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Applied Surface Science
Article . 2023 . Peer-reviewed
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Optimization of multilayer graphene-based gas sensors by ultraviolet photoactivation

Authors: Peña, Álvaro (author); Matatagui, Daniel (author); Ricciardella, F. (author); Sacco, L.N. (author); Vollebregt, S. (author); Otero, Daniel (author); López-Sánchez, Jesús (author); +2 Authors

Optimization of multilayer graphene-based gas sensors by ultraviolet photoactivation

Abstract

Nitrogen dioxide (NO) is a potential hazard to human health at low concentrations, below one part per million (ppm). NO can be monitored using gas sensors based on multi-layered graphene operating at ambient temperature. However, reliable detection of concentrations on the order of parts per million and lower is hindered by partial recovery and lack of reproducibility of the sensors after exposure. We show how to overcome these longstanding problems using ultraviolet (UV) light. When exposed to NO, the sensor response is enhanced by 290 % − 550 % under a 275 nm wavelength light emitting diode irradiation. Furthermore, the sensor's initial state is completely restored after exposure to the target gas. UV irradiation at 68 W/m2 reduces the NO detection limit to 30 parts per billion (ppb) at room temperature. We investigated sensor performance optimization for UV irradiation with different power densities and target gases, such as carbon oxide and ammonia. Improved sensitivity, recovery, and reproducibility of UV-assisted graphene-based gas sensors make them suitable for widespread environmental applications.

11 páginas; 7 figuras, 4 tablas

Countries
Netherlands, Spain
Keywords

Física de materiales, Limit of detection, Graphene gas sensors, 538.9, 620, Keywords: Graphene gas sensors Ultraviolet Nitrogen dioxide, Ammonia, Carbon monoxide, Ultraviolet, Nitrogen dioxide

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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35
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85
206
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