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Graphene Nanoribbons Obtained by Electrically Unwrapping Carbon Nanotubes
Abstract
We describe a clean method of graphene nanoribbon (GNR) extraction from multiwall carbon nanotubes (MWNTs), performed in a high vacuum, nonchemical environment. Electrical current and nanomanipulation are used to unwrap a portion of the MWNT and thus produce a GNR of desired width and length. The unwrapping method allows GNRs to be concurrently characterized structurally via high-resolution transmission electron microscopy (TEM) and evaluated for electrical transport, including situations for which the GNR is severely mechanically flexed. High quality GNRs have exceptional current-carrying capacity, comparable to the exfoliated graphene.
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Citations
Cites
Narrow graphene nanoribbons from carbon nanotubes
Jiao, L., Zhang, L., Wang, X., Diankov, G., & Dai, H. (2009) · Nature · doi:10.1038/nature07919 · Cited by 2,441
Cited by
Georgakilas, V., Perman, J. A., Tucek, J., & Zboril, R. (2015) · Chemical Reviews · doi:10.1021/cr500304f · Cited by 2,147
Biological and chemical sensors based on graphene materials
Liu, Y., Dong, X., & Chen, P. (2012) · Chem. Soc. Rev. · doi:10.1039/c1cs15270j · Cited by 1,748
Guo, S., & Dong, S. (2011) · Chemical Society Reviews · doi:10.1039/c0cs00079e · Cited by 1,293
Kumar, R., Sahoo, S., Joanni, E., Singh, R. K., Tan, W. K., Kar, K. K., & Matsuda, A. (2019) · Progress in Energy and Combustion Science · doi:10.1016/j.pecs.2019.100786 · Cited by 554
Graphene edges: a review of their fabrication and characterization
Jia, X., Campos-Delgado, J., Terrones, M., Meunier, V., & Dresselhaus, M. S. (2011) · Nanoscale · doi:10.1039/c0nr00600a · Cited by 461
Metadata
- Authors
- Kim, K., Sussman, A., & Zettl, A.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2010-02-04
- Volume
- 4
- Issue
- 3
- Pages
- 1362-1366
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W1993574804
- Cited by
- 164
- References
- 1
- FWCI
- 9.73
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
