Please use this identifier to cite or link to this item: doi:10.22028/D291-37679
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Title: Highly sensitive benzene detection with MOS gas sensors
Author(s): Leidinger, Martin
Baur, Tobias
Sauerwald, Tilman
Schütze, Andreas
Reimringer, Wolfhard
Spinelle, Laurent
Gerboles, Michel
Language: English
Title: 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
Pages: 92-97
Publisher/Platform: AMA Service GmbH
Year of Publication: 2017
Place of publication: Wunstorf
Place of the conference: Nürnberg, Germany
Free key words: Indoor air quality
volatile organic compounds
gas sensing
temperature cycled operation
trace gas detection
DDC notations: 670 Manufacturing
Publikation type: Conference Paper
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 of the first publication: 10.5162/sensor2017/A4.3
URL of the first publication: https://www.ama-science.org/proceedings/details/2498
Link to this record: 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
Date of registration: 21-Oct-2022
Faculty: NT - Naturwissenschaftlich- Technische Fakultät
Department: NT - Systems Engineering
Professorship: NT - Prof. Dr. Andreas Schütze
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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