Topological acoustics is an emerging field that lies at the intersection of condensed matter physics, mechanical structural design and acoustics engineering. It explores the design and construction of novel artificial structures, such as acoustic metamaterials and phononic crystals, to manipulate sound waves robustly, taking advantage of topological protection. Early work on topological acoustics was limited to duplicating topological phases that have been understood in condensed matter systems, but recent advances have shifted to exploring new topological concepts that are difficult to realize in other physical systems, such as various topological semimetal phases, and topological phases associated with Floquet engineering, fragile topology, non-Hermiticity and synthetic dimensions. These developments demonstrate the unique advantages of topological acoustic systems and their role in developing topological physics. In this Review, we survey the fundamental mechanisms, basic designs and practical realizations of topological phases in acoustic systems and provide an overview of future directions and potential applications. The introduction of topology into acoustic platforms enables robust sound control. This Review discusses the fundamental mechanisms, basic designs, practical realizations and promising future directions for topological acoustic systems.
The book deals with sound propagation and scattering in moving inhomogeneous media. Although the theories presented in this book are much broader in scope, the main interest lies in sound propagation in the atmospheric boundary layer. Some sections are devoted to particularities of underwater sound propagation. The book can be roughly divided in 3 parts. In a first part, the fundamentals of acoustics in moving media with deterministic inhomogeneities (such as temperature profiles) are discussed. The second part adds the effects of propagation medium randomness (turbulence). A last part deals with numerical approaches to implement some of the presented equations and theories.
The reduction of noises, achieved through absorption, is of paramount importance to the well‐being of both humans and machines. Lattice structures, defined as architectured porous solids arranged in repeating patterns, are emerging as advanced sound‐absorbing materials. Their immense design freedom allows for customizable pore morphology and interconnectivity, enabling the design of specific absorption properties. Thus far, the sound absorption performance of various types of lattice structures are studied and they demonstrated favorable properties compared to conventional materials. Herein, this review gives a thorough overview on the current research status, and characterizations for lattice structures in terms of acoustics is proposed. Till date, there are four main sound absorption mechanisms associated with lattice structures. Despite their complexity, lattice structures can be accurately modelled using acoustical impedance models that focus on critical acoustical geometries. Four defining features: morphology, relative density, cell size, and number of cells, have significant influences on the acoustical geometries and hence sound wave dissipation within the lattice. Drawing upon their structural‐property relationships, a classification of lattice structures into three distinct types in terms of acoustics is proposed. It is proposed that future attentions can be placed on new design concepts, advanced materials selections, and multifunctionalities.
As artificial intelligence (AI) advances, it is critical to give conventional electronics the capacity to “think,” “analyze,” and “advise.” The need for intelligent, self-powered devices has increased due to recent significant developments in the computer field, namely, in the fields of AI and machine learning (ML). The use of nanogenerators in the area of acoustics is examined in this Review, with an emphasis on how they might be integrated with ML and AI. Innovative energy-harvesting devices called nanogenerators are able to produce electrical power from outside sources, such as vibrations in the air or mechanical movements. The study examines a number of acoustic applications for nanogenerators, such as energy harvesting, sound detection, noise monitoring, and acoustic sensing. Furthermore, the research highlights how AI and ML techniques enhance the performance of nanogenerators and enable more efficient acoustic applications through data analysis and model training. At the end of this Review, the future development prospects of nanogenerators based on AI and ML were discussed.
This study proposes a framework for incorporating wavenumber-domain acoustic reflection coefficients into sound field analysis to characterize direction-dependent material reflection and scattering phenomena. The reflection coefficient is defined as the amplitude ratio between incident and reflected waves for each propagation direction and is estimated from spatial Fourier transforms of the incident and reflected sound fields. The resulting wavenumber-domain reflection coefficients are converted into an acoustic admittance representation that is directly compatible with numerical methods such as the Boundary Element Method (BEM), enabling simulation of reflections beyond simple specular components. Unlike conventional extended reaction models, the proposed approach avoids explicit modeling of the material interior. This significantly reduces computational cost while allowing direct use of measured data, empirical models, or user-defined directional reflection characteristics. The validity of the proposed formulation was previously demonstrated by the authors through two-dimensional sound field simulations, in which accurate reproduction of direction-dependent reflection behavior was confirmed. In the present work, the framework is extended to three-dimensional analysis, demonstrating its applicability to more realistic and complex acoustic environments. The proposed approach provides a practical and flexible tool for simulating direction-dependent acoustic reflections and scattering, with potential applications in architectural acoustics, material characterization, and noise control.
Shoichi Koyama, Enzo De Sena, Prasanga Samarasinghe
et al.
The study of spatial audio and room acoustics aims to create immersive audio experiences by modeling the physics and psychoacoustics of how sound behaves in space. In the long history of this research area, various key technologies have been developed based both on theoretical advancements and practical innovations. We highlight historical achievements, initiative activities, recent advancements, and future outlooks in the research area of spatial audio recording and reproduction, and room acoustic simulation, modeling, analysis, and control.
