Conventional ultrasonic approaches for corrosion surveillance such as large-scale C-scans and continuous localised monitoring face inherent limitations in either temporal resolution or spatial coverage. Recent advances in sensor technology and low-cost autonomous robotics enables a hybrid approach that combine their strengths. However, critical questions remain about optimising such approaches, including determining the optimal inspection intervals, spatial coverage, and number of sensors. This study presents a multi-stage framework that addresses these challenges through integrated modelling: degradation simulation for spatiotemporal evolution of component surfaces, physics-based surrogate models for ultrasonic thickness measurements, data subsampling to replicate inspection and monitoring procedures, and reliability assessments against surveillance targets. Through Monte Carlo simulations on synthesised data calibrated to field measurements, we demonstrate the potential benefits of the hybrid strategy. Results show that strategic sensor placement and periodic repositioning can enhance reliability while reducing coverage requirements and extending inspection intervals. Importantly, this framework provides quantitative guidance for corrosion surveillance planning and can be adapted to different degradation phenomena across various asset types.

A lubricant film separates metal-to-metal contacts and is critical for industrial components such as bearings, engines, and transmissions, to assure their durability and energy efficiency. The lubricant film thickness can reflect oil rheological properties and thus its degradation, while the interfacial temperature variation is mainly caused by friction heating that can reflect wear conditions. Therefore, simultaneous monitoring of these two key variables will enable comprehensive characterization of the lubrication condition, facilitating predictive maintenance of energy equipment. Traditional ultrasonic measurement techniques based on longitudinal waves have been widely employed for monitoring lubricant film thickness; however, the acoustic velocity in such methods is highly sensitive to temperature and lacks effective compensation mechanisms. This severely limits their applicability in high-precision scenarios. To address this issue, this paper proposes a hybrid ultrasonic measurement approach that employs co-located longitudinal and shear waves. Shear waves propagate only in solids and are unaffected by the lubricant film, while longitudinal waves travel through both solids and liquids. Thus, the method utilizes the longitudinal wave to estimate film thickness and the shear wave to evaluate solid temperature and infer interfacial temperature. This temperature information is then used to improve estimates of the phase of the wave that is propagating in the solid medium and the assumed acoustic velocity in the lubricating film, thereby enhancing the accuracy and robustness of thickness measurements. Experimental validation was conducted on both a heating plate and a rheometer system. The temperature experiments demonstrated the feasibility of using ultrasound to measure temperature gradients within solids. On the rheometer platform, practical lubrication conditions were simulated by adjusting the upper plate temperature, allowing for further evaluation of the shear-wave-based temperature sensing method. Experimental results confirm that the proposed method can accurately obtain interfacial temperatures and compensate for temperature-induced errors in the lubricant film thickness measurements.

Traditional phased array controllers are bulky and expensive meaning they cannot be used for SHM applications where equipment needs to be left in place for regular measurements to be made. Much of the size and cost associated with traditional array controllers arises due to the electronics architecture used for the transmission signals and receiver amplification. Removing these components is not possible when traditional excitation techniques are used. Similarly, high-voltage transmit signals are not easily switched, making channel multiplexing for the purpose of cost-reduction complicated. Conversely, coded excitation techniques can enable the construction of miniature, low-power acquisition systems that are light-weight and low-cost. This is possible due to the use of long-sequence based transmit signals that enable transmission energy to be spread over time, making low-voltage excitations capable of producing high-quality signals following appropriate processing. Furthermore, low voltage transmit signals are easily switched, which enables additional system simplification via multiplexing. Devices using this code-based architecture are therefore well suited to SHM as they can be installed in place on structures to monitor cracks online. A phased array monitoring system was built using an acquisition module designed around using coded excitation – a CA1-MUX32 from CodeAcq. This system uses <1V transmit amplitudes (in pulse-echo mode) and is of similar size to phased array probes themselves. The system was installed on a reference sample containing a notch of increasing depth and used to measure the notch size. Total Focusing Method images were acquired at regular intervals across the block. This paper presents the results of the experiments and compares the performance of the low-power coded excitation system to a standard phased array controller commonly used in lab conditions.

