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doi:10.22028/D291-37679
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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