Hunter J. Pratt, Logan T. Mathews, Tyce W. Olaveson
et al.
A sound power spectrum analysis has been conducted on a T-7A-installed F404 engine, for operating conditions spanning intermediate thrust to afterburner. From free-field pressure spectra at microphone arc arrays with radii of 38 and 76 m, sound power level spectra are calculated from surface integrals and assumed axisymmetric radiation. The spectral peak-frequency region, from ∼100–500 Hz, broadens with increasing engine conditions. When the power level spectra are plotted with Strouhal number, the spectral peak decreases with engine condition. Comparing this decrease with rocket data suggests that military jet noise radiation is becoming more rocket-like, especially at afterburner conditions.
This review comprehensively examines recent advances in ultrasound-enhanced heat transfer, a promising active cooling technology for high-heat-flux electronic devices. It systematically analyzes the fundamental mechanisms: thermal effect, acoustic cavitation, acoustic streaming, acoustic fountain and atomization. Among them, acoustic cavitation and acoustic streaming are identified as the two primary mechanisms for enhancing heat transfer. In addition, the review discusses their roles in improving heat transfer in single-phase flow, pool boiling, forced convective boiling, and heat exchanger. Key influencing parameters, such as ultrasonic frequency, power, transducer configuration, flow rate, heat flux, and subcooling are critically evaluated. The synergistic effects of combining ultrasound with nanofluids, channel structure, and other active methods are also highlighted. Numerical modeling approaches, including bubble dynamics and multiphysics simulations, are reviewed for their potential in exploring underlying mechanisms and optimizing system performance. Finally, current challenges and future research directions are outlined, with a focus on multiscale coupling, energy efficiency, and adaptability under extreme conditions.
Hossein Haghi, Mahshid Yaali, Agata A. Exner
et al.
This study presents an experimental investigation of the influence of MB concentration on the resonance frequency of lipid-coated microbubbles (MBs). Expanding on theoretical models and numerical simulations from previous research, this work experimentally investigates the effect of MB size on the rate of resonance frequency increase with concentration, a phenomenon observed across MBs with two different lipid compositions: propylene glycol (PG) and propylene glycol and glycerol (PGG). Employing a custom-designed ultrasound attenuation measurement setup, we measured the frequency-dependent attenuation of MBs, isolating MBs based on size to generate distinct monodisperse sub-populations for analysis. The resonance frequency of MBs was determined by identifying the attenuation peak in the broadband attenuation ultrasound attenuation measurements. Our experimental findings confirm that larger MBs (≈2.1μm) demonstrate a more significant shift in resonance frequency (≈ 5 MHz, ≈ 40%) as a function of MB concentration. In contrast, smaller MBs (≈1.3μm) show a minor shift in the resonant frequency (≈ 1.8 MHz, ≈ 8%), underlining the importance of size in determining acoustic behavior compared to changes in the lipid shell properties. Additionally, we observed that resonance frequency increase with concentration reaching a saturation point at higher concentrations. This plateau occurs at higher concentrations for larger MBs (≈2.1μm), while smaller MBs (≈1.6μm and ≈1.3μm) reach this saturation point at lower concentrations. Furthermore, the study highlights the small effect of bubble–bubble interactions on the resonance frequency of MB populations, particularly at lower MB concentrations and for smaller MBs. This insight is important for applications utilizing MB clusters, such as contrast-enhanced ultrasound imaging and MB-mediated therapies. While both size and lipid shell composition influence resonance frequency, MB size has a more significant effect. In conclusion, our findings affirm the need to consider both MB size and concentration when utilizing MBs for clinical and industrial ultrasonic applications.
M. Eric Cui, Emilie Verno-Lavigne, Shreshth Saxena
et al.
To extend the assessment of listening effort beyond a sound booth, we validated mobile eye-tracking glasses (Pupil Labs Neon; Pupil Labs, Berlin, Germany) by comparing them to a stationary system (Eyelink DUO; SR Research Ltd., Ottawa, Canada) in a controlled environment. We recorded eye movements, pupil size, and head movements from 26 young adults during a speech-in-noise task. When listening conditions became challenging, we observed reduced gaze dispersion and increased pupil sizes of similar magnitude from both devices, in addition to reduced head movements recorded solely by the mobile device. These findings suggest that mobile eye-trackers reliably capture listening effort, paving the path towards assessments in daily settings.
The strangulation of intestinal obstruction (IO) presents challenges in the assessment of disease progression and surgical decision-making. Intraoperatively, an accurate evaluation of the status of the IO is critical for determining the extent of surgical resection. Dual-modality ultrasound/photoacoustic tomography (US/PAT) imaging has the potential to provide spatially resolved tissue oxygen saturation (SO₂), serving as a valuable marker for IO diagnosis. In this study, US/PAT was utilized for imaging rat models of IO, with the data used for reconstruction, statistical analysis, and distribution evaluation. Results showed that SO₂ decreased with increasing strangulation severity. Notably, the kurtosis and skewness of the SO₂ distribution outperformed SO₂ itself in diagnosis, as they more effectively capture the heterogeneity of SO₂ distribution. Kurtosis reflects distribution concentration, while skewness measures asymmetry, both achieving areas under the receiver operating characteristic curve (AUROC) of 0.969. In conclusion, US/PAT offers a rapid and convenient method for assessing strangulation in IO.
The process conditions, content of ingredients and in vitro antioxidant activity of Piper nigrum L. polysaccharides (PNP) by ultrasound-assisted extraction (UAE) and PNP by hot water extraction (HWE) were compared. The findings demonstrated that the UAE produced greater polysaccharides content (74.41 %) with the yield of PNP (2.9 %) than HWE. The ideal conditions were 324 W of ultrasonic power, 36 mL/g of liquid to material ratio, 70 min of ultrasonic time, and 78 °C of temperature. Structural analysis showed UAE-PNP was the α-type polysaccharides with a pyran ring structure, which were mainly neutral polysaccharides. In addition, UAE-PNP had great antioxidant activity, especially in its ability to scavenge ABTS free radicals. According to the experimental results, the UAE method was an efficient way to extract PNP. This experiment showed for the first time the structure and antioxidant activity of HWE-PNP and UAE-PNP, which provided some theoretical proof for the application of PNP in food additives and biopharmaceuticals.
Advanced biofabrication techniques can create tissue-like constructs that can be applied for reconstructive surgery or as in vitro three-dimensional (3D) models for disease modeling and drug screening. While various biofabrication techniques have recently been widely reviewed in the literature, acoustics-based technologies still need to be explored. The rapidly increasing number of publications in the past two decades exploring the application of acoustic technologies highlights the tremendous potential of these technologies. In this review, we contend that acoustics-based methods can address many limitations inherent in other biofabrication techniques due to their unique advantages: noncontact manipulation, biocompatibility, deep tissue penetrability, versatility, precision in-scaffold control, high-throughput capabilities, and the ability to assemble multilayered structures. We discuss the mechanisms by which acoustics directly dictate cell assembly across various biostructures and examine how the advent of novel acoustic technologies, along with their integration with traditional methods, offers innovative solutions for enhancing the functionality of organoids. Acoustic technologies are poised to address fundamental challenges in biofabrication and tissue engineering and show promise for advancing the field in the coming years.
Sagnik Majumder, Changan Chen, Ziad Al-Halah
et al.
Room impulse response (RIR) functions capture how the surrounding physical environment transforms the sounds heard by a listener, with implications for various applications in AR, VR, and robotics. Whereas traditional methods to estimate RIRs assume dense geometry and/or sound measurements throughout the environment, we explore how to infer RIRs based on a sparse set of images and echoes observed in the space. Towards that goal, we introduce a transformer-based method that uses self-attention to build a rich acoustic context, then predicts RIRs of arbitrary query source-receiver locations through cross-attention. Additionally, we design a novel training objective that improves the match in the acoustic signature between the RIR predictions and the targets. In experiments using a state-of-the-art audio-visual simulator for 3D environments, we demonstrate that our method successfully generates arbitrary RIRs, outperforming state-of-the-art methods and -- in a major departure from traditional methods -- generalizing to novel environments in a few-shot manner. Project: http://vision.cs.utexas.edu/projects/fs_rir.
Environment Sound Classification has been a well-studied research problem in the field of signal processing and up till now more focus has been laid on fully supervised approaches. Over the last few years, focus has moved towards semi-supervised methods which concentrate on the utilization of unlabeled data, and self-supervised methods which learn the intermediate representation through pretext task or contrastive learning. However, both approaches require a vast amount of unlabelled data to improve performance. In this work, we propose a novel framework called Environmental Sound Classification with Hierarchical Ontology-guided semi-supervised Learning (ECHO) that utilizes label ontology-based hierarchy to learn semantic representation by defining a novel pretext task. In the pretext task, the model tries to predict coarse labels defined by the Large Language Model (LLM) based on ground truth label ontology. The trained model is further fine-tuned in a supervised way to predict the actual task. Our proposed novel semi-supervised framework achieves an accuracy improvement in the range of 1\% to 8\% over baseline systems across three datasets namely UrbanSound8K, ESC-10, and ESC-50.
This paper summarizes our acoustic modeling efforts in the Johns Hopkins University speech recognition system for the CHiME-5 challenge to recognize highly-overlapped dinner party speech recorded by multiple microphone arrays. We explore data augmentation approaches, neural network architectures, front-end speech dereverberation, beamforming and robust i-vector extraction with comparisons of our in-house implementations and publicly available tools. We finally achieved a word error rate of 69.4% on the development set, which is a 11.7% absolute improvement over the previous baseline of 81.1%, and release this improved baseline with refined techniques/tools as an advanced CHiME-5 recipe.