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Carbon Nanotube Gas and Vapor Sensors

Kauffman, Douglas R., Star, Alexander·2008·Angewandte Chemie International Edition

Abstract

Carbon nanotubes have aroused great interest since their discovery in 1991. Because of the vast potential of these materials, researchers from diverse disciplines have come together to further develop our understanding of the fundamental properties governing their electronic structure and susceptibility towards chemical reaction. Carbon nanotubes show extreme sensitivity towards changes in their local chemical environment that stems from the susceptibility of their electronic structure to interacting molecules. This chemical sensitivity has made them ideal candidates for incorporation into the design of chemical sensors. Towards this end, carbon nanotubes have made impressive strides in sensitivity and chemical selectivity to a diverse array of chemical species. Despite the lengthy list of accomplishments, several key challenges must be addressed before carbon nanotubes are capable of competing with state‐of‐the‐art solid‐state sensor materials. The development of carbon nanotube based sensors is still in its infancy, but continued progress may lead to their integration into commercially viable sensors of unrivalled sensitivity and vanishingly small dimensions.

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Metadata

Authors
Kauffman, D. R., & Star, A.
Venue
Angewandte Chemie International Edition
Publisher
Wiley
Published
2008-08-11
Volume
47
Issue
35
Pages
6550-6570
ISSN
  • 1433-7851 (ISSN-L)
  • 1521-3773
OpenAlex
W2158861167
Cited by
828
References
0
FWCI
48.71
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Carbon Nanotube Gas and Vapor Sensors. https://app.cochat.ai/papers/10.1002/anie.200704488
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Kauffman, D. R., & Star, A. (2008). Carbon Nanotube Gas and Vapor Sensors. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.200704488

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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