Thickness optimization of a double-layered microwave absorber combining magnetic and dielectric particles

Abstract

The purpose of this study is to optimize the thickness of the double-layered microwave absorber for obtaining the highest absorption. The graphenic-based carbon compounds and Fe _3 O _4 magnetic particles were combined to fabricate the double-layered absorber. The thickness was optimized by employing a genetic algorithm (GA) to obtain high reflection loss $\left(R{L}_{\min }\right)$ values. These samples at a thickness of 2 mm were measured for reflection loss (RL) with a Vector Network Analyzer (VNA). Input variables, such as relatively complex permeability and relatively complex permittivity, were obtained using a conversion program that uses Nicolson-Ross-Weir (NRW) method from VNA S-parameter values (S _11 and S _21 ) data. By entering the permeability and permittivity of the complex relative to GA, the thickness can be optimized to produce high $R{L}_{\min }$ value. Optimization of the double-layer thickness of 12 absorbers produces the optimum thickness of ${d}_{1}$ = 5.99 mm and ${d}_{2}$ = 0.87 mm among the materials combination, which results in a high $R{L}_{\min }$ (−44.69 dB). This optimization is very important for designing double-layer radar absorbing material (RAM) which results in high $R{L}_{\min }$ values.

Keywords

• iron rock
• double-layer absorber
• graphenic
• genetic algorithm
• thickness optimization