Please use this identifier to cite or link to this item: doi:10.22028/D291-27799
Title: Graphene Decorated with Iron Oxide Nanoparticles for Highly Sensitive Interaction with Volatile Organic Compounds
Author(s): Rodner, Marius
Puglisi, Donatella
Ekeroth, Sebastian
Helmersson, Ulf
Shtepliuk, Ivan
Yakimova, Rositsa
Skallberg, Andreas
Uvdal, Kajsa
Schütze, Andreas
Eriksson, Jens
Language: English
Title: Sensors
Volume: 19
Issue: 4
Publisher/Platform: MDPI
Year of Publication: 2019
Free key words: epitaxial graphene
metal oxide nanoparticle
gas sensor
volatile organic compounds
benzene
formaldehyde
derivative sensor signal
air quality sensor
DDC notations: 600 Technology
Publikation type: Journal Article
Abstract: Gases, such as nitrogen dioxide, formaldehyde and benzene, are toxic even at very low concentrations. However, so far there are no low-cost sensors available with sufficiently low detection limits and desired response times, which are able to detect them in the ranges relevant for air quality control. In this work, we address both, detection of small gas amounts and fast response times, using epitaxially grown graphene decorated with iron oxide nanoparticles. This hybrid surface is used as a sensing layer to detect formaldehyde and benzene at concentrations of relevance (low parts per billion). The performance enhancement was additionally validated using density functional theory calculations to see the effect of decoration on binding energies between the gas molecules and the sensor surface. Moreover, the time constants can be drastically reduced using a derivative sensor signal readout, allowing the sensor to work at detection limits and sampling rates desired for air quality monitoring applications.
DOI of the first publication: 10.3390/s19040918
Link to this record: urn:nbn:de:bsz:291--ds-277997
hdl:20.500.11880/29967
http://dx.doi.org/10.22028/D291-27799
ISSN: 1424-8220
Date of registration: 5-Nov-2020
Description of the related object: Supplementary Materials
Related object: http://www.mdpi.com/1424-8220/19/4/918/s1
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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