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Cited by 164

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

Architecture of Metallic Nanostructures: Synthesis Strategy and Specific Applications

Chen, Hao Ming, Liu, Ru-Shi·2011·The Journal of Physical Chemistry C

Abstract

Metallic nanoparticles are emerging as key materials use in catalysis, plasmonics, sensing, and spectroscopy. To approach these applications, the control of nanostructures provides increasing selectivity and functionality. This feature article highlights our recent research progress in this emerging field. This article discusses control of the shape of metallic nanostructures and their physical/chemical nature. The numerous approaches for synthesizing multishaped nanostructures include (i) the use of hard templates such as anodic aluminum oxide, (ii) the use of soft templates such as cetyltrimethylammonium bromide (CTAB), and (iii) the use of sacrificial templates. Finally, the use of such nanostructures in catalysis, sensing, and photothermal therapy are demonstrated. General strategies for these methods are discussed and related recent research directions will also be addressed in this feature article.

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Metadata

Authors
Chen, H. M., & Liu, R.-S.
Venue
The Journal of Physical Chemistry C
Published
2011-02-08
Volume
115
Issue
9
Pages
3513-3527
ISSN
  • 1932-7447 (ISSN-L)
  • 1932-7455
OpenAlex
W2330865980
Cited by
164
References
3
FWCI
8.08
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Architecture of Metallic Nanostructures: Synthesis Strategy and Specific Applications. https://app.cochat.ai/papers/10.1021/jp108403r
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Chen, H. M., & Liu, R.-S. (2011). Architecture of Metallic Nanostructures: Synthesis Strategy and Specific Applications. The Journal of Physical Chemistry C. https://doi.org/10.1021/jp108403r

Data sources

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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.