This study investigates the performance of established image registration methods for stitching partially overlapping ultrasonic C-scan corrosion maps, with the aim of improving data continuity in phased array ultrasonic testing (PAUT). Three popular feature detectors, KAZE, SIFT, and SURF, are evaluated alongside two extraction methods, SURF descriptor format and Histogram of Oriented Gradients (HOG), on a dataset of 1200 simulated corrosion maps with a 10 mm initial backwall thickness. Each corroded map is divided into two overlapping C-scan strips (100 x 200 pixels), simulating inspection scenarios with overlap ranging from 1 to 50 pixels and misalignments up to 20 degrees rotation. The analysis incorporates realistic acquisition imperfections, including signal noise (0-2 mm) and encoder skips. Results show that KAZE outperforms SIFT and SURF, particularly under noisy conditions, achieving stitching success rates up to 98% when overlaps exceed 10 elements. In ideal conditions, all detectors maintain high performance (90%-95%), but noise and rotational misalignment significantly degrade the results. The two extraction methods are similar for large depth variations, but when depth variation is small (<= 1 mm), SURF is more effective at small overlaps (<= 20 elements), while HOG exhibits greater robustness at larger overlaps. Among all tested inspection errors, rotational misalignment had the greatest negative impact on stitching accuracy, followed by noise, with encoder skips showing minimal effect. These findings support the integration of advanced feature-based registration techniques into PAUT data processing workflows, enabling improved corrosion mapping and defect characterisation across multiple scans.

Thermal fatigue is a damage mechanism which can occur in a range of engineering contexts. For example, high-cycle thermal fatigue (HCTF) can occur in nuclear power plant (NPP) piping where turbulent fluid mixing produces rapid, localised temperature fluctuations. If undetected, the accumulated damage may initiate cracks, as highlighted by the Civaux 1 reactor incident in 1998. Existing monitoring methods rely on external temperature sensors, but fail to capture high-frequency (1 Hz) fluctuations because the pipe wall acts as a low-pass thermal filter. A non-invasive technique for HCTF monitoring that overcomes the thermal filtering effect is desirable given the potentially deadly repercussions of cracks in NPPs. Ultrasonic velocity and attenuation are known to be sensitive to thermal fatigue. However, experimental studies to date were limited to post-fatiguing measurements. This study investigated whether thermal-fatigue-induced changes in velocity and attenuation could be detected during thermal cycling using a permanently installed transducer. Cyclic thermal transients of up to 600 degrees C were used to induce (low-cycle) thermal fatigue in three samples of austenitic stainless steel, with two taken to failure (cracking). Fatigue damage was confirmed using electron backscatter diffraction (EBSD), and shear and Rayleigh wave measurements. The ultrasonic shear velocity decreased as the number of thermal transients experienced by each sample increased, as expected. However, the relationship between the magnitude of the decrease and the number of transients was not straightforward. The attenuation increased following crack initiation; approximate to 30% and approximate to 150% for shear polarisation parallel and perpendicular to the (expected) crack direction, respectively. Further validation on a larger sample set, and under representative conditions and geometries is required. However, these results demonstrate the potential for HCTF monitoring using changes in velocity and attenuation.

