Impact Factor5.1

DOI number:10.1016/j.diamond.2025.112793

Affiliation of Author(s):西北大学电子信息学院

Teaching and Research Group:电子科学与技术系

Journal:Diamond and Related Materials

Place of Publication:Netherladn

Funded by:国际科技合作项目

Key Words:Metamaterial absorber; Ultra-wideband; Terahertz; Graphene; Machine learning; Tunability

Abstract:Ultra-wideband absorbers are essential devices capable of efficiently absorbing electromagnetic waves over a broad frequency range, with extensive applications in radar detection, wireless communication, and stealth technology. Their primary advantage lies in the ability to simultaneously cover both low and high-frequency absorption bands, thereby significantly enhancing stealth performance and anti-interference capabilities. However, the design of ultra-wideband absorbers still faces two major technical challenges: first, achieving stable absorption performance across an ultra-wide frequency range; and second, further improving absorption efficiency while maintaining broadband stability to meet the demands of various application scenarios. In this study, we propose a terahertz metamaterial absorber based on a three-layer composite structure incorporating patterned graphene sheets. This structure enables dynamic tunability between absorption and reflection states. To optimize the absorption performance, an innovative machine learning-based optimization strategy is introduced. Firstly, forwarding prediction is employed to quantify the optimization weights of different structural parameters, allowing for the selection of key tunable parameters. Subsequently, inverse prediction is utilized to determine the optimal structural configuration based on the target absorption performance. As a result, the proposed design achieves an absorption rate exceeding 90 % within the 2.28–4.68 THz frequency range, demonstrating significant improvements in absorption efficiency and tunability.

Indexed by:Journal paper

Discipline:Engineering

First-Level Discipline:Electronic Science and Techonology

Document Type:J

Volume:Part B

Issue:195

Page Number:112793

Translation or Not:no

Date of Publication:2025-11-01

Included Journals:SCI

Links to published journals:https://www.sciencedirect.com/science/article/pii/S0925963525008507

First Author:Shilei Tian

Correspondence Author:Cheng Chen*

All the Authors:Jiaxuan Xue

All the Authors:Zhihao Li

All the Authors:Jixin Wang

All the Authors:Johan Stiens