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Cited by 474

The DOI matches its Crossref record; 99 of the 99 references it cites were found in a registry or an index.

Structure, Properties, Functionalization, and Applications of Carbon Nanohorns

Karousis, Nikolaos, Suarez-Martinez, Irene, Ewels, Christopher P., Tagmatarchis, Nikos·2016·Chemical Reviews

Abstract

Carbon nanohorns (sometimes also known as nanocones) are conical carbon nanostructures constructed from an sp(2) carbon sheet. Nanohorns require no metal catalyst in their synthesis, and can be produced in industrial quantities. They provide a realistic and useful alternative to carbon nanotubes, and possibly graphene, in a wide range of applications. They also have their own unique behavior due to their specific conical morphology. However, their research and development has been slowed by several factors, notably during synthesis, they aggregate into spherical clusters ∼100 nm in diameter, blocking functionalization and treatment of individual nanocones. This limitation has recently been overcome with a new approach to separating these "dahlia-like" clusters into individual nanocones. In this review, we describe the structure, synthesis, and topology of carbon nanohorns, and provide a detailed review of nanohorn chemistry.

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Metadata

Authors
Karousis, N., Suarez-Martinez, I., Ewels, C. P., & Tagmatarchis, N.
Venue
Chemical Reviews
Published
2016-04-13
Volume
116
Issue
8
Pages
4850-4883
ISSN
  • 0009-2665 (ISSN-L)
  • 1520-6890
OpenAlex
W2341375611
Cited by
474
References
99
FWCI
1.33
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Structure, Properties, Functionalization, and Applications of Carbon Nanohorns. https://app.cochat.ai/papers/10.1021/acs.chemrev.5b00611
The paper
Karousis, N., Suarez-Martinez, I., Ewels, C. P., & Tagmatarchis, N. (2016). Structure, Properties, Functionalization, and Applications of Carbon Nanohorns. Chemical Reviews. https://doi.org/10.1021/acs.chemrev.5b00611

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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.