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Optical modulators with 2D layered materials

Open access
Sun, Zhipei, Martinez, Amos, Wang, Feng·2016·Nature Photonics

Abstract

The recent realization that 2D layered materials could modulate light with superior performance has prompted intense research and significant advances, paving the way for realistic applications. Light modulation is an essential operation in photonics and optoelectronics. With existing and emerging technologies increasingly demanding compact, efficient, fast and broadband optical modulators, high-performance light modulation solutions are becoming indispensable. The recent realization that 2D layered materials could modulate light with superior performance has prompted intense research and significant advances, paving the way for realistic applications. In this Review, we cover the state of the art of optical modulators based on 2D materials, including graphene, transition metal dichalcogenides and black phosphorus. We discuss recent advances employing hybrid structures, such as 2D heterostructures, plasmonic structures, and silicon and fibre integrated structures. We also take a look at the future perspectives and discuss the potential of yet relatively unexplored mechanisms, such as magneto-optic and acousto-optic modulation.

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Metadata

Authors
Sun, Z., Martinez, A., & Wang, F.
Venue
Nature Photonics
Published
2016-03-31
Volume
10
Issue
4
Pages
227-238
ISSN
  • 1749-4885 (ISSN-L)
  • 1749-4893
OpenAlex
W2271673449
Cited by
1,515
References
4
FWCI
80.77
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Optical modulators with 2D layered materials. https://app.cochat.ai/papers/10.1038/nphoton.2016.15
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Sun, Z., Martinez, A., & Wang, F. (2016). Optical modulators with 2D layered materials. Nature Photonics. https://doi.org/10.1038/nphoton.2016.15

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.