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Cited by 2,229

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Emerging Transparent Electrodes Based on Thin Films of Carbon Nanotubes, Graphene, and Metallic Nanostructures

Hecht, David S., Hu, Liangbing, Irvin, Glen·2011·Advanced Materials

Abstract

Transparent electrodes are a necessary component in many modern devices such as touch screens, LCDs, OLEDs, and solar cells, all of which are growing in demand. Traditionally, this role has been well served by doped metal oxides, the most common of which is indium tin oxide, or ITO. Recently, advances in nano‐materials research have opened the door for other transparent conductive materials, each with unique properties. These include CNTs, graphene, metal nanowires, and printable metal grids. This review will explore the materials properties of transparent conductors, covering traditional metal oxides and conductive polymers initially, but with a focus on current developments in nano‐material coatings. Electronic, optical, and mechanical properties of each material will be discussed, as well as suitability for various applications.

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Crossref · 10.1002/adma.201003188

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Metadata

Authors
Hecht, D. S., Hu, L., & Irvin, G.
Venue
Advanced Materials
Publisher
Wiley
Published
2011-02-15
Volume
23
Issue
13
Pages
1482-1513
ISSN
  • 0935-9648 (ISSN-L)
  • 1521-4095
OpenAlex
W2013739204
Cited by
2,229
References
9
FWCI
107.40
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Emerging Transparent Electrodes Based on Thin Films of Carbon Nanotubes, Graphene, and Metallic Nanostructures. https://app.cochat.ai/papers/10.1002/adma.201003188
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Hecht, D. S., Hu, L., & Irvin, G. (2011). Emerging Transparent Electrodes Based on Thin Films of Carbon Nanotubes, Graphene, and Metallic Nanostructures. Advanced Materials. https://doi.org/10.1002/adma.201003188

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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.