOI: 10.1038/s41598-023-33188-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 04/08/2023] [Indexed: 04/15/2023] Open
Abstract
Early and significant results for a real-time, column-free miniaturized gas mass spectrometer in detecting target species with partial overlapping spectra are reported. The achievements have been made using both nanoscale holes as a nanofluidic sampling inlet system and a robust statistical technique. Even if the presented physical implementation could be used with gas chromatography columns, the aim of high miniaturization requires investigating its detection performance with no aid. As a study case, in the first experiment, dichloromethane (CH2Cl2) and cyclohexane (C6H12) with concentrations in the 6-93 ppm range in single and compound mixtures were used. The nano-orifice column-free approach acquired raw spectra in 60 s with correlation coefficients of 0.525 and 0.578 to the NIST reference database, respectively. Then, we built a calibration dataset on 320 raw spectra of 10 known different blends of these two compounds using partial least square regression (PLSR) for statistical data inference. The model showed a normalized full-scale root-mean-square deviation (NRMSD) accuracy of [Formula: see text] and [Formula: see text] for each species, respectively, even in combined mixtures. A second experiment was conducted on mixes containing two other gasses, Xylene and Limonene, acting as interferents. Further 256 spectra were acquired on 8 new mixes, from which two models were developed to predict CH2Cl2 and C6H12, obtaining NRMSD values of 6.4% and 13.9%, respectively.
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Affiliation(s)
- Leonardo Franceschelli
- Department of Electrical, Electronic and Information Engineering (DEI), Alma Mater Studiorum University of Bologna (IT), Bologna, Italy.
| | | | | | - Aldo Romani
- Department of Electrical, Electronic and Information Engineering (DEI), Alma Mater Studiorum University of Bologna (IT), Bologna, Italy
| | - Annachiara Berardinelli
- Department of Industrial Engineering, University of Trento (IT), Trento, Italy
- C3A Center Agriculture Food Environment, University of Trento (IT), Trento, Italy
| | - Marco Tartagni
- Department of Electrical, Electronic and Information Engineering (DEI), Alma Mater Studiorum University of Bologna (IT), Bologna, Italy
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