Evaluating the structural integrity, operational safety, and material degradation of lithium-ion batteries has become a key concern across manufacturing (Gervilli & eacute;-Mouravieff et al. 2024; McGovern et al. 2023), maintenance (Gervilli & eacute;-Mouravieff et al. 2024; Zuo et al. 2025), and recycling processes (Zhao et al. 2025). As lithium-ion batteries are increasingly deployed in electric vehicles, aerospace systems, and stationary storage apparatus, the demand for reliable and efficient characterization tools continues to grow. Internally, these batteries exhibit complex multilayer architectures comprising stacked electrodes, separators, and current collectors, enclosed within tightly packed casing structures (McGovern et al. 2023; Wang et al. 2024). This multilayer construction governs not only their electrochemical performance but also their mechanical and acoustic behaviors, posing challenges for subsurface inspection and state identification (Gou et al. 2024; Wang et al. 2024). Nondestructive evaluation (NDE) techniques are thus essential for providing noninvasive and scalable solutions for quality assurance and in situ characterization (Gervilli & eacute;- Mouravieff et al. 2024; Zuo et al. 2025). Among these, ultrasonic NDE methods have gained increasing attention for battery characterization due to their ability to probe internal mechanical structures and track electrochemical states through wave-based sensing (Wang et al. 2024; Gou et al. 2024; Williams et al. 2024). Their flexible configuration, suitable penetration depth, and physical sensitivity make them a valuable complement to electrochemical, electrical, and optical techniques, particularly in high-throughput and real-time applications (Zuo et al. 2025). Ultrasound probes the internal physics of batteries through wave-material interactions, offering a direct mechanical pathway for structural and compositional assessment. Various ultrasonic modes-such as longitudinal and guided waves-have been employed to characterize electrode materials, embedded defects and bubbles, mechanical properties, electrolyte distribution, lithium plating, thermal behaviors, and both state-of-charge (SOC) and state-of-health (SOH) across different measurement configurations (Zuo et al. 2025; Gou et al. 2024; Wang et al. 2024; Williams et al. 2024). Among these configurations, the pulse-echo setup has gained particular traction for SOC/SOH evaluation due to its simplicity and flexibility (Wang et al. 2024; Gou et al. 2024). In this context, both time-domain metrics (e.g., time of flight, amplitude decay) (Hsieh et al. 2015; Fordham et al. 2023) and frequency-domain signatures (e.g., resonance shifts, spectral energy redistribution) (Chang and Steingart 2021; Sun et al. 2022; Ren et al. 2025a) have been used to correlate ultrasonic responses with mechanical and electrochemical changes in battery components. A defining feature of wave-battery interactions is their pronounced dependence on frequency (Copley et al. 2021; Huang et al. 2022; Ren et al. 2025a), which critically affects the interpretation of complex signal patterns arising from coupled structural and electrochemical phenomena in multilayer cells (Sun et al. 2022; Reichmann and Sharif-Khodaei 2023). Early studies observed this dependence empirically, reporting that different excitation frequencies led to varying characterization performance (Copley et al. 2021; Sun et al. 2022; Reichmann and Sharif-Khodaei 2023). Subsequent investigations identified underlying physics such as ultrasonic resonance (Huang et al. 2022, 2023) and Bragg bandgaps (Ma et al. 2024; Lee et al. 2025), where reflection intensities varied across different frequency intervals. This understanding has since been extended into a generalized analysis framework (Ren et al. 2025a, 2025b), revealing structured frequency responses that encode the interplay between wave propagation, cell architecture, and electrochemical states. These spectral structures serve as physically meaningful fingerprints of the internal battery configuration and are highly relevant for state-dependent analysis (Ren et al. 2025a). However, extracting such frequency structures from reflection signals in an efficient manner remains a technical challenge, especially when constrained by testing time, data volume, and real-time evaluation requirements. Conventional approaches to ultrasonic band structure identification rely on sequential narrow-band excitations, typically toneburst pulses, sweeping across discrete center frequencies within the range of interest (Huang et al. 2022; Ren et al. 2023, 2025a). While this method enables effective mapping of the frequency-dependent reflection response, it is inherently inefficient, particularly when wide spectral coverage is required. Additionally, narrow-band excitations often yield redundant or uninformative measurements outside the sensitive frequency range, reducing data storage compactness. Frequency-modulated excitations, such as linear chirps, present a promising alternative: by encoding a continuous range of frequencies within a single waveform, they allow for time-compressed and spectrally broad probing (Yang et al. 2019; Tian et al. 2024; Challinor and Cegla 2024). However, the design and implementation of such excitations-particularly in terms of sweep format, signal shaping, and time-frequency characteristics-remain underexplored in the context of ultrasonic evaluation of batteries. In this study, we propose a frequency-modulated angular-sweep excitation strategy for efficiently identifying the ultrasonic frequency response structure of multilayer pouch cells. Simulation studies are conducted to compare the performance of toneburst-based linear sweeps with frequency-modulated chirp signals configured at various time-frequency angles. By analyzing the resulting spectral morphologies and reflection waveforms, we demonstrate that angular chirp excitations can achieve a sparse yet informative description of the battery's critical band structure, effectively reducing measurement redundancy and enhancing information density. We further incorporate amplitude modulation to improve time localization, thereby aligning the waveform characteristics with those of traditional pulse-echo measurements and improving suitability for real-world diagnostics. The remainder of this paper is organized as follows: Section 2 presents the method for identifying frequency structures using both narrow-band and frequency-modulated ultrasonic excitations. Section 3 reports the simulation results and comparative analyses between linear and angular sweep strategies, including their time-frequency behavior and characterization performance. Section 4 summarizes the main findings and outlines the potential of the proposed approach for practical deployment in ultrasonic battery characterization systems.

