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Titel: Highly sensitive benzene detection with MOS gas sensors
VerfasserIn: Leidinger, Martin
Baur, Tobias
Sauerwald, Tilman
Schütze, Andreas
Reimringer, Wolfhard
Spinelle, Laurent
Gerboles, Michel
Sprache: Englisch
Titel: AMA conferences 2017 : Nuremberg Exhibition Centre, Germany, 30.5.-1.6.2017 : proceedings : SENSOR 2017, 18th International Conference on Sensors and Measurement Technology/IRS2 2017, 15th International Conference on Infrared Sensors & Systems
Seiten: 92-97
Verlag/Plattform: AMA Service GmbH
Erscheinungsjahr: 2017
Erscheinungsort: Wunstorf
Konferenzort: Nürnberg, Germany
Freie Schlagwörter: Indoor air quality
volatile organic compounds
gas sensing
temperature cycled operation
trace gas detection
DDC-Sachgruppe: 670 Industrielle und handwerkliche Fertigung
Dokumenttyp: Konferenzbeitrag (in einem Konferenzband / InProceedings erschienener Beitrag)
Abstract: For detection of benzene, a gas sensor system using metal oxide semiconductor (MOS) gas sensors is presented and measurement results for a concentration range up to 10 ppb are presented. The system is equipped with three gas sensors and advanced temperature control and read-out electronics for using the sensors in temperature cycled operation (TCO). The performance of the system regarding benzene quantification has been tested in two different gas test setups at two different labs. Using features extracted from the TCO signals, regression models for the quantification of benzene have been calculated for both test runs. In the tests with the first setup, benzene was applied in defined gas profiles in a continuous gas flow with variation of humidity and various interferents. In this setup, a quantification accuracy of less than ± 0.5 ppb has been achieved at nearly constant background incl. ubiquitous interferent gases; with more complex background variations the quantification error increased to approx. ± 2 ppb. The second gas mixing system is based on recirculation of the carrier gas stream and closed loop control for the benzene concentration based on continuously available reference data for the benzene concentration. In this system, a similar accuracy was again achieved for low background contaminations and constant humidity; the benzene level could be quantified with an error of less than 0.5 ppb.
DOI der Erstveröffentlichung: 10.5162/sensor2017/A4.3
URL der Erstveröffentlichung: https://www.ama-science.org/proceedings/details/2498
Link zu diesem Datensatz: urn:nbn:de:bsz:291--ds-376793
hdl:20.500.11880/34089
http://dx.doi.org/10.22028/D291-37679
ISBN: 978-3-9816876-4-4
Datum des Eintrags: 21-Okt-2022
Fakultät: NT - Naturwissenschaftlich- Technische Fakultät
Fachrichtung: NT - Systems Engineering
Professur: NT - Prof. Dr. Andreas Schütze
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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