微波食品加热
架空(工程)
计算机科学
电子工程
雷达
电磁仿真
无线
电磁辐射
还原(数学)
材料科学
超材料
声学
极高频率
频带
电磁学
微波传输
工程类
光电子学
物理
计算电磁学
电流(流体)
导电体
电磁场
电气工程
作者
Fan Li,Taisong Pan,Le Zuo,Taiqi Hu,YiFan Xiao,Lingxiao Wang,Rui Duan,Min Gao,Guang Yao,Mei Bi,Xiaolong Weng,T. Luo
标识
DOI:10.1002/lpor.202502669
摘要
ABSTRACT Creating a stretchable microwave metasurface capable of maintaining stable performance without relying on active tunable components is crucial for low‐cost, large‐scale, conformal, and shape‐adaptive electromagnetic wave manipulation. Current design paradigms leveraging simulations and theoretical predictions with deterministic metasurface geometries suffer from significantly high computational overhead to achieve this goal. Here, we present a stretchable metasurface (SM) that maintains consistent beam‐steering performance under external mechanical loading, designed through a machine learning‐based algorithm guided by simulation and experimental datasets of SM's electromagnetic responses to the deformation. The SM with hierarchical I‐shaped meta‐atoms exhibits robust beam‐steering performance (angular deviation ≤ 2°) under tensile strain up to 20%, enabling stable wireless communication in the 7.75–8.25 GHz band with an error vector magnitude variation of ≤ 1.5 dB. Additionally, an SM capable of consistently reducing the radar cross‐section by over 10 dB across 7.5–8.5 GHz is also realized with the proposed design approach.
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