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Chew BS, Trinh NN, Koch DT, Borras E, Levasseur MK, Simms LA, McCartney MM, Gibson P, Kenyon NJ, Davis CE. Data-Driven Approach to Modeling Microfabricated Chemical Sensor Manufacturing. Anal Chem 2024; 96:364-372. [PMID: 38156894 PMCID: PMC11015434 DOI: 10.1021/acs.analchem.3c04394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Abstract
We have developed a statistical model-based approach to the quality analysis (QA) and quality control (QC) of a gas micro pre-concentrator chip (μPC) performance when manufactured at scale for chemical and biochemical analysis of volatile organic compounds (VOCs). To test the proposed model, a medium-sized university-led production batch of 30 wafers of chips were subjected to rigorous chemical performance testing. We quantitatively report the outcomes of each manufacturing process step leading to the final functional chemical sensor chip. We implemented a principal component analysis (PCA) model to score individual chip chemical performance, and we observed that the first two principal components represent 74.28% of chemical testing variance with 111 of 118 viable chips falling into the 95% confidence interval. Chemical performance scores and chip manufacturing data were analyzed using a multivariate regression model to determine the most influential manufacturing parameters and steps. In our analysis, we find the amount of sorbent mass present in the chip (variable importance score = 2.6) and heater and the RTD resistance values (variable importance score = 1.1) to be the manufacturing parameters with the greatest impact on chemical performance. Other non-obvious latent manufacturing parameters also had quantified influence. Statistical distributions for each manufacturing step will allow future large-scale production runs to be statistically sampled during production to perform QA/QC in a real-time environment. We report this study as the first data-driven, model-based production of a microfabricated chemical sensor.
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Affiliation(s)
- Bradley S. Chew
- Department of Mechanical and Aerospace Engineering, One Shields Avenue, University of California Davis, Davis, CA 95616
- UC Davis Lung Center, One Shields Avenue, University of California Davis, Davis, CA 95616
| | - Nhi N. Trinh
- Department of Biomedical Engineering, One Shields Avenue, University of California Davis, Davis, CA 95616
- UC Davis Lung Center, One Shields Avenue, University of California Davis, Davis, CA 95616
| | - Dylan T. Koch
- Department of Electrical and Computer Engineering, One Shields Avenue, University of California Davis, Davis, CA 95616
- UC Davis Lung Center, One Shields Avenue, University of California Davis, Davis, CA 95616
| | - Eva Borras
- Department of Mechanical and Aerospace Engineering, One Shields Avenue, University of California Davis, Davis, CA 95616
- UC Davis Lung Center, One Shields Avenue, University of California Davis, Davis, CA 95616
| | - Michael K. Levasseur
- Department of Mechanical and Aerospace Engineering, One Shields Avenue, University of California Davis, Davis, CA 95616
- UC Davis Lung Center, One Shields Avenue, University of California Davis, Davis, CA 95616
| | - Leslie A. Simms
- Department of Mechanical and Aerospace Engineering, One Shields Avenue, University of California Davis, Davis, CA 95616
- UC Davis Lung Center, One Shields Avenue, University of California Davis, Davis, CA 95616
| | - Mitchell M. McCartney
- Department of Mechanical and Aerospace Engineering, One Shields Avenue, University of California Davis, Davis, CA 95616
- UC Davis Lung Center, One Shields Avenue, University of California Davis, Davis, CA 95616
- VA Northern California Health Care System, 10535 Hospital Way, Mather, CA 95655
| | - Patrick Gibson
- Department of Mechanical and Aerospace Engineering, One Shields Avenue, University of California Davis, Davis, CA 95616
- UC Davis Lung Center, One Shields Avenue, University of California Davis, Davis, CA 95616
| | - Nicholas J. Kenyon
- UC Davis Lung Center, One Shields Avenue, University of California Davis, Davis, CA 95616
- VA Northern California Health Care System, 10535 Hospital Way, Mather, CA 95655
- Department of Internal Medicine, 4150 V Street, University of California Davis, Sacramento, CA 95817
| | - Cristina E. Davis
- Department of Mechanical and Aerospace Engineering, One Shields Avenue, University of California Davis, Davis, CA 95616
- UC Davis Lung Center, One Shields Avenue, University of California Davis, Davis, CA 95616
- VA Northern California Health Care System, 10535 Hospital Way, Mather, CA 95655
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Jung AE, Davidson CN, Land CJ, Dash AI, Guess BT, Edmonds HS, Pitsch RL, Harshman SW. Impact of thermal desorption tubes on the variability of exhaled breath data. J Breath Res 2023; 18:016008. [PMID: 38096565 DOI: 10.1088/1752-7163/ad15a3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 12/14/2023] [Indexed: 12/23/2023]
Abstract
Due to the overall low abundance of volatile compounds in exhaled breath, it is necessary to preconcentrate the sample prior to traditional thermal desorption (TD) gas chromatography mass spectrometry analysis. While certain aspects of TD tubes, such as volatile storage, have been evaluated, many aspects remain uncharacterized. Two common TD tubes, Tenax TA and Biomonitoring 5TD tubes, were evaluated for background content and flow rate variability. The data illustrate that the Biomonitoring 5TD tubes have the highest number (23) and abundance of background contamination greater than 3x the mean noise when compared to Tenax TA (13) and empty tubes (9). Tentative identifications of the compounds in the background contamination experiment show that greater than 59% (16/27) of the compounds identified have been reported in the breath literature. The data illustrate the TD tube background abundance could account for more than 70% of the chromatographic signal from exhaled breath for these select compounds. Flow rate measurements of 200 Tenax TA and 200 Biomonitoring 5TD tubes show a large range in measured flow rates among the TD tubes (Tenax: 252.9-284.0 ml min-1, 5TD: 220.6-255.1 ml min-1). Finally, TD tubes of each type, Tenax TA and Biomonitoring 5TD, previously established to have high, medium, and low flow rates, show insignificant differences (p> 0.05) among the tubes of different flow rates, using both gas standards and an exhaled breath from a peppermint experiment. Collectively, these results establish overall background compounds attributed to each TD tube type tested. Additionally, while measured flow rate variability is present and plausibly impacts exhaled breath results, the data demonstrate no statistically significant difference was observed between tubes showing high, medium, and low flow rates from two separate sample types.
