Results in Physics (Jun 2021)
Multi-bias graphene-based THz super absorber
Abstract
The terahertz frequency band becomes a growth platform of various applications from medical imaging to indoor communications. Emerging new materials such as graphene and developing reliable models paved the design way for graphene-based microstructures. This paper proposes a relatively comprehensive design methodology for graphene-based multi-layers structures. The procedure includes forming device geometry, finding graphene patterns, material types, and optimizing control parameters. In this way, a reconfigurable THz wave absorber is introduced. Exploiting a multi bias scheme for a single graphene layer provide opportunity to affect device reaction via bias itself and patterns period simultaneously which increase adjustability of device response. Also using two different graphene patterns turns the device complex regarding design optimizations and simulations. So a well-known and simple circuit representation is used to design the proposed methodology and the proposed device. Knowing equivalent circuit models for the device elements triggers developing an evolutionary algorithm to search for a desirable response. In this context, the paper suggests using a weighted binary matrix in the design process. The matrix determines bias schemes for each layer. Then an evolutionary algorithm optimizes whole biases values. The expectation is more in-depth control over the device behavior via biases values. This is verified by exploited circuit model formulations and Finite Element Method (FEM) as numerical simulation for a unique three layers device.