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A Self-Adaptive Reconfigurable Metasurface for Electromagnetic Wave Sensing and Dynamic Reflection Control
Bo-Wen Ren1, Chu Qi1, Peixing Li1
1Department of Electrical Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong SAR, China.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|June 11, 2025
Summary
This study introduces a novel self-adaptive metasurface that autonomously adjusts wave reflection in real-time. This innovation simplifies control, reduces energy use, and lowers costs for applications in wireless communication and radar sensing.
Area of Science:
- Metasurface technology
- Electromagnetics
- Wave manipulation
Background:
- Reconfigurable metasurfaces are gaining attention.
- Existing metasurfaces require manual intervention, external sensors, or complex deep learning for functionality switching.
- These limitations hinder real-time applications and increase costs.
Purpose of the Study:
- To develop a simple, real-time self-adaptive metasurface.
- To integrate wave sensing and reconfigurable reflection capabilities.
- To eliminate the need for auxiliary detection or external controllers.
Main Methods:
- Designed a metasurface integrating sensing and reconfigurable reflection meta-atoms.
- Employed a phase comparator and lookup table for autonomous control.
- Investigated metasurfaces for adaptive wave redirection and focusing.
Main Results:
- Demonstrated effective reflection of incident waves from any direction within ±50° to the normal.
- Achieved rapid self-adaptation to changing incidence angles (up to 12°/s).
- Reported low power consumption (415 mW) and significant savings in response time, energy, and fabrication cost.
Conclusions:
- The proposed metasurface offers an autonomous, computationally simple, cost-effective, and energy-efficient solution for real-time adaptive reflection control.
- This technology opens new possibilities for wireless communication, radar sensing, and related fields.
- The system eliminates the need for external controllers and complex processing, enabling practical real-world deployment.

