Please use this identifier to cite or link to this item: doi:10.22028/D291-27471
Title: Highly Sensitive and Selective VOC Sensor Systems Based on Semiconductor Gas Sensors: How to?
Author(s): Schütze, Andreas
Baur, Tobias
Leidinger, Martin
Reimringer, Wolfhard
Jung, Ralf
Conrad, Thorsten
Sauerwald, Tilman
Language: English
Title: Environments
Volume: 4
Issue: 1
Publisher/Platform: MDPI
Year of Publication: 2017
DDC notations: 620 Engineering and machine engineering
Publikation type: Journal Article
Abstract: Monitoring of volatile organic compounds (VOCs) is of increasing importance in many application fields such as environmental monitoring, indoor air quality, industrial safety, fire detection, and health applications. The challenges in all of these applications are the wide variety and low concentrations of target molecules combined with the complex matrix containing many inorganic and organic interferents. This paper will give an overview over the application fields and address the requirements, pitfalls, and possible solutions for using low-cost sensor systems for VOC monitoring. The focus lies on highly sensitive metal oxide semiconductor gas sensors, which show very high sensitivity, but normally lack selectivity required for targeting relevant VOC monitoring applications. In addition to providing an overview of methods to increase the selectivity, especially virtual multisensors achieved with dynamic operation, and boost the sensitivity further via novel pro-concentrator concepts, we will also address the requirement for high-performance gas test systems, advanced solutions for operating and read-out electronic, and, finally, a cost-efficient factory and on-site calibration. The various methods will be primarily discussed in the context of requirements for monitoring of indoor air quality, but can equally be applied for environmental monitoring and other fields.
DOI of the first publication: 10.3390/environments4010020
Link to this record: urn:nbn:de:bsz:291--ds-274713
ISSN: 2076-3298
Date of registration: 13-Jan-2020
Faculty: NT - Naturwissenschaftlich- Technische Fakultät
Department: NT - Systems Engineering
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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