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Author Spotlight: A Stable Phantom Material for Optical and Acoustic Imaging
Published on: June 16, 2023
Intelligent Acousto-Electrical Metamaterials (IAM) for Sound Source Detection
Victor Couëdel1,2,3, Haotian Lu1,3, Jiayan Zhang1,3
1Department of Material Sciences and Engineering, University of California, Berkeley, California, USA.
Abstract:
Acoustic transducers are essential for object localization and environmental sensing. Conventional transducers rely on piezoelectric crystals, whose acoustic-electric response is fixed by the crystal lattice's inherent asymmetry and orientation. This results in static coupling behavior, necessitating bulky arrays of rigid elements with complex wiring and high computational demands for directional sensing. Here, we report a fundamentally new class of acoustic-electric coupling that emerges from topology-governed charge transport in 3D micro-architected piezoelectric metamaterials. Unlike single crystals, these architected materials exhibit dynamic, geometry-driven electromechanical responses. Acoustic waves excite multiple coupled vibration modes, enabling selective amplification, suppression, or reversal of charge flow based on the incident wave's frequency, direction, and the material's topology. This tunable, symmetry-breaking response is encoded not in the chemistry but in the architecture-representing a shift from crystal-defined to structure-programmed piezoelectricity. We further demonstrate that a single metamaterial transducer can perform frequency-dependent beam shaping without changing aperture size or requiring mechanical adjustment. Combined with machine learning and 3D printing, these intelligent acousto-electrical metamaterials (IAM) enable real-time localization of multiple moving sound sources. This approach lays the foundation for compact, adaptive, and intelligent acoustic sensing systems across a range of applications-from autonomous vehicles to medical imaging and underwater robotics.
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