Structural health monitoring often involves temperature measurement. However, traditional sensors cannot measure subsurface temperature non-invasively, making them unsuitable for monitoring temperature-driven damage mechanisms such as high-cycle thermal fatigue. This limitation arises, in part, due to effective thermal low-pass filtering caused by material properties. A previous feasibility study demonstrated that subsurface temperature can be inferred non-invasively in mild steel subjected to uniform heating. This was achieved using the ultrasonic-based inverse thermal modelling (ITM) method, which assumes the temperature of a component can be described by a 1D system. This study investigated the behaviour of ITM under non-uniform heating applied to the 'inaccessible' surface of a stainless steel sample through experiments and simulations. The experimental results show that ITM over-predicts temperature by as much as 120% when the heated region is small compared with the 10mm ultrasonic beam size. In simulation, the overestimation was reduced as the size of the heating source increased, effectively making the temperature distribution more uniform across the volume through which the ultrasonic wave travels. Despite the overestimation under non-uniform heating, ITM overcomes the thermal low-pass filtering, allowing the detection of thermal transients compared with a thermocouple mounted on the 'accessible' surface of a component.

Inefficiencies in the slurry mixing stage are a major factor in high scrap rates in battery manufacturing, thus hindering sustainable production.

Coded excitation has been shown to be a simple yet effective technique for improving signal quality in ultrasonic active ranging applications. Despite many reported benefits, uptake of coded excitation in industrial applications to date has been minimal. The authors speculate that this can be in part attributed to a lack of understanding of the robustness of the technique in practical use. To combat this, this paper reports on research into the main mechanisms that can introduce performance degradation and describes the effect of the two most important mechanisms, referred to as symbol asymmetry and symbol misalignment. These mechanisms lower output signal quality through the introduction of unexpected signal artifacts, as well as by reducing useful signal amplitude. We show how symbol asymmetry can be introduced through hardware imperfections and the relative degradation severity associated with different imperfection types. We similarly show how symbol misalignment can be introduced when using coded excitation in non-stationary situations. As a result, we formulate the minimum hardware requirements and inspection conditions required to correctly utilise coded excitation such that users can be confident of achieving high quality outcomes. We quantitatively simulate and experimentally verify the output signal degradation across many scenarios to identify the operating conditions that need to be satisfied to ensure that degradation does not exceed an arbitrarily chosen threshold of 40 dB (the noise floor from random noise in our experimental setup).

