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doi:10.22028/D291-34316
Titel: | Functionalized epitaxial graphene as versatile platform for air quality sensors |
VerfasserIn: | Rodner, Marius |
Sprache: | Englisch |
Erscheinungsjahr: | 2021 |
Freie Schlagwörter: | graphene gas sensor |
DDC-Sachgruppe: | 500 Naturwissenschaften 600 Technik |
Dokumenttyp: | Dissertation |
Abstract: | The work presented in this thesis focuses on epitaxial graphene on SiC as a platform for air quality sensors. Several approaches have been tested and evaluated to increase the sensitivity, selectivity, speed of response and stability of the sensors. The graphene surfaces have been functionalized, for example, with different metal oxide nanoparticles and nanolayers using hollow-cathode sputtering and pulsed laser deposition. The modified surfaces were investigated to-wards topography, integrity and chemical composition with characterization methods such as atomic force microscopy and Raman spectroscopy. Interaction energies between several analytes and nanoparticle-graphene-combinations were calculated by density functional theory to find the optimal material for specific target gases, and to verify the usefulness of this approach. The impact of environmental influences such as operating temperature, relative humidity and UV irradiation on sensing properties was investigated as well. To further enhance sensor performances, the first-order time-derivative of the sensor’s resistance was introduced to speed up sensor response and a temperature cycled operation mode was investigated towards selectivity. Applying these methods in laboratory conditions, sensors with a quantitative readout of single ppb benzene and formaldehyde were developed. These results show promise to fill the existing gap of low-cost but highly sensitive and fast gas sensors for air quality monitoring. |
Link zu diesem Datensatz: | urn:nbn:de:bsz:291--ds-343166 hdl:20.500.11880/31516 http://dx.doi.org/10.22028/D291-34316 |
Erstgutachter: | Schütze, Andreas |
Tag der mündlichen Prüfung: | 28-Mai-2021 |
Datum des Eintrags: | 13-Jul-2021 |
Drittmittel / Förderung: | Financial support by the Swedish Foundation for Strategic Research (SSF) through the grants GMT14-0077 and RMA15-024. |
In Beziehung stehendes Objekt: | http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-174680 |
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 | |
---|---|---|---|---|
Dissertation_MRodner_UdS.pdf | Doctoral thesis | 7,75 MB | Adobe PDF | Öffnen/Anzeigen |
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