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Non-Gaussian Resistance Fluctuations in Gold-Nanoparticle-Based Gas Sensors: An Appraisal of Different Evaluation Techniques
Gdansk Univ Technol, Fac Elect Telecommun & Informat, Narutowicza 11-12, PL-80233 Gdansk, Poland..
Gdansk Univ Technol, Fac Elect Telecommun & Informat, Narutowicza 11-12, PL-80233 Gdansk, Poland..
Gdansk Univ Technol, Fac Elect Telecommun & Informat, Narutowicza 11-12, PL-80233 Gdansk, Poland..
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Physics.
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2017 (English)In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 17, no 4, 757Article in journal (Refereed) Published
Abstract [en]

Volatile organic compounds, such as formaldehyde, can be used as biomarkers in human exhaled breath in order to non-invasively detect various diseases, and the same compounds are of much interest also in the context of environmental monitoring and protection. Here, we report on a recently-developed gas sensor, based on surface-functionalized gold nanoparticles, which is able to generate voltage noise with a distinctly non-Gaussian component upon exposure to formaldehyde with concentrations on the ppm level, whereas this component is absent, or at least much weaker, when the sensor is exposed to ethanol or to pure air. We survey four different statistical methods to elucidate a non-Gaussian component and assess their pros and cons with regard to efficient gas detection. Specifically, the non-Gaussian component was clearly exposed in analysis using level-crossing parameters, which require nothing but a modest computational effort and simple electronic circuitry, and analogous results could be reached through the bispectrum function, albeit with more intense computation. Useful information could be obtained also via the Levy-stable distribution and, possibly, the second spectrum.

Place, publisher, year, edition, pages
MDPI AG , 2017. Vol. 17, no 4, 757
Keyword [en]
gas sensor, 1/f noise, gold nanoparticles, higher-order statistics, bispectrum, second spectrum, level-crossing statistics, Levy-stable distribution
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:uu:diva-324335DOI: 10.3390/s17040757ISI: 000400822900098OAI: oai:DiVA.org:uu-324335DiVA: diva2:1110388
Available from: 2017-06-15 Created: 2017-06-15 Last updated: 2017-06-15Bibliographically approved

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Granqvist, Claes Göran
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