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Cited by 745

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Graphene Oxide: Structural Analysis and Application as a Highly Transparent Support for Electron Microscopy

Wilson, Neil R., Pandey, Priyanka A., Beanland, Richard, Young, Robert J., Kinloch, Ian A., Gong, Lei, Liu, Zheng, Suenaga, Kazu, Rourke, Jonathan P., York, Stephen J., Sloan, Jeremy·2009·ACS Nano

Abstract

We report on the structural analysis of graphene oxide (GO) by transmission electron microscopy (TEM). Electron diffraction shows that on average the underlying carbon lattice maintains the order and lattice-spacings of graphene; a structure that is clearly resolved in 80 kV aberration-corrected atomic resolution TEM images. These results also reveal that single GO sheets are highly electron transparent and stable in the electron beam, and hence ideal support films for the study of nanoparticles and macromolecules by TEM. We demonstrate this through the structural analysis of physiological ferritin, an iron-storage protein.

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Metadata

Authors
Wilson, N. R., Pandey, P. A., Beanland, R., Young, R. J., Kinloch, I. A., Gong, L., Liu, Z., Suenaga, K., Rourke, J. P., York, S. J., & Sloan, J.
Venue
ACS Nano
Published
2009-08-18
Volume
3
Issue
9
Pages
2547-2556
ISSN
  • 1936-0851 (ISSN-L)
  • 1936-086X
OpenAlex
W2098821528
Cited by
745
References
2
FWCI
24.38
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Graphene Oxide: Structural Analysis and Application as a Highly Transparent Support for Electron Microscopy. https://app.cochat.ai/papers/10.1021/nn900694t
The paper
Wilson, N. R., Pandey, P. A., Beanland, R., Young, R. J., Kinloch, I. A., Gong, L., Liu, Z., Suenaga, K., Rourke, J. P., York, S. J., & Sloan, J. (2009). Graphene Oxide: Structural Analysis and Application as a Highly Transparent Support for Electron Microscopy. ACS Nano. https://doi.org/10.1021/nn900694t

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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.