Abstract
The exceptionally large active surface-to-volume ratio of carbon nanotubes makes it an appealing candidate for gas sensing applications. Here, we studied the DC and low-frequency noise characteristics of a randomly oriented network of carbon nanotubes under NO2 gas atmosphere at two different wavelengths of the UV light-emitting diodes. The UV irradiation allowed to sense lower concentrations of NO2 (at least 1 ppm) compared to dark conditions. Our experimental studies confirmed that the flicker noise of resistance fluctuations under UV irradiation significantly enhanced the sensing characteristics of nanotube networks at low concentrations. We observed a dominating 1/f-like noise component below 1 kHz. The sensitivity of nanotube networks was higher for shorter wavelength, whereas drift in the resistance was smaller for longer wavelength. The measurements under the NO2 gas atmosphere revealed a remarkable reduction in DC resistance drift of the nanotube network between consecutive cycles of gas sensing. This phenomenon was explained via absorption-desorption of NO2 gas molecules on nanotubes surface. Since small concentrations of NO2 pose a threat to the ecosystem, these results might play a significant role in the development of sensitive nanotubes-based photo-activated gas sensors.
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- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.1016/j.snb.2021.131069
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- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
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SENSORS AND ACTUATORS B-CHEMICAL
no. 352,
ISSN: 0925-4005 - Language:
- English
- Publication year:
- 2022
- Bibliographic description:
- Drozdowska K., Rehman A., Krajewska A., Lioubtchenko D. V., Pavłov K., Rumyantsev S., Smulko J., Cywiński G.: Effects of UV light irradiation on fluctuation enhanced gas sensing by carbon nanotube networks// SENSORS AND ACTUATORS B-CHEMICAL -Vol. 352,iss. Part 2 (2022), s.131069-
- DOI:
- Digital Object Identifier (open in new tab) 10.1016/j.snb.2021.131069
- Sources of funding:
-
- Free publication
- Verified by:
- Gdańsk University of Technology
Referenced datasets
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