Deep neural network-enabled dual-functional wideband absorbers

Abstract

Abstract The increasing interest in switchable and tunable wideband perfect absorbers for applications such as modulation, energy harvesting, and spectroscopy has significantly driven research efforts. In this study, we present a dual-function terahertz (THz) metamaterial absorber supported by deep neural networks (DNN). This absorber achieves dual-wideband perfect absorption through the use of graphene and vanadium dioxide (VO₂), enabling both switching and tuning functionalities. Simulation results show that, in the insulating phase of VO₂, a high-frequency wideband absorption ranging from 9.31 to 9.77 THz is achieved, with an absorption rate exceeding 90%. In contrast, in the metallic phase of VO₂, a full-band wideband absorption above 90% is observed from 8.44 to 9.75 THz. The corresponding fractional bandwidths are 61.3% and 174.6%, respectively. Additionally, electrical tuning of graphene’s Fermi level from 0.01 to 1 eV enables continuous modulation of absorption intensity between 48 and 100%. The absorber also exhibits polarization insensitivity to TE and TM waves due to its symmetric design and broad incidence angle. This design holds significant potential for various THz applications, including switching, electromagnetic shielding, stealth technology, filtering, and sensing.

Keywords

• Metamaterial absorber
• Deep neural networks (DNN)
• Dual-function
• Dual-wideband