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Chemical Vapor Sensing with Monolayer MoS2

Perkins, F. K., Friedman, A. L., Cobas, E., Campbell, P. M., Jernigan, G. G., Jonker, B. T.·2013·Nano Letters

Abstract

Two-dimensional materials such as graphene show great potential for future nanoscale electronic devices. The high surface-to-volume ratio is a natural asset for applications such as chemical sensing, where perturbations to the surface resulting in charge redistribution are readily manifested in the transport characteristics. Here we show that single monolayer MoS(2) functions effectively as a chemical sensor, exhibiting highly selective reactivity to a range of analytes and providing sensitive transduction of transient surface physisorption events to the conductance of the monolayer channel. We find strong response upon exposure to triethylamine, a decomposition product of the V-series nerve gas agents. We discuss these results in the context of analyte/sensor interaction in which the analyte serves as either an electron donor or acceptor, producing a temporary charge perturbation of the sensor material. We find highly selective response to electron donors and little response to electron acceptors, consistent with the weak n-type character of our MoS(2). The MoS(2) sensor exhibits a much higher selectivity than carbon nanotube-based sensors.

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Metadata

Authors
Perkins, F. K., Friedman, A. L., Cobas, E., Campbell, P. M., Jernigan, G. G., & Jonker, B. T.
Venue
Nano Letters
Published
2013-01-24
Volume
13
Issue
2
Pages
668-673
ISSN
  • 1530-6984 (ISSN-L)
  • 1530-6992
OpenAlex
W1966932982
Cited by
1,138
References
2
FWCI
64.11
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Chemical Vapor Sensing with Monolayer MoS2. https://app.cochat.ai/papers/10.1021/nl3043079
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Perkins, F. K., Friedman, A. L., Cobas, E., Campbell, P. M., Jernigan, G. G., & Jonker, B. T. (2013). Chemical Vapor Sensing with Monolayer MoS2. Nano Letters. https://doi.org/10.1021/nl3043079

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.