Clinical evidence for externally delivered electrical/mechanical stimulation in bone healing is mixed: proponents describe large benefits, while others report no difference. This may be because inconsistent targeting, anatomical differences, and physical phenomena (e.g., attenuation, reflection) mean cells experience highly variable stimulation doses. This study aimed to overcome this by developing implants that stimulate directly at the bone-implant interface. A bioelectronic implant (Fig. 1a; Ø8×16 mm) was developed to provide controlled electromechanical stimulation at the bone-implant interface. These implants had a rough titanium fixation surface (Ra: 75 µm) akin to contemporary cementless arthroplasty devices, but had electronics and sensors sealed inside. Eight were inserted into surgical defects (Fig. 1b; Ø8 mm) in the femoral condyles of four skeletally mature ewes (License P16F4AA0A). Half were activated intraoperatively by a mobile phone app such that they delivered electromechanical stimulus postoperatively (active) and half were left off (passive), with a double-blind paired-limb study design. Samples were retrieved after six weeks. Bone growth was analysed using fluorochrome histomorphometry (day 7: oxytetracycline; 21: alizarin red; 42: calcein blue). Microcomputed tomography (µCT) and scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM/EDX) assessed mineralisation. Histology (H&E) was analysed by two blinded reviewers. Temperature was measured daily with onboard sensing. Bone growth at the implant interface was 58% faster with stimulation between days 7–21 (Fig. 1c; 5.4±1.2 vs. 3.5±0.9 µm/day; p=0.001) and 47% faster between days 21–42 (Fig. 1c; 3.3±0.6 vs. 2.3±0.7 µm/day; p=0.005). Remodeling within three trabeculae of the interface increased by 14% between days 7–42 (p = 0.017); no differences were observed beyond this, confirming effects were localised. µCT revealed mineralised bone within 100 µm of all implants, which was consistently high for the active samples (Fig. 1e&g vs. 1f&i); SEM/EDX confirmed mineralisation (Ca:P ratio ~1.7). Histology (Fig. 1h vs. 1j) found moderate-to-strong osseointegration around all active implants, but only half the passive controls. Temperature sensing indicated a beneficial short-sharp inflammatory response for the active implants relative to controls (Fig. 1d; p<0.05). Controlled, locally-targeted electromechanical stimulation from a bioelectronic implant leads to osseointegration that is >50% faster and twice as reliable as contemporary clinical technology. This first-of-its-kind technological advance could lead to a more digital future for orthopaedics whereby implant fixation is controlled and sensed postoperatively. Acknowledgements: UKRI (EP/W524323/1, EP/X52556X/1, EP/R042721/1), Wellcome Trust (223797/Z/21/Z), Imperial (DT-prime, FILM). For any figures or tables, please contact the authors directly.

Characterizing and understanding internal battery physics is essential for stability, safety, and recyclability. Ultrasound provides a non-destructive solution by encoding battery dynamics into mechanical waves. However, the complex multi-layer structure and coupled mechanical-electrochemical behaviors of commercial cells hinder standardized and physically interpretable ultrasonic testing. This study presents a unified ultrasonic framework for multi-layer pouch cells, linking wave dynamics to battery structures, materials, and states across frequency and time domains. Inspired by electrochemical impedance spectroscopy, we examine structure-and state-waveform relationships of batteries under various excitation conditions, decoding ultrasonic responses related to mechanical and electrochemical factors in a generalizable manner. Using first-principles modeling and frequency sweep experiments, we identify battery-specific frequency bandstructures and wave modulation signatures tied to cell architecture and cathode chemistry, allowing mechanical discrimination of these factors in electrochemically steady states. In-operando tests demonstrate that changes in localized ultrasonic resonance associated with shifting bandstructure can map variations in battery state of charge, with the evolution of anode material stiffness as a key driving mechanism. This work establishes a physics-grounded foundation for understanding wave-battery interactions and is expected to guide the development of high-sensitivity, task-specific tools and diagnostic strategies across the in-laboratory, post-manufacture, and in-service stages of a battery's lifecycle.

Batteries, particularly lithium-ion batteries, are essential for electronic devices, electric vehicles, and aerospace applications. However, manufacturing defects and operational degradations pose significant safety and reliability risks. Ultrasound has become widely recognized as a non-destructive method for assessing battery states and structures. Nevertheless, the current understanding of wave-battery interaction dynamics still depends on trial-and-error results, lacking insight into the general ultrasonic response characteristics and their evolution across different operational conditions and cell chemistries. In this work, we present a unified framework to model, predict, and analyze the generalized frequency response characteristics of ultrasound during battery testing in the pulse-echo configuration. Using forward modeling and swept frequency analysis, we describe the generalized frequency responses and wave structure characteristics of multilayered battery systems and clarify the physical relationship between reflection modulations and internal battery substructures. We then propose a physics-guided state evaluation method to investigate changes in mechanical dynamics induced by variations in electrochemical state, enabling a substructure-resolved mapping of state-of-charge heterogeneity across the inspection surface and through the battery's thickness. We further demonstrate the advantages of our method in terms of state response sensitivity, structural resolvability, and robustness through comparative studies with state-of-the-art methods across various batteries. By providing a foundational understanding of the wave physics and generalized ultrasonic tools, this work aims to facilitate standardized, high-throughput ultrasonic evaluation of batteries throughout in-lab, post-manufacture and in-service phases of a battery's life.

This paper presents a low-power hardware architecture that facilitates the simultaneous transmission and reception of ultrasonic signals when using coded excitations for ultrasonic measurements. With this architecture, long pseudo-periodic coded excitations, which have previously been unsuitable for pulse-echo measurements, can be used to produce high Signal-to-Noise Ratio (SNR) results without an increase in signal dead-zone and without introducing filter artefacts within a set measurement window. We show that a low-power system (±2V peak excitation amplitude without receiver amplification) utilising such coded excitations can achieve the same level of performance as a conventional high-power system (−200V peak excitation amplitude with 15dB receiver amplification) by producing 45dB SNR measurements whilst maintaining a high Pulse Repetition Frequency (PRF) of ≥0.5 kHz. The use of pseudo-periodic sequences to produce quasi-orthogonal sequence families is then demonstrated to allow an arbitrary number of acquisition channels to be used simultaneously with complete crosstalk removal within a set measurement window. Therefore, the work presented here can open the door for the development of simplified low-power multi-channel acquisition systems without sacrificing system performance.

Failure of pipe network components in so-called mixing zones due to high-cycle thermal fatigue (HCTF) can occur within nuclear power plants where fluids of different thermal and hydraulic properties interact. Given that the consequences of such failures are potentially deadly, a method to monitor HCTF non-invasively in real-time is expected to be of great use. This method may be realised by a technique to determine the inaccessible temperature distribution of a component since thermal gradients drive HCTF. Previous work showed that a physics-based method called the inverse thermal modelling (ITM) method can obtain the temperature distribution from external temperature and ultrasonic time of flight (TOF) measurements. This study investigated whether the long-short-term memory (LSTM) machine learning architecture could be a faster alternative to the ITM method for data inversion. On experimental data, a 25-member ensemble of LSTM networks achieved an ensemble median root mean square error (RMSE) of 1.04°C and an ensemble median mean error of 0.194°C (both relative to a resistance temperature device measurement). These values are similar to the ITM method which achieved a RMSE of 1.04°C and a mean error of 0.196°C. The single LSTM network and the ITM method achieved a computation-to-real-world time ratio of 0.008% and 14%, respectively demonstrating that both methods can invert data in real-time. Simulation studies revealed that LSTM performance is sensitive to small differences between the training and real-world parameters leading to unacceptable errors. However, these errors can be detected via an ensemble of independent networks and, corrected by simply adding a correction factor to the TOF prior to being input into the networks. The results show that LSTM has the potential to be an alternative to the ITM method; however, the authors favour ITM for temperature distribution monitoring given its interpretability.

Coded excitation is a well-researched signal processing technique that employs phase modulations to improve signal quality in acquired A-scan ultrasonic timetraces. By utilising phase modulations based on sequences with favourable time-compression properties, total excitation energy can be increased. This directly improves Signal-to-Noise Ratio (SNR) without necessitating an increase in peak output power or reducing range resolution. Most prior research into this topic has focussed on understanding how typical ultrasonic inspection systems can be improved by incorporating coded excitations. This work instead highlights the benefits of an ultrasonic inspection system that is designed especially for coded excitations. Traditional systems ensure a high SNR by using high-voltage excitations, isolation circuits and pre-amplifiers before received signal digitisation. Instead, in this work we propose the use of low-voltage transmissions amplitudes which are within the operating range of the receiver components such that receiver isolation is not required. This removes the limitation on applicable sequence lengths for coded excitation measurements. Therefore, ever increasing sequence lengths can be utilised to improve the measurement SNR without increasing signal dead-zone. Further, this opens the possibility of using different types of sequence which can achieve quasi-ideal compression from a single transmission event, and facilitates the use of quasi-orthogonality for suppressing crosstalk during simultaneous operation of multi-channel systems. Through physical experiments, we show how this low-power coded approach can be utilised to match the performance (45dB SNR) of conventional high voltage systems (200V transmission amplitude with 15dB receiver amplification) whilst using only +/-2V transmission signals (40dB reduction in peak excitation power). The ability to remove inefficient high-voltage transmission hardware by adopting this technique can open the door for equally capable but much more cost effective and compact ultrasonic inspection hardware, making it ideal for applications such as permanently installed systems for Structural Health Monitoring.

Pulse compression based excitation signals have been shown to improve signal quality in many active ranging applications without negatively impacting range resolution. Most prior work into using pulse compression presents the technique as if matched filtering is necessary to successfully achieve signal compression. Matched filtering against modulated excitation signals does result in useful information compression, however, it also suppresses information outside of the bandwidth of the transmission signal. This can distort or remove useful information in some applications, such as ultrasonic guided wave inspections, making the processing step unsuitable.In this paper, we show that when pulse compression with coded excitation is employed, a second filtering option is available for compressing the modulated information. The second option, which we have termed the sequence filter, utilises sequence elements as the template against which the filtering of coded excitation measurements is undertaken, thereby allowing compression to be achieved independent of received signal frequency content. We verify that sequence filtering successfully produces signal compression in two experimental ultrasound non-destructive testing applications where frequency modulated pulse compression was unsuitable. With both sequence filtering and matched filtering, we show signal-to-noise ratio gains in excess of 20 dB from using pulse compression.

This research introduces a chemistry-agnostic approach to achieve rapid and degradation-free battery charging via ultrasonic agitation. An ultrasonic device operating in the megahertz range was used to stimulate electrolyte flow from outside the cell. The acoustic streaming effect accelerates ion transport from the bulk electrolyte to the electrode surface and suppresses the formation of an ion depletion zone. An experimental setup was used to optically observe the formation of dendrites when the current imposed across two zinc electrodes exceeded the limiting current. Beyond this limit, diffusion alone cannot provide sufficient ions, resulting in an ion depletion zone. It was subsequently shown that dendrite formation was reduced by over 98% when 15x the limiting current was forced across the electrodes and acoustic stimulation was delivered. Furthermore, it was shown that compared to the scenario without ultrasonic stimulation, the steady state potential was also reduced by 29%, indicating much better ion exchange between the electrodes. These findings suggest that ultrasonic stimulation can be a tool for enhancing electrochemical processes such as battery charging and discharging.

