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Cited by 531

The DOI matches its Crossref record; 188 of the 188 references it cites were found in a registry or an index.

Novel Nanostructures and Materials for Strong Light–Matter Interactions

Baranov, Denis G., Wersäll, Martin, Cuadra, Jorge, Antosiewicz, Tomasz J., Shegai, Timur·2018·ACS Photonics

Abstract

Quantum mechanical interactions between electromagnetic radiation and matter underlie a broad spectrum of optical phenomena. Strong light-matter interactions result in the well-known vacuum Rabi splitting and emergence of new polaritonic eigenmodes of the coupled system. Thanks to recent progress in nanofabrication, observation of strong coupling has become possible in a great variety of optical nanostructures. Here, we review recently studied and emerging materials for realization of strong light–matter interactions. We present general theoretical formalism describing strong coupling and give an overview of various photonic structures and materials allowing for realization of this regime, including plasmonic and dielectric nanoantennas, novel two-dimensional materials, carbon nanotubes, and molecular vibrational transitions. In addition, we discuss practical applications that can benefit from these effects and give an outlook on unsettled questions that remain open for future research.

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Metadata

Authors
Baranov, D. G., Wersäll, M., Cuadra, J., Antosiewicz, T. J., & Shegai, T.
Venue
ACS Photonics
Published
2017-10-20
Volume
5
Issue
1
Pages
24-42
ISSN
2330-4022 (ISSN-L)
OpenAlex
W2761506025
Cited by
531
References
188
FWCI
25.49
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Novel Nanostructures and Materials for Strong Light–Matter Interactions. https://app.cochat.ai/papers/10.1021/acsphotonics.7b00674
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Baranov, D. G., Wersäll, M., Cuadra, J., Antosiewicz, T. J., & Shegai, T. (2018). Novel Nanostructures and Materials for Strong Light–Matter Interactions. ACS Photonics. https://doi.org/10.1021/acsphotonics.7b00674

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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