Low-Frequency Broadband Bandgap of a Tunable Metamaterial Beam with Electromagnetic Resonators: Numerical and Experimental Study

Xinlei Fan, Xiaochen Mao, Youheng Dong, Minqiang Shao, Lifeng Wang, Jianghai Wu · World Scientific Pub Co Pte Ltd · 2026

This study explores a tunable metamaterial beam that achieves low-frequency broadband bandgap broadening through electromagnetic resonators.

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Plain English summary

The paper investigates a metamaterial beam structure that incorporates tunable electromagnetic resonance units. By adjusting the voltage of these resonators, the researchers can control the bandgaps of the beam, allowing for a tunable low-frequency broadband bandgap. The study includes both numerical modeling and experimental validation of the findings.

Why this matters

This research is significant as it enhances the understanding of how to design metamaterials with adjustable properties, which can lead to advancements in various applications such as vibration control and sound insulation. The ability to tune the bandgap could have implications for improving material performance in engineering and construction.

Key findings

  • Integration of tunable electromagnetic resonators into a metamaterial beam structure.
  • Establishment of dispersion behavior and wave transmittance characteristics.
  • Control of bandgaps achieved by adjusting the voltage of the EMRs.
  • Multi-frequency coupling among resonators through different control voltages.
  • Experimental validation of numerical results.

What's new

The study introduces a method for broadening low-frequency bandgaps in metamaterials through tunable electromagnetic resonators.

Limitations

The abstract does not specify the range of frequencies tested or the specific applications of the findings.

Commercial context

The abstract does not provide information on commercial applications or readiness.

Publication

Publisher
World Scientific Pub Co Pte Ltd
Publication date
February 25, 2026
Research type
Paper

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Method note: Summaries and ratings on this page are generated by AI from the abstract only. Read the original paper for full context. · Model: gpt-4o-mini-2024-07-18