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Cited by 567

The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.

Semiconductor-Metal Nanoparticle Molecules: Hybrid Excitons and the Nonlinear Fano Effect

Open access
Zhang, Wei, Govorov, Alexander O., Bryant, Garnett W.·2006·Physical Review Letters

Abstract

Modern nanotechnology opens the possibility of combining nanocrystals of various materials with very different characteristics in one superstructure. Here we study theoretically the optical properties of hybrid molecules composed of semiconductor and metal nanoparticles. Excitons and plasmons in such a hybrid molecule become strongly coupled and demonstrate novel properties. At low incident light intensity, the exciton peak in the absorption spectrum is broadened and shifted due to incoherent and coherent interactions between metal and semiconductor nanoparticles. At high light intensity, the absorption spectrum demonstrates a surprising, strongly asymmetric shape. This shape originates from the coherent internanoparticle Coulomb interaction and can be viewed as a nonlinear Fano effect which is quite different from the usual linear Fano resonance.

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Metadata

Authors
Zhang, W., Govorov, A. O., & Bryant, G. W.
Venue
Physical Review Letters
Published
2006-10-04
Volume
97
Issue
14
Pages
146804-146804
ISSN
  • 0031-9007 (ISSN-L)
  • 1079-7114
OpenAlex
W2011464846
Cited by
567
References
19
FWCI
9.26
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Semiconductor-Metal Nanoparticle Molecules: Hybrid Excitons and the Nonlinear Fano Effect. https://app.cochat.ai/papers/10.1103/physrevlett.97.146804
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Zhang, W., Govorov, A. O., & Bryant, G. W. (2006). Semiconductor-Metal Nanoparticle Molecules: Hybrid Excitons and the Nonlinear Fano Effect. Physical Review Letters. https://doi.org/10.1103/physrevlett.97.146804

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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.