The purpose of this study is to optimize the thickness of a layered graphenic-based carbon compound, which is a non-magnetic material derived from biomass (old coconut shell). After the sample was exfoliated using HCl solution, the morphological structure showed that the material used in this study is a reduced graphene oxide (rGO), similar to carbon but with a thickness of less than 10 nm and lateral size in submicron (100 nm). The sample with a 2 mm thickness was then characterized using a vector network analyzer (VNA) to measure its reflection loss (RL). The measurement result is evaluated by converting the S-parameter values (S11 and S21) from the VNA using the Nicolsson Ross Weir (NRW) method to obtain input variables such as relative complex permeability and relative complex permittivity. Following this, the single-layer thickness of the sample was optimized using a genetic algorithm (GA), which can predict the appropriate thickness so that the optimum RL can be obtained. The optimum thickness of the sample was found to be 3.48 mm, which resulted in a much higher RL. The RL was re-measured for verification using a sample with the corresponding optimized thickness, revealing that this optimization is feasibly operational for a radar absorbing material (RAM) design.
HIGHLIGHTS
Carbon compounds containing graphenic phase derived from coconut shell are functional materials having various unique properties such as superior electrical conductivity, large surface area, and excellent structural flexibility, and microwave absorbtion
The single-layer microwave absorber employing carbon compounds has been prepared
The layer thickness optimized using a genetic algorithm (GA) can estimate the appropriate design with the maximum reflection loss (RL)
Development of magnetic functional materials based on carbon/manganite/ferrite composites for Microwave absorber materials applications
