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Cited by 526

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Visualizing Graphene Based Sheets by Fluorescence Quenching Microscopy

Open access
Kim, Jaemyung, Cote, Laura J., Kim, Franklin, Huang, Jiaxing·2010·Journal of the American Chemical Society

Abstract

Graphene based sheets have stimulated great interest due to their superior mechanical, electrical, and thermal properties. A general visualization method that allows quick observation of these single atomic layers would be highly desirable as it can greatly facilitate sample evaluation and manipulation, and provide immediate feedback to improve synthesis and processing strategies. Here we report that graphene based sheets can be made highly visible under a fluorescence microscope by quenching the emission from a dye coating, which can be conveniently removed afterward by rinsing without disrupting the sheets. Current imaging techniques for graphene based sheets rely on the use of special substrates. In contrast, the fluorescence quenching mechanism is no longer limited by the type of substrate. Graphene, reduced graphene oxide, or even graphene oxide sheets deposited on arbitrary substrates can now be readily visualized with good contrast for layer counting. Direct observation of suspended sheets in solution was also demonstrated. The fluorescence quenching microscopy offers unprecedented imaging flexibility and could become a general tool for characterizing graphene based materials.

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Crossref · 10.1021/ja906730d

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Metadata

Authors
Kim, J., Cote, L. J., Kim, F., & Huang, J.
Venue
Journal of the American Chemical Society
Published
2009-12-04
Volume
132
Issue
1
Pages
260-267
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W1975333813
Cited by
526
References
3
FWCI
16.43
Type
journal article
Language
en
Open access
green

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.