Meta-lens for acoustic concentration and enhanced sensing via transformation acoustics
Abstract
Detecting weak acoustic signals requires broadband energy concentration, but the acoustic power coupled into a device can be strongly curtailed by impedance mismatch at the inlet. Here, we develop a transformation-acoustics-based acoustic meta-lens in which a rectangular virtual domain is mapped to a trapezoidal physical domain, directing incident energy toward a narrow output aperture. In contrast to an air-filled trapezoidal horn with the same outer envelope, the meta-lens reshapes the wavefront through a spatially varying anisotropic mass-density tensor and an equivalent bulk modulus. A cubic-polynomial transition layer is introduced at the inlet to bridge the parameter jump between air and the anisotropic equivalent medium. Finite-element simulations from 200 to 3,000 Hz show positive sound transmission gain for the original design, with a mean value of 3.582 dB. With the transition layer, the mean gain increases to 5.470 dB, the minimum gain rises from 2.695 dB to 3.672 dB, and the mean inlet reflection coefficient decreases from 0.5644 to 0.3239, corresponding to a reduction of 42.6%. A genetic algorithm optimization of the lens length, inlet width, outlet width, and transition-layer thickness further increases the maximum gain from approximately 6.54 dB to 7.36 dB and the minimum gain from approximately 3.67 dB to 4.14 dB. These results indicate that inlet impedance grading and geometric optimization can work together to provide more robust broadband acoustic concentration for weak-signal sensing.
Copyright (c) 2026 Botao Yang, Li Cai, KunSheng Xing, Shixin Yu, Huajie Hong

This work is licensed under a Creative Commons Attribution 4.0 International License.
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