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Published February 21, 2018 | Submitted
Journal Article Open

Ultralight Angstrom-Scale Optimal Optical Reflectors

Abstract

High reflectance in many state-of-the-art optical devices is achieved with noble metals. However, metals are limited by losses and, for certain applications, by their high mass density. Using a combination of ab initio and optical transfer matrix calculations, we evaluate the behavior of graphene-based angstrom-scale metamaterials and find that they could act as nearly perfect reflectors in the mid–long-wave infrared (IR) range. The low density of states for electron–phonon scattering and interband excitations leads to unprecedented optical properties for graphene heterostructures, especially alternating atomic layers of graphene and hexagonal boron nitride, at wavelengths greater than 10 μm. At these wavelengths, these materials exhibit reflectivities exceeding 99.7% at a fraction of the weight of noble metals, as well as plasmonic mode confinement and quality factors that are greater by an order of magnitude compared to noble metals. These findings hold promise for ultracompact optical components and waveguides for mid-IR applications. Moreover, unlike metals, the photonic properties of these heterostructures could be actively tuned via chemical and/or electrostatic doping, providing exciting possibilities for tunable devices.

Additional Information

© 2017 American Chemical Society. Received: June 13, 2017; Published: October 11, 2017. G.T.P. acknowledges fruitful discussions with Prof. P. Yeh. We also thank Prof. Harry A. Atwater, Prof. John D. Joannopoulous, Yi Yang, and Tena Dubcek for helpful discussions. We acknowledge financial support from NG Next at the Northrop Grumman Corporation. G.T.P. acknowledges financial support from the American Association of University Women (AAUW). P.N. acknowledges support from the Harvard University Center for the Environment (HUCE) and faculty startup funding from the John A. Paulson School of Engineering and Applied Sciences at Harvard. R.S. acknowledges startup funding from Rensselaer Polytechnic Institute (RPI). N.E. acknowledges partial support from the U.S. Air Force Office of Scientific Research Multidisciplinary University Research Initiative grant number FA9550-17-1-0002. This research was supported (in part) by the U.S. Army Research Office under contract W911NF-13-D-0001. Calculations in this work were performed on the BlueGene/Q supercomputer in the Center for Computational Innovations (CCI) at RPI, as well as in the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. M.S. (reading and analysis of the manuscript) was supported by S3TEC, an Energy Frontier Research Center funded by the U.S. Department of Energy under grant no. DE-SC0001299. H.B. acknowledges support from the QuantiXLie Center of Excellence.

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