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In this study, we investigate the magnetic induction heating induced in a conducting polymer (CP) under alternative magnetic fields (AMFs). Experimental results and numerical simulations have proved that the magneto-thermal conversion of the CP is caused by the induced eddy current, which is related to the shape and intensity of the applied external AMF, and the intrinsic electrical conductivity, macrostructure and microstructure of the CP. By employing various fabrication methods, specific temperature distribution and control of thermal field within conducting polymer films and aerogels could be achieved. To exploit the potential of magnetic induction heating in CP for biomedical applications, we designed a conducting polymer aerogel-based self-adaptive heat patch and demonstrated its AMF-enabled localized heating of skin. In addition to the thermal ablation of tumor cells via magneto-thermal conversion of the CP, the promotion of neuronal differentiation at mild temperature by noninvasive magneto-electrical stimulation has also been demonstrated to be an effective strategy for tissue engineering.

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Crack detection in high-pressure hydrogen gas components, such as pipes, is crucial for ensuring the safety and reliability of hydrogen infrastructure. This study conducts the nondestructive testing of crack propagation in steel piping under cyclic compressive loads in the presence of hydrogen in the material. The specimens were hydrogen-precharged through immersion in a 20 mass% ammonium thiocyanate solution at 40 °C for 72 h. The crack growth rate in hydrogen-precharged specimens was approximately 10 times faster than that in uncharged specimens, with cracks propagating from the inner to outer surfaces of the pipe. The fracture surface morphology differed significantly, with flat surfaces in hydrogen-precharged materials and convex or concave surfaces in uncharged materials. Eddy current and hammering tests revealed differences in the presence of large cracks between the two materials. By contrast, hammering tests revealed differences in the presence of a half size crack between the two materials. These findings highlight the effect of hydrogen precharging on crack propagation in steel piping and underscore the importance of early detection methods.

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PURPOSE: To develop a 3D spherical EPTI (sEPTI) acquisition and a comprehensive reconstruction pipeline for rapid high-quality whole-brain submillimeter T 2 * $$ {\mathrm{T}}_2^{\ast } $$ and QSM quantification. METHODS: For the sEPTI acquisition, spherical k-space coverage is utilized with variable echo-spacing and maximum kx ramp-sampling to improve efficiency and signal incoherency compared to existing EPTI approaches. For reconstruction, an iterative rank-shrinking B0 estimation and odd-even high-order phase correction algorithms were incorporated into the reconstruction to better mitigate artifacts from field imperfections. A physics-informed unrolled network was utilized to boost the SNR, where 1-mm and 0.75-mm isotropic whole-brain imaging were performed in 45 and 90 s at 3 T, respectively. These protocols were validated through simulations, phantom, and in vivo experiments. Ten healthy subjects were recruited to provide sufficient data for the unrolled network. The entire pipeline was validated on additional five healthy subjects where different EPTI sampling approaches were compared. Two additional pediatric patients with epilepsy were recruited to demonstrate the generalizability of the unrolled reconstruction. RESULTS: sEPTI achieved 1.4 × $$ \times $$ faster imaging with improved image quality and quantitative map precision compared to existing EPTI approaches. The B0 update and the phase correction provide improved reconstruction performance with lower artifacts. The unrolled network boosted the SNR, achieving high-quality T 2 * $$ {\mathrm{T}}_2^{\ast } $$ and QSM quantification with single average data. High-quality reconstruction was also obtained in the pediatric patients using this network. CONCLUSION: sEPTI achieved whole-brain distortion-free multi-echo imaging and T 2 * $$ {\mathrm{T}}_2^{\ast } $$ and QSM quantification at 0.75 mm in 90 s which has the potential to be useful for wide clinical applications.

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In the field of quality control, the critical challenge of analyzing microdefects in steel filament holds significant importance. This is particularly vital, as steel filaments serve as reinforced fibers in the use and applications within various component manufacturing industries. This paper addresses the crucial requirement of identifying and investigating microdefects in steel filaments. Eddy current signals are used for the identification of microdefects, and an in-depth investigation is conducted. The core objective is to establish the relationship between the depth of defects and the signals detected through the eddy current sensing principle. The threshold of the eddy current instrument was set at 10%, corresponding to a created depth of 20 µm, to identify defective specimens. A total of 30 defective samples were analyzed, and the phase angles between the experