Air-Coupled Ultrasonic Arrays for Assessment of Pipe Internal Geometry and Surface Condition.

This article explores what useful information can be retrieved from pipeline interiors using an air-coupled ultrasonic array. Experiments are performed using an array, custom array controller, and supporting electronics controlled by a Raspberry Pi 4, mounted on board a crawler robot. A 64-transducer 40-kHz array configuration is selected based on uniformity of imaging amplitude over the circumference of the pipe wall. Testing revealed joints between pipe sections could be imaged at high amplitude, and that angular displacement between sections produced a different response to a properly aligned joint, potentially enabling detection of faulty joints. The surface roughness of some pipes also provides enough backscatter to be imaged, which is useful for detecting regions of corrosion. It was also found that reflections from the pipe wall in the plane of the array allow imaging of the wall shape. This can indicate the presence of junctions, as well as detect ovality to within 1%. These in-plane wall reflections were also found to be a source of low-amplitude coherent noise throughout the imaging domain, which is of similar amplitude to small (< 10 mm) through-holes in the pipe wall.

Envelope correction for shear-longitudinal collinear wave mixing to extract absolute nonlinear acoustic parameters.

This paper addresses the effect of the excitation envelope on the generated nonlinear resonant signal (NRS) for collinear wave mixing of shear and longitudinal waves. The aim is to explore how the absolute material nonlinearity can be extracted accurately for any enveloped sinusoidal excitation signal. A finite difference time domain (FDTD) model was built to simulate the effect of input waveforms on the NRS. A change in the measured nonlinearity was seen as the input waveforms were changed from rectangular to Hanning windowed tone burst. The required waveform correction was derived theoretically and validated against the FDTD simulation. Experimental measurements were carried out for different waveforms at several input amplitudes, demonstrating its influence over the NRS. The theoretically derived correction factor, which is required to map the small NRS to the rectangular tone burst resonant amplitude, was validated experimentally. The correction was then used to extract one the fundamental Murnaghan constant (m). Comparatively, Hanning tone burst inputs showed lower variance in the extracted material property due to better control of the frequency bandwidth, relative to that of the transducers. This opens the opportunity to using Hanning windowed tone burst inputs reliably for the measurement of the absolute nonlinearity parameter and m through collinear shear-longitudinal wave mixing.

Acoustic Trapping: An Emerging Tool for Microfabrication Technology.

The high throughput deposition of microscale objects with precise spatial arrangement represents a key step in microfabrication technology. This can be done by creating physical boundaries to guide the deposition process or using printing technologies; in both approaches, these microscale objects cannot be further modified after they are formed. The utilization of dynamic acoustic fields offers a novel approach to facilitate real-time reconfigurable miniaturized systems in a contactless manner, which can potentially be used in physics, chemistry, biology, as well as materials science. Here, the physical interactions of microscale objects in an acoustic pressure field are discussed and how to fabricate different acoustic trapping devices and how to tune the spatial arrangement of the microscale objects are explained. Moreover, different approaches that can dynamically modulate microscale objects in acoustic fields are presented, and the potential applications of the microarrays in biomedical engineering, chemical/biochemical sensing, and materials science are highlighted alongside a discussion of future research challenges.

Ultrasound modulates neuronal potassium currents via ionotropic glutamate receptors.

BACKGROUND: Focused ultrasound stimulation (FUS) has the potential to provide non-invasive neuromodulation of deep brain regions with unparalleled spatial precision. However, the cellular and molecular consequences of ultrasound stimulation on neurons remains poorly understood. We previously reported that ultrasound stimulation induces increases in neuronal excitability that persist for hours following stimulation in vitro. In the present study we sought to further elucidate the molecular mechanisms by which ultrasound regulates neuronal excitability and synaptic function. OBJECTIVES: To determine the effect of ultrasound stimulation on voltage-gated ion channel function and synaptic plasticity. METHODS: Primary rat cortical neurons were exposed to a 40 s, 200 kHz pulsed ultrasound stimulus or sham-stimulus. Whole-cell patch clamp electrophysiology, quantitative proteomics and high-resolution confocal microscopy were employed to determine the effects of ultrasound stimulation on molecular regulators of neuronal excitability and synaptic function. RESULTS: We find that ultrasound exposure elicits sustained but reversible increases in whole-cell potassium currents. In addition, we find that ultrasound exposure activates synaptic signalling cascades that result in marked increases in excitatory synaptic transmission. Finally, we demonstrate the requirement of ionotropic glutamate receptor (AMPAR/NMDAR) activation for ultrasound-induced modulation of neuronal potassium currents. CONCLUSION: These results suggest specific patterns of pulsed ultrasound can induce contemporaneous enhancement of both neuronal excitability and synaptic function, with implications for the application of FUS in experimental and therapeutic settings. Further study is now required to deduce the precise molecular mechanisms through which these changes occur.

Dynamic patterning of microparticles with acoustic impulse control.

This paper describes the use of impulse control of an acoustic field to create complex and precise particle patterns and then dynamically manipulate them. We first demonstrate that the motion of a particle in an acoustic field depends on the applied impulse and three distinct regimes can be identified. The high impulse regime is the well established mode where particles travel to the force minima of an applied continuous acoustic field. In contrast acoustic field switching in the low impulse regime results in a force field experienced by the particle equal to the time weighted average of the constituent force fields. We demonstrate via simulation and experiment that operating in the low impulse regime facilitates an intuitive and modular route to forming complex patterns of particles. The intermediate impulse regime is shown to enable more localised manipulation of particles. In addition to patterning, we demonstrate a set of impulse control tools to clear away undesired particles to further increase the contrast of the pattern against background. We combine these tools to create high contrast patterns as well as moving and re-configuring them. These techniques have applications in areas such as tissue engineering where they will enable complex, high fidelity cell patterns.

Tissue Engineering Cartilage with Deep Zone Cytoarchitecture by High-Resolution Acoustic Cell Patterning.

The ultimate objective of tissue engineering is to fabricate artificial living constructs with a structural organization and function that faithfully resembles their native tissue counterparts. For example, the deep zone of articular cartilage possesses a distinctive anisotropic architecture with chondrocytes organized in aligned arrays ≈1-2 cells wide, features that are oriented parallel to surrounding extracellular matrix fibers and orthogonal to the underlying subchondral bone. Although there are major advances in fabricating custom tissue architectures, it remains a significant technical challenge to precisely recreate such fine cellular features in vitro. Here, it is shown that ultrasound standing waves can be used to remotely organize living chondrocytes into high-resolution anisotropic arrays, distributed throughout the full volume of agarose hydrogels. It is demonstrated that this cytoarchitecture is maintained throughout a five-week course of in vitro tissue engineering, producing hyaline cartilage with cellular and extracellular matrix organization analogous to the deep zone of native articular cartilage. It is anticipated that this acoustic cell patterning method will provide unprecedented opportunities to interrogate in vitro the contribution of chondrocyte organization to the development of aligned extracellular matrix fibers, and ultimately, the design of new mechanically anisotropic tissue grafts for articular cartilage regeneration.

Building programmable multicompartment artificial cells incorporating remotely activated protein channels using microfluidics and acoustic levitation.

Intracellular compartments are functional units that support the metabolism within living cells, through spatiotemporal regulation of chemical reactions and biological processes. Consequently, as a step forward in the bottom-up creation of artificial cells, building analogous intracellular architectures is essential for the expansion of cell-mimicking functionality. Herein, we report the development of a droplet laboratory platform to engineer complex emulsion-based, multicompartment artificial cells, using microfluidics and acoustic levitation. Such levitated models provide free-standing, dynamic, definable droplet networks for the compartmentalisation of chemical species. Equally, they can be remotely operated with pneumatic, heating, and magnetic elements for post-processing, including the incorporation of membrane proteins; alpha-hemolysin; and mechanosensitive channel of large-conductance. The assembly of droplet networks is three-dimensionally patterned with fluidic input configurations determining droplet contents and connectivity, whilst acoustic manipulation can be harnessed to reconfigure the droplet network in situ. The mechanosensitive channel can be repeatedly activated and deactivated in the levitated artificial cell by the application of acoustic and magnetic fields to modulate membrane tension on demand. This offers possibilities beyond one-time chemically mediated activation to provide repeated, non-contact, control of membrane protein function. Collectively, this expands our growing capability to program and operate increasingly sophisticated artificial cells as life-like materials.

Ultrasonic Nondestructive Characterization of Blockages and Defects in Underground Pipes.

This article explores the use of a 40-kHz air-coupled ultrasonic array in detecting and imaging blockages and defects in buried pipes with 17-26 wavelengths in diameter at short ranges (approximately 20-60 wavelengths). In particular, the imaging performance of arrays with different numbers of transducers is quantified and compared to establish how many are required for adequate performance. Even low numbers of transducers (<25) are capable of producing -6-dB contours of blockages that match reference images to within 95% by restricting the aperture to maintain element density. However, doing so also limits the resolving power, so arrays with more transducers ultimately image better by having great enough density even at larger apertures. Using <25 transducers also gives a poor contrast ratio of features above background noise (as low as 2), resulting in low tolerance for detection and producing unusable images in some cases. More robust performance is achieved with larger numbers of transducers, which achieves sufficient contrast. All images of planar objects feature a low-amplitude band due to interference between direct reflections and reflections via the pipe wall, which was verified by comparison to simulation. When tested in larger pipes in a deployment case, the low-amplitude band was notably larger but was found to decrease in size at longer ranges.

Moth wings as sound absorber metasurface.

In noise control applications, a perfect metasurface absorber would have the desirable traits of not only mitigating unwanted sound, but also being much thinner than the wavelengths of interest. Such deep-subwavelength performance is difficult to achieve technologically, yet moth wings, as natural metamaterials, offer functionality as efficient sound absorbers through the action of the numerous resonant scales that decorate their wing membrane. Here, we quantify the potential for moth wings to act as a sound-absorbing metasurface coating for acoustically reflective substrates. Moth wings were found to be efficient sound absorbers, reducing reflection from an acoustically hard surface by up to 87% at the lowest frequency tested (20 kHz), despite a thickness to wavelength ratio of up to 1/50. Remarkably, after the removal of the scales from the dorsal surface the wing's orientation on the surface changed its absorptive performance: absorption remains high when the bald wing membrane faces the sound but breaks down almost completely in the reverse orientation. Numerical simulations confirm the strong influence of the air gap below the wing membrane but only when it is adorned with scales. The finding that moth wings act as deep-subwavelength sound-absorbing metasurfaces opens the door to bioinspired, high-performance sound mitigation solutions.

Strategies for guided acoustic wave inspection using mobile robots.

Continuous non-destructive monitoring of large-scale structures is extremely challenging with traditional manual inspections. In this paper, we explore possible strategies that a collection of inspection robots could adopt to address this challenge. We envision the continuous inspection of a plate performed by multiple robots or a single robot that combines measurements from multiple locations. The robots use guided ultrasonic waves to interrogate a localized region for defects such as cracking or corrosion. In the detection stage, the receiver operating characteristic defines a detection zone in which a defect is thought to be present. In the localization stage, further measurements are made to locate the defect within this zone to a certain accuracy. We then address the question of what additional measurements are needed to achieve a given level of performance in the presence of uncertainty in robot locations? We explore this problem with Monte Carlo simulations that reveal the compromise between number of robots and performance in terms of defect location accuracy. In an experimental validation example on an aluminium plate, we show that six measurements arranged in a pentagon with a central measurement point leads to localization errors of similar magnitude to the uncertainty in sensor location.

Ultrasonic Defect Characterization Using the Scattering Matrix: A Performance Comparison Study of Bayesian Inversion and Machine Learning Schemas.

Accurate defect characterization is desirable in the ultrasonic nondestructive evaluation as it can provide quantitative information about the defect type and geometry. For defect characterization using ultrasonic arrays, high-resolution images can provide the size and type information if a defect is relatively large. However, the performance of image-based characterization becomes poor for small defects that are comparable to the wavelength. An alternative approach is to extract the far-field scattering coefficient matrix from the array data and use it for characterization. Defect characterization can be performed based on a scattering matrix database that consists of the scattering matrices of idealized defects with varying parameters. In this article, the problem of characterizing small surface-breaking notches is studied using two different approaches. The first approach is based on the introduction of a general coherent noise model, and it performs characterization within the Bayesian framework. The second approach relies on a supervised machine learning (ML) schema based on a scattering matrix database, which is used as the training set to fit the ML model exploited for the characterization task. It is shown that convolutional neural networks (CNNs) can achieve the best characterization accuracy among the considered ML approaches, and they give similar characterization uncertainty to that of the Bayesian approach if a notch is favorably oriented. The performance of both approaches varied for unfavorably oriented notches, and the ML approach tends to give results with higher variance and lower biases.

Transient ultrasound stimulation has lasting effects on neuronal excitability.

BACKGROUND: Transcranial ultrasound stimulation can acutely modulate brain activity, but the lasting effects on neurons are unknown. OBJECTIVE: To assess the excitability profile of neurons in the hours following transient ultrasound stimulation. METHODS: Primary rat cortical neurons were stimulated with a 40 s, 200 kHz pulsed ultrasound stimulation or sham-stimulation. Intrinsic firing properties were investigated through whole-cell patch-clamp recording by evoking action potentials in response to somatic current injection. Recordings were taken at set timepoints following ultrasound stimulation: 0-2 h, 6-8 h, 12-14 h and 24-26 h. Transmission electron microscopy was used to assess synaptic ultrastructure at the same timepoints. RESULTS: In the 0-2 h window, neurons stimulated with ultrasound displayed an increase in the mean frequency of evoked action potentials of 32% above control cell levels (p = 0.023). After 4-6 h this increase was measured as 44% (p = 0.0043). By 12-14 h this effect was eliminated and remained absent 24-26 h post-stimulation. These changes to action potential firing occurred in conjunction with statistically significant differences between control and ultrasound-stimulated neurons in action potential half-width, depolarisation rate, and repolarisation rate, that were similarly eliminated by 24 h following stimulation. These effects occurred in the absence of alterations to intrinsic membrane properties or synaptic ultrastructure. CONCLUSION: We report that stimulating neurons with 40 s of ultrasound enhances their excitability for up to 8 h in conjunction with modifications to action potential kinetics. This occurs in the absence of major ultrastructural change or modification of intrinsic membrane properties. These results can inform the application of transcranial ultrasound in experimental and therapeutic settings.

Moth wings are acoustic metamaterials.

Metamaterials assemble multiple subwavelength elements to create structures with extraordinary physical properties (1-4). Optical metamaterials are rare in nature and no natural acoustic metamaterials are known. Here, we reveal that the intricate scale layer on moth wings forms a metamaterial ultrasound absorber (peak absorption = 72% of sound intensity at 78 kHz) that is 111 times thinner than the longest absorbed wavelength. Individual scales act as resonant (5) unit cells that are linked via a shared wing membrane to form this metamaterial, and collectively they generate hard-to-attain broadband deep-subwavelength absorption. Their collective absorption exceeds the sum of their individual contributions. This sound absorber provides moth wings with acoustic camouflage (6) against echolocating bats. It combines broadband absorption of all frequencies used by bats with light and ultrathin structures that meet aerodynamic constraints on wing weight and thickness. The morphological implementation seen in this evolved acoustic metamaterial reveals enticing ways to design high-performance noise mitigation devices.

Comparison of Time Domain and Frequency-Wavenumber Domain Ultrasonic Array Imaging Algorithms for Non-Destructive Evaluation.

Ultrasonic array imaging algorithms have been widely developed and used for non-destructive evaluation (NDE) in the last two decades. In this paper two widely used time domain algorithms are compared with two emerging frequency domain algorithms in terms of imaging performance and computational speed. The time domain algorithms explored here are the total focusing method (TFM) and plane wave imaging (PWI) and the frequency domain algorithms are the wavenumber algorithm and Lu's frequency-wavenumber domain implementation of PWI. In order to make a fair comparison, each algorithm was first investigated to choose imaging parameters leading to overall good imaging resolution and signal-to-noise-ratio. To reflect the diversity of samples encountered in NDE, the comparison is made using both a low noise material (aluminium) and a high noise material (copper). It is shown that whilst wavenumber and frequency domain PWI imaging algorithms can lead to fast imaging, they require careful selection of imaging parameters.

Chemical Information Exchange in Organized Protocells and Natural Cell Assemblies with Controllable Spatial Positions.

An ultrasound-based platform is established to prepare homogenous arrays of giant unilamellar vesicles (GUVs) or red blood cell (RBCs), or hybrid assemblies of GUV/RBCs. Due to different responses to the modulation of the acoustic standing wave pressure field between the GUVs and RBCs, various types of protocell/natural cell hybrid assemblies are prepared with the ability to undergo reversible dynamic reconfigurations from vertical to horizontal alignments, or from 1D to 2D arrangements. A two-step enzymatic cascade reaction between transmitter glucose oxidase-containing GUVs and peroxidase-active receiver RBCs is used to implement chemical signal transduction in the different hybrid micro-arrays. Taken together, the obtained results suggest that the ultrasound-based micro-array technology can be used as an alternative platform to explore chemical communication pathways between protocells and natural cells, providing new opportunities for bottom-up synthetic biology.

Thoracic scales of moths as a stealth coating against bat biosonar.

Many moths are endowed with ultrasound-sensitive ears that serve the detection and evasion of echolocating bats. Moths lacking such ears could still gain protection from bat biosonar by using stealth acoustic camouflage, absorbing sound waves rather than reflecting them back as echoes. The thorax of a moth is bulky and hence acoustically highly reflective. This renders it an obvious target for any bat. Much of the thorax of moths is covered in hair-like scales, the layout of which is remarkably similar in structure and arrangement to natural fibrous materials commonly used in sound insulation. Despite this structural similarity, the effect of thorax scales on moth echoes has never been characterized. Here, we test whether and how moth thorax scales function as an acoustic absorber. From tomographic echo images, we find that the thin layer of thoracic scales of diurnal butterflies affects the strength of ultrasound echoes from the thorax very little, while the thorax scales of earless moths absorbs an average of 67 ± 9% of impinging ultrasonic sound energy. We show that the thorax scales of moths provide acoustic camouflage by acting as broadband (20-160 kHz) stealth coating. Modelling results suggest the scales are acting as a porous sound absorber; however, the thorax scales of moths achieve a considerably higher absorption than technical fibrous porous absorbers with the same structural parameters. Such scales, despite being thin and lightweight, constitute a broadband, multidirectional and efficient ultrasound absorber that reduces the moths' detectability to hunting bats and gives them a survival advantage.

Artificial morphogen-mediated differentiation in synthetic protocells.

The design and assembly of artificial protocell consortia displaying dynamical behaviours and systems-based properties are emerging challenges in bottom-up synthetic biology. Cellular processes such as morphogenesis and differentiation rely in part on reaction-diffusion gradients, and the ability to mimic rudimentary aspects of these non-equilibrium processes in communities of artificial cells could provide a step to life-like systems capable of complex spatiotemporal transformations. Here we expose acoustically formed arrays of initially identical coacervate micro-droplets to uni-directional or counter-directional reaction-diffusion gradients of artificial morphogens to induce morphological differentiation and spatial patterning in single populations of model protocells. Dynamic reconfiguration of the droplets in the morphogen gradients produces a diversity of membrane-bounded vesicles that are spontaneously segregated into multimodal populations with differentiated enzyme activities. Our results highlight the opportunities for constructing protocell arrays with graded structure and functionality and provide a step towards the development of artificial cell platforms capable of multiple operations.

Acoustic deformation for the extraction of mechanical properties of lipid vesicle populations.

We use an ultrasonic standing wave to simultaneously trap and deform thousands of soft lipid vesicles immersed in a liquid solution. In our device, acoustic radiation stresses comparable in magnitude to those generated in optical stretching devices are achieved over a spatial extent of more than ten acoustic wavelengths. We solve the acoustic scattering problem in the long-wavelength limit to obtain the radiation stress. The result is then combined with thin-shell elasticity theory to form expressions that relate the deformed geometry to the applied acoustic field intensity. Using observation of the deformed geometry and this model, we rapidly extract mechanical properties, such as the membrane Young's modulus, from populations of lipid vesicles.

Grain Scattering Noise Modeling and Its Use in the Detection and Characterization of Defects Using Ultrasonic Arrays.

In the field of ultrasonic array imaging for non-destructive testing (NDT), material structural noise caused by grain scattering is one of the main sources of error when characterizing defects that are found in the polycrystalline materials. The existence of grains can also severely affect the detection performance of ultrasonic testing, making small defects indistinguishable from the grain indications due to ultrasonic attenuation and backscatter. This paper proposes a model in which the statistical distribution of the defect data is obtained from different realizations of the grain structure. This statistical distribution, termed the defect+grains model in this paper, is shown to contain information that is needed for detection and characterization of defects. Hence, given a specific measurement configuration, the characterization result can be obtained by constructing a defect+grains model based on the multiple realizations of each possible defect and calculating their probability. The detection, classification, and sizing accuracy are shown to be predictable by quantifying the probabilities that an experimentally measured defect matches the different defect+grains models. This defect+grains modeling approach gives insight into the detection/characterization problem, leading to an evaluation of the fundamental limits of the achievable inspection performance.