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doi:10.22028/D291-27502
Titel: | Facile Quantification and Identification Techniques for Reducing Gases over a Wide Concentration Range Using a MOS Sensor in Temperature-Cycled Operation |
VerfasserIn: | Schultealbert, Caroline Baur, Tobias Schütze, Andreas Sauerwald, Tilman |
Sprache: | Englisch |
Titel: | Sensors |
Bandnummer: | 18 |
Heft: | 3 |
Verlag/Plattform: | MDPI |
Erscheinungsjahr: | 2018 |
DDC-Sachgruppe: | 600 Technik |
Dokumenttyp: | Journalartikel / Zeitschriftenartikel |
Abstract: | Dedicated methods for quantification and identification of reducing gases based on model-based temperature-cycled operation (TCO) using a single commercial MOS gas sensor are presented. During high temperature phases the sensor surface is highly oxidized, yielding a significant sensitivity increase after switching to lower temperatures (differential surface reduction, DSR). For low concentrations, the slope of the logarithmic conductance during this low-temperature phase is evaluated and can directly be used for quantification. For higher concentrations, the time constant for reaching a stable conductance during the same low-temperature phase is evaluated. Both signals represent the reaction rate of the reducing gas on the strongly oxidized surface at this low temperature and provide a linear calibration curve, which is exceptional for MOS sensors. By determining these reaction rates on different low-temperature plateaus and applying pattern recognition, the resulting footprint can be used for identification of different gases. All methods are tested over a wide concentration range from 10 ppb to 100 ppm (4 orders of magnitude) for four different reducing gases (CO, H2, ammonia and benzene) using randomized gas exposures. |
DOI der Erstveröffentlichung: | 10.3390/s18030744 |
Link zu diesem Datensatz: | urn:nbn:de:bsz:291--ds-275022 hdl:20.500.11880/28659 http://dx.doi.org/10.22028/D291-27502 |
ISSN: | 1424-8220 |
Datum des Eintrags: | 30-Jan-2020 |
Bezeichnung des in Beziehung stehenden Objekts: | Supplementary Material |
In Beziehung stehendes Objekt: | https://www.mdpi.com/1424-8220/18/3/744/s1 |
Fakultät: | NT - Naturwissenschaftlich- Technische Fakultät |
Fachrichtung: | NT - Systems Engineering |
Professur: | NT - Prof. Dr. Andreas Schütze |
Sammlung: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
Dateien zu diesem Datensatz:
Datei | Beschreibung | Größe | Format | |
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sensors-18-00744-v2.pdf | 2,25 MB | Adobe PDF | Öffnen/Anzeigen |
Diese Ressource wurde unter folgender Copyright-Bestimmung veröffentlicht: Lizenz von Creative Commons