Pipe networks within nuclear power plants (NPPs) are susceptible to high-cycle thermal fatigue (HCTF) failures especially in so-called mixing zones where fluids with different thermal and hydraulic properties interact. The 1998 incident at Civaux 1 NPP is a good example of such a failure and its potential consequences. Given the critical impact on safety of these NPP components, a non-invasive method for HCTF progression monitoring in real time is expected to be of great use. Previous ultrasonic monitoring work showed that it is possible to predict the through-thickness temperature distribution and its temporal evolution of a mild steel block to within ±2 °C, relative to a resistance temperature device. These predictions were achieved using time of flight measurements from an ultrasonic transducer placed on the accessible surface with the so-called inverse thermal model (ITM) to invert the data. However, experiments to date have been limited to slow (10 minute) thermal transients at low temperatures (T < 100 °C). Given that HCTF is driven by thermal gradients, the ITM method seems promising to monitor its progression. In this work the performance of the ITM method was investigated under more realistic conditions: faster (1 minute) thermal transients at higher temperatures (≈ 250-300 °C). A special high temperature electromagnetic acoustic transducer (EMAT) and a fast acquisition and inversion methodology were created to collect the data. The measurement setup and the collected data will be presented in this paper.

Achieving osseointegration is a fundamental requirement for many orthopaedic, oral, and craniofacial implants. Osseointegration typically takes three to 6 months, during which time implants are at risk of loosening. The aim of this study was to investigate whether osseointegration could be actively enhanced by delivering controllable electromechanical stimuli to the periprosthetic bone. First, the osteoconductivity of the implant surface was confirmed using an in vitro culture with murine preosteoblasts. The effects of active treatment on osseointegration were then investigated in a 21-day ex vivo model with freshly harvested cancellous bone cylinders (n = 24; Ø10 mm × 5 mm) from distal porcine femora, with comparisons to specimens treated by a distant ultrasound source and static controls. Cell viability, proliferation and distribution was evident throughout culture. Superior ongrowth of tissue onto the titanium discs during culture was observed in the actively stimulated specimens, with evidence of ten-times increased mineralisation after 7 and 14 days of culture (p < 0.05) and 2.5 times increased expression of osteopontin (p < 0.005), an adhesive protein, at 21 days. Moreover, histological analyses revealed increased bone remodelling at the implant-bone interface in the actively stimulated specimens compared to the passive controls. Active osseointegration is an exciting new approach for accelerating bone growth into and around implants.

Objective Ultrasound speckle tracking enables in vivo measurement of soft tissue deformation or strain, providing a non-invasive diagnostic tool to quantify tissue health. However, adoption into new fields is challenging since algorithms need to be tuned with gold-standard reference data that are expensive or impractical to acquire. Here, we present a novel optimization approach that only requires repeated measurements, which can be acquired for new applications where reference data might not be readily available or difficult to get hold of. Methods Soft tissue motion was captured using ultrasound for the medial collateral ligament (MCL) of three quasi-statically loaded porcine stifle joints, and medial ligamentous structures of a dynamically loaded human cadaveric knee joint. Using a training subset, custom speckle tracking algorithms were created for the porcine and human ligaments using surrogate optimization, which aimed to maximize repeatability by minimizing the normalized standard deviation of calculated strain maps for repeat measurements. An unseen test subset was then used to validate the tuned algorithms by comparing the ultrasound strains to digital image correlation (DIC) surface strains (porcine specimens) and length change values of the optically tracked ligament attachments (human specimens). Results After 1500 iterations, the optimization routine based on the porcine and human training data converged to similar values of normalized standard deviations of repeat strain maps (porcine: 0.19, human: 0.26). Ultrasound strains calculated for the independent test sets using the tuned algorithms closely matched the DIC measurements for the porcine quasi-static measurements (R > 0.99, RMSE < 0.59%) and the length change between the tracked ligament attachments for the dynamic human dataset (RMSE < 6.28%). Furthermore, strains in the medial ligamentous structures of the human specimen during flexion showed a strong correlation with anterior/posterior position on the ligaments (R > 0.91). Conclusion Adjusting ultrasound speckle tracking algorithms using an optimization routine based on repeatability led to robust and reliable results with low RMSE for the medial ligamentous structures of the knee. This tool may be equally beneficial in other soft-tissue displacement or strain measurement applications and can assist in the development of novel ultrasonic diagnostic tools to assess soft tissue biomechanics.