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Chemical Discrimination in Turbulent Gas Mixtures with MOX Sensors Validated by Gas Chromatography-Mass Spectrometry
BioCircuits Institute, University of California San Diego, La Jolla, USA .
BioCircuits Institute, University of California San Diego, La Jolla, USA .
Örebro University, School of Science and Technology. AASS Research Center, Örebro University, Örebro, Sweden .ORCID iD: 0000-0003-0195-2102
Biomolecular Measurement Division, Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, USA.
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2014 (English)In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 14, no 10, 19336-19353 p.Article in journal (Refereed) Published
Abstract [en]

Chemical detection systems based on chemo-resistive sensors usually include a gas chamber to control the sample air flow and to minimize turbulence. However, such a kind of experimental setup does not reproduce the gas concentration fluctuations observed in natural environments and destroys the spatio-temporal information contained in gas plumes. Aiming at reproducing more realistic environments, we utilize a wind tunnel with two independent gas sources that get naturally mixed along a turbulent flow. For the first time, chemo-resistive gas sensors are exposed to dynamic gas mixtures generated with several concentration levels at the sources. Moreover, the ground truth of gas concentrations at the sensor location was estimated by means of gas chromatography-mass spectrometry. We used a support vector machine as a tool to show that chemo-resistive transduction can be utilized to reliably identify chemical components in dynamic turbulent mixtures, as long as sufficient gas concentration coverage is used. We show that in open sampling systems, training the classifiers only on high concentrations of gases produces less effective classification and that it is important to calibrate the classification method with data at low gas concentrations to achieve optimal performance.

Place, publisher, year, edition, pages
2014. Vol. 14, no 10, 19336-19353 p.
Keyword [en]
chemical sensors, open sampling systems, gas turbulence, dynamic chemical mixture, inhibitory support vector machine, gas chromatography
National Category
Chemical Sciences
Research subject
Chemistry
Identifiers
URN: urn:nbn:se:oru:diva-39812DOI: 10.3390/s141019336ISI: 000344455700076PubMedID: 25325339Scopus ID: 2-s2.0-84908530056OAI: oai:DiVA.org:oru-39812DiVA: diva2:772159
Note

Funding Agencies:

U.S. Office of Naval Research (ONR) N00014-13-1-0205

California Institute for Telecommunications and Information Technology (CALIT2) 2014CSRO 136

Available from: 2014-12-16 Created: 2014-12-16 Last updated: 2017-12-05Bibliographically approved

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Trincavelli, Marco

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