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Affiliation(s)
- Anne E Jung
- UES Inc., Air Force Research Laboratory, 711th Human Performance Wing/RHBBA, 2510 Fifth Street, Area B, Building 840, Wright- Patterson AFB, OH 45433, United States of America
| | - Christina N Davidson
- Air Force Research Laboratory, 711th Human Performance Wing/RHBBA, 2510 Fifth Street, Area B, Building 840, Wright- Patterson AFB, OH 45433, United States of America
| | - Christopher J Land
- Air Force Research Laboratory, 711th Human Performance Wing/RHBBA, 2510 Fifth Street, Area B, Building 840, Wright- Patterson AFB, OH 45433, United States of America
| | - Aubrianne I Dash
- Air Force Research Laboratory, 711th Human Performance Wing/RHBBA, 2510 Fifth Street, Area B, Building 840, Wright- Patterson AFB, OH 45433, United States of America
| | - Barlow T Guess
- Air Force Research Laboratory, 711th Human Performance Wing/RHBBA, 2510 Fifth Street, Area B, Building 840, Wright- Patterson AFB, OH 45433, United States of America
| | - Heidi S Edmonds
- United States Air Force Academy, 2304 Cadet Drive, United States Air Force Academy, CO 80840, United States of America
| | - Rhonda L Pitsch
- Air Force Research Laboratory, 711th Human Performance Wing/RHBBA, 2510 Fifth Street, Area B, Building 840, Wright- Patterson AFB, OH 45433, United States of America
| | - Sean W Harshman
- Air Force Research Laboratory, 711th Human Performance Wing/RHBBA, 2510 Fifth Street, Area B, Building 840, Wright- Patterson AFB, OH 45433, United States of America
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McCartney MM, Borras E, Rojas DE, Hicks TL, Hamera KL, Tran NK, Tham T, Juarez MM, Lopez E, Kenyon NJ, Davis CE. Predominant SARS-CoV-2 variant impacts accuracy when screening for infection using exhaled breath vapor. COMMUNICATIONS MEDICINE 2022; 2:158. [PMID: 36482179 PMCID: PMC9731983 DOI: 10.1038/s43856-022-00221-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 11/21/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND New technologies with novel and ambitious approaches are being developed to diagnose or screen for SARS-CoV-2, including breath tests. The US FDA approved the first breath test for COVID-19 under emergency use authorization in April 2022. Most breath-based assays measure volatile metabolites exhaled by persons to identify a host response to infection. We hypothesized that the breathprint of COVID-19 fluctuated after Omicron became the primary variant of transmission over the Delta variant. METHODS We collected breath samples from 142 persons with and without a confirmed COVID-19 infection during the Delta and Omicron waves. Breath samples were analyzed by gas chromatography-mass spectrometry. RESULTS Here we show that based on 63 exhaled compounds, a general COVID-19 model had an accuracy of 0.73 ± 0.06, which improved to 0.82 ± 0.12 when modeling only the Delta wave, and 0.84 ± 0.06 for the Omicron wave. The specificity improved for the Delta and Omicron models (0.79 ± 0.21 and 0.74 ± 0.12, respectively) relative to the general model (0.61 ± 0.13). CONCLUSIONS We report that the volatile signature of COVID-19 in breath differs between the Delta-predominant and Omicron-predominant variant waves, and accuracies improve when samples from these waves are modeled separately rather than as one universal approach. Our findings have important implications for groups developing breath-based assays for COVID-19 and other respiratory pathogens, as the host response to infection may significantly differ depending on variants or subtypes.
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Affiliation(s)
- Mitchell M McCartney
- Mechanical and Aerospace Engineering, UC Davis, Davis, CA, USA
- UC Davis Lung Center, Davis, CA, USA
- VA Northern California Health Care System, Mather, CA, USA
| | - Eva Borras
- Mechanical and Aerospace Engineering, UC Davis, Davis, CA, USA
- UC Davis Lung Center, Davis, CA, USA
| | - Dante E Rojas
- Mechanical and Aerospace Engineering, UC Davis, Davis, CA, USA
- UC Davis Lung Center, Davis, CA, USA
| | - Tristan L Hicks
- Mechanical and Aerospace Engineering, UC Davis, Davis, CA, USA
- UC Davis Lung Center, Davis, CA, USA
| | - Katherine L Hamera
- Mechanical and Aerospace Engineering, UC Davis, Davis, CA, USA
- UC Davis Lung Center, Davis, CA, USA
| | - Nam K Tran
- Department of Pathology and Laboratory Medicine, UC Davis, Sacramento, CA, USA
| | - Tina Tham
- Department of Internal Medicine, UC Davis, Sacramento, CA, USA
| | - Maya M Juarez
- Department of Internal Medicine, UC Davis, Sacramento, CA, USA
| | | | - Nicholas J Kenyon
- UC Davis Lung Center, Davis, CA, USA
- VA Northern California Health Care System, Mather, CA, USA
- Department of Internal Medicine, UC Davis, Sacramento, CA, USA
| | - Cristina E Davis
- Mechanical and Aerospace Engineering, UC Davis, Davis, CA, USA.
- UC Davis Lung Center, Davis, CA, USA.
- VA Northern California Health Care System, Mather, CA, USA.
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Trinh NN, Simms LA, Chew BS, Weinstein A, La Saponara V, McCartney MM, Kenyon NJ, Davis CE. Glass-to-Glass Fusion Bonding Quality and Strength Evaluation with Time, Applied Force, and Heat. MICROMACHINES 2022; 13:1892. [PMID: 36363914 PMCID: PMC9695810 DOI: 10.3390/mi13111892] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 10/29/2022] [Accepted: 10/31/2022] [Indexed: 06/16/2023]
Abstract
A bonding process was developed for glass-to-glass fusion bonding using Borofloat 33 wafers, resulting in high bonding yield and high flexural strength. The Borofloat 33 wafers went through a two-step process with a pre-bond and high-temperature bond in a furnace. The pre-bond process included surface activation bonding using O2 plasma and N2 microwave (MW) radical activation, where the glass wafers were brought into contact in a vacuum environment in an EVG 501 Wafer Bonder. The optimal hold time in the EVG 501 Wafer bonder was investigated and concluded to be a 3 h hold time. The bonding parameters in the furnace were investigated for hold time, applied force, and high bonding temperature. It was concluded that the optimal parameters for glass-to-glass Borofloat 33 wafer bonding were at 550 °C with a hold time of 1 h with 550 N of applied force.
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Affiliation(s)
- Nhi N. Trinh
- Department of Biomedical Engineering, One Shields Avenue, University of California Davis, Davis, CA 95616, USA
| | - Leslie A. Simms
- Department of Mechanical and Aerospace Engineering, One Shields Avenue, University of California Davis, Davis, CA 95616, USA
| | - Bradley S. Chew
- Department of Mechanical and Aerospace Engineering, One Shields Avenue, University of California Davis, Davis, CA 95616, USA
| | - Alexander Weinstein
- Department of Mechanical and Aerospace Engineering, One Shields Avenue, University of California Davis, Davis, CA 95616, USA
| | - Valeria La Saponara
- Department of Mechanical and Aerospace Engineering, One Shields Avenue, University of California Davis, Davis, CA 95616, USA
| | - Mitchell M. McCartney
- Department of Mechanical and Aerospace Engineering, One Shields Avenue, University of California Davis, Davis, CA 95616, USA
- UC Davis Lung Center, One Shields Avenue, University of California Davis, Davis, CA 95616, USA
- VA Northern California Health Care System, 10535 Hospital Way, Mather, CA 95655, USA
| | - Nicholas J. Kenyon
- UC Davis Lung Center, One Shields Avenue, University of California Davis, Davis, CA 95616, USA
- VA Northern California Health Care System, 10535 Hospital Way, Mather, CA 95655, USA
- Department of Internal Medicine, 4150 V Street, University of California Davis, Davis, CA 95616, USA
| | - Cristina E. Davis
- Department of Mechanical and Aerospace Engineering, One Shields Avenue, University of California Davis, Davis, CA 95616, USA
- UC Davis Lung Center, One Shields Avenue, University of California Davis, Davis, CA 95616, USA
- VA Northern California Health Care System, 10535 Hospital Way, Mather, CA 95655, USA
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