Computationally efficient surface conductivity graphene model for tunable graphene-based devices (Conference Presentation)

Ludmila J. Prokopeva; Huan Jiang; Alexander V. Kildishev; Di Wang; Sajid Choudhury

doi:10.1117/12.2547341

10 March 2020 Computationally efficient surface conductivity graphene model for tunable graphene-based devices (Conference Presentation)

Ludmila J. Prokopeva, Huan Jiang, Alexander V. Kildishev, Di Wang, Sajid Choudhury

Author Affiliations +

Proceedings Volume 11282, 2D Photonic Materials and Devices III; 112820W (2020) https://doi.org/10.1117/12.2547341
Event: SPIE OPTO, 2020, San Francisco, California, United States

Abstract

We present our computationally efficient approach to modeling graphene-based active metadevices followed by the design and optimization of a graphene-based tunable refractive index (RI) sensor with ultra-high sensitivity. The classical integral multi-variate surface conductivity is reformulated in the time and frequency domains with physically interpretable and fast-to-compute integration-free terms. The model reveals decomposition of graphene response into a universal constant term plus a damped oscillator (digamma functions in the frequency domain) plus non-oscillating correction terms for near-zero potentials. We showcase the advantage of our approach by optimizing an ultrasensitive, tunable RI sensor with graphene and hexagonal boron nitride nanoribbons.

Conference Presentation

Citation Download Citation

Ludmila J. Prokopeva, Huan Jiang, Alexander V. Kildishev, Di Wang, and Sajid Choudhury "Computationally efficient surface conductivity graphene model for tunable graphene-based devices (Conference Presentation)", Proc. SPIE 11282, 2D Photonic Materials and Devices III, 112820W (10 March 2020); https://doi.org/10.1117/12.2547341

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