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ARTICLES

Design of programmable beam splitting metasurface

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Pages 1495-1508 | Received 03 May 2023, Accepted 08 Sep 2023, Published online: 15 Sep 2023
 

Abstract

Metasurface has been applied as one critical platform for electromagnetic modulation devices. Here, a programmable metasurface loaded with positive-intrinsic negative (PIN) diodes is proposed to realize dynamic switching of arbitrary multi-beam. Furthermore, the multi-beam coding sequence is optimized by a genetic algorithm (GA) to achieve dual- to nine-beam with different scattering directions. As a proof of concept, a programmable metasurface prototype that operates around 8 GHz is designed and fabricated to be tested in far-field measurements. The beam splitter has been verified by theoretical analysis and numerical simulation to have a power efficiency of over 70%. In the measurement system, multi-beam splitting phenomena are obtained using DC control of the PIN diodes “on” and “off”, which is consistent with the simulation results. The proposed beam splitter can be designed with real-time multi-beam switching and intelligently provides coding sequences with multiple directive angles, thus providing potential benefits for next-generation antennas.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability

Data underlying the results presented in this paper are available from the authors upon reasonable request.

Additional information

Funding

This work was supported by National Natural Science Foundation of China [grant number: 12273012].

Notes on contributors

Shaochen Li

Li Shaochen, College of Information Technology, Nanjing Forestry University, Nanjing, China.

Teng Yan

Teng Yan, College of Information Technology, Nanjing Forestry University, Nanjing, China.

Xiao Yuhua

Xiao Yuhua, College of Information Technology, Nanjing Forestry University, Nanjing, China.

Li Chun

Li Chun, College of Information Technology, Nanjing Forestry University, Nanjing, China.

Bian Borui

Bian Borui, College of Information Technology, Nanjing Forestry University, Nanjing, China.

Juan Yue

Juan Yue, College of Information Technology, Nanjing Forestry University, Nanjing, China.

Jiang Ling

Jiang Ling* received the B.E. degree from Central China Normal University, Wuhan, China, in 2001, and the Ph.D. degree from Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing, China, in 2007. She is currently a Professor at the College of Information Technology, Nanjing Forestry University, Nanjing, China. Her research interests include Electromagnetic Metamaterials, artificial intelligence and machine learning algorithms and terahertz spectroscopy and imaging applications. e-mail: [email protected]

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