Mechanically Programmable Electromagnetic Metamaterials for Generalized Phase Tailoring With Zero Static Power Consumption
Abstract
ABSTRACT Mechanically modulated reconfigurable electromagnetic metamaterials represent a promising avenue for flexible wavefront manipulation. However, most mechanically tunable designs rely on collective deformations and continuous external loading, leading to limited programmability and high static power consumption. Here, we present a mechanically programmable electromagnetic metamaterial enabled by 3D‐printed shape memory polymer (SMP) compression‐torsion coupling structures integrated with the three‐fold symmetric three‐armed meta‐atoms (C3 meta‐atoms) for generalized phase tailoring with zero static power consumption. The compression‐torsion coupling structures enable deterministic and independent in‐plane rotation of each unit cell under vertical compression, while the C3 meta‐atoms provide sixfold cross‐circularly polarized phase amplification, achieving full 0°–360° phase coverage with a narrow rotational angular range of 0°–60°. Leveraging the intrinsic shape‐locking and shape‐recovery properties of SMP, arbitrary phase distribution patterns are attainable via mechanical coding without sustained power consumption, and can be repeatedly erased and rewritten via thermal recovery. Numerical simulations and experimental characterizations reveal the design principle and operation mechanism of the metamaterial, verifying its programmable functionalities through demonstrations of anomalous refraction, reconfigurable metalens, and orbital‐angular‐momentum (OAM) generators. These findings provide a conceptual framework for low‐energy, programmable, and reconfigurable wavefront modulation, laying a foundation for advancing next‐generation mechanically programmable electromagnetic metamaterials.
Article Details
Authors (8)
Shuchang He
Huanjiang Laboratory State Key Laboratory of Brain‐Machine Intelligence The First Affiliated Hospital School of Medicine Zhejiang University Zhejiang China
Chen Yang
Hangzhou Institute of Advanced Studies
Maosheng Ye
Department of Electronic Science, College of Big Data and Information Engineering, Guizhou University 1 , Guiyang 550025,
Haishan Tang
Huanjiang Laboratory State Key Laboratory of Brain‐Machine Intelligence The First Affiliated Hospital School of Medicine Zhejiang University Zhejiang China
Fei Gao
Chengjun Wang
Qian Zhao
Zhejiang University , , ,
Jizhou Song
Department of Engineering Mechanics, Key Laboratory of Soft Machines and Smart Devices of Zhejiang Province, State Key Laboratory of Brain-Machine Intelligence, Zhejiang University