Effective Modeling of Magnetized Graphene by the Wave Concept Iterative Process Method Using Boundary Conditions

Abstract

Due to static magnetic field, the conductivity of graphene becomes an anisotropic tensor, which complicates most modeling methodologies. A practical approach to the Wave Concept Iterative Process method (WCIP) modeling of magnetized graphene sheets as an anisotropic conductive surface from the microwave to terahertz frequencies is proposed. We first introduce a brief description of modeling magnetized graphene as an infinitesimally thin conductive sheet. Then, we present a novel manner for the implementation of the anisotropic boundary conditions using the wave concept in the WCIP method. This proposed method is benchmarked with numerical examples to demonstrate its applicability and accuracy. The proposed approach is used to compare the anisotropic model, isotropic model, and the metal for a strip waveguide. We show that the anisotropic model gives more efficient results.

Non-Reciprocal Antenna Array Based on Magnetized Graphene for THZ Applications Using the Iterative Method

“…The classic WCIP method has been described in detail in various articles [16][17][18][19][20][21][22][23][24][25]. This method is presented by writing the electric field and current density in terms of waves.…”

“…The implementation of the boundary conditions of the magnetized graphene in the WCIP method has been demonstrated in detail in this article [25]. After some manipulation, we can derive the scattering matrix of the magnetized graphene as ⎛…”

“…In most of the numerical methods, magnetized graphene is usually incorporated in the algorithm by transforming the surface conductivity to a volumetric conductivity by dividing the thickness of the graphene, which might introduce a multiscale computational problem in simulation, require massive CPU time and memory, and make the optimization process tiresome. In order to overcome this problem, the wave concept iterative process method can be applied by treating the 2D materials as conductive surface boundaries, to not only yield precision in the result, but also reduce the time consumption and memory size [16][17][18][19][20][21][22][23][24][25].…”