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Cited by 384

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Surface enhanced Raman scattering in the near infrared using metal nanoshell substrates

Oldenburg, Steven J., Westcott, Sarah L., Averitt, Richard D., Halas, Naomi J.·1999·The Journal of Chemical Physics

Abstract

A metal nanoshell is a composite nanoparticle consisting of a dielectric core coated by a thin metal shell; its peak plasmon resonance wavelength is determined by the ratio of the core diameter to the shell thickness. When p-mercaptoaniline (p-MA) is in solution with gold nanoshells that have their plasmon resonance near a 1.06 μm excitation source, significant surface enhanced Raman scattering (SERS) is observed. The strongest Raman enhancements are obtained when enough gold is deposited on the silica cores to form a nearly complete metal shell. Correlations between transmission electron microscopy (TEM)-defined structure, ultraviolet (UV)-visible spectra, SERS signal strength, and electromagnetic theory show that the SERS signal is due to both the local enhancement of the dielectric field via the plasmon resonance of the nanostructure and to the localized regions of high field intensity provided by the nearly completed gold shell. Comparison with SERS enhancements on completed nanoshell structures indicates the relative contribution of these two effects.

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Metadata

Authors
Oldenburg, S. J., Westcott, S. L., Averitt, R. D., & Halas, N. J.
Venue
The Journal of Chemical Physics
Published
1999-09-08
Volume
111
Issue
10
Pages
4729-4735
ISSN
  • 0021-9606 (ISSN-L)
  • 1089-7690
OpenAlex
W1963786116
Cited by
384
References
2
FWCI
7.71
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Surface enhanced Raman scattering in the near infrared using metal nanoshell substrates. https://app.cochat.ai/papers/10.1063/1.479235
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Oldenburg, S. J., Westcott, S. L., Averitt, R. D., & Halas, N. J. (1999). Surface enhanced Raman scattering in the near infrared using metal nanoshell substrates. The Journal of Chemical Physics. https://doi.org/10.1063/1.479235

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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.