Advances in Acoustic/Elastic Wave Sensing for Information Processing, Volume II

This Research Topic is Volume II of a series. The previous volume can be found here: Advances in Acoustic/Elastic Wave Sensing for Information Processing.Acoustic and elastic waves serve as rich physical carriers of information across diverse fields, from structural health monitoring and non-destructive evaluation (NDE) to biomedical diagnostics and seismic exploration. Seamlessly bridging the physical wave domain with digital processing systems relies on advanced sensing architectures that can capture, extract, and convert raw wave signals into structured, actionable intelligence. Traditional wave sensing paradigms, however, face fundamental bottlenecks: they heavily depend on dense, high-cost sensor arrays or intrusive transducers that perturb the ambient wave field. Furthermore, conventional detectors struggle with far-field subwavelength resolution, face high latency in processing massive wave datasets, and suffer severe signal distortion from material interfaces.Over the past decade, acoustic and elastic metamaterials—along with actively programmable metasurfaces—have emerged as transformative hardware platforms that redefine wave-domain information processing. By manipulating wave amplitude, phase, polarization, and spatial dispersion at the subwavelength scale, metamaterial-enabled sensing shifts the computational burden from backend digital processors directly into the physical propagation medium.Coupled with modern deep learning and physics-informed AI, metamaterial hardware enables complex spatial-frequency field encoding. This allows ultra-sparse or single-sensor setups to reconstruct multidimensional wave fields via advanced compressive sensing. Simultaneously, the field has moved beyond simple wave guiding: modern metastructures can perform real-time wave-based analog computing and function as physical neural networks. By executing mathematical operations (e.g., differentiation, integration, spatial filtering) and matrix multiplications at the speed of wave propagation, these systems achieve ultra-fast signal pre-processing with near-zero power consumption.This Research Topic aims to highlight cutting-edge advancements at the intersection of wave physics, functional metamaterials, and digital information processing. We welcome original research and review articles focusing on, but not limited to, the following topics:• Wave-Based Analog Computing & Physical Neural Networks• Active, Programmable, and Coding Metasurfaces• AI-Driven Sensing & Inverse Design• Extreme Compressive Sensing & Field Encoding• Subwavelength Imaging & Deep-Resolution Recovery• Acoustic/elastic Wave Sensing for Biomedical Applications• Non-Hermitian & Topological Wave Sensing• Advanced Impedance Matching & Super-Scattering• Metamaterial-Enabled NDE/NDT & Edge Sensing• Metamaterial-Based Multi-Modal/Parameter SensingTopic Editor Dr. Taehwa Lee is employed by Toyota Motor North America, a private company. All other Topic Editors declare no competing interests with regards to the Research Topic subject. Topic editors: Taehwa Lee, Chen Shen, Qingbo He Source: https://www.frontiersin.org/research-topics/85950/advances-in-acousticelastic-wave-sensing-for-information-processing-volume-ii