Abstract

Electro-optical modulators which work at the near-infrared range are significant for a variety of applications such as communication and sensing. However, currently available approaches result in rather bulky devices which suffer from low integration and can hardly operate at low power consumption levels. Graphene, an emerging advanced material, has been widely utilized due to its tunability by gating which allows one to realize active optical devices. Plasmonic waveguides, one of the most promising candidates for subwavelength optical confinement, provide a way to manipulate light on scales much smaller than the wavelength. In this paper, we combine the advantages of graphene and plasmonic waveguides and propose a tunable graphene-based hybrid plasmonic modulator (GHPM). Considering several parameters of the GHPM, the modulation depth can reach approximately 0.3 dB·μm−1 at low gating voltages. Moreover, we combine GHPM with metal-insulator-metal (MIM) structure to propose another symmetrical GHPM with a modulation depth of 0.6 dB·μm−1. Our modulators which utilize the light-matter interaction tuned by electro-doped graphene are of great potential for many applications in nanophotonics.

Highlights

  • The need for fast, compact and low-energy consumption electro-optical modulators has motivated research into optical structures capable of guiding light with deep subwavelength confinement[1]

  • We propose a tunable graphene-based hybrid plasmonic modulator (GHPM) combining the advantages of graphene and plasmonic waveguides

  • We have proposed a tunable graphene-based hybrid plasmonic modulator (GHPM) combining the advantages of graphene and plasmonic waveguides

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Summary

Introduction

The need for fast, compact and low-energy consumption electro-optical modulators has motivated research into optical structures capable of guiding light with deep subwavelength confinement[1]. We can use a grating to couple light into a plasmon-propagating mode which can be tuned by gated graphene via electrical doping (details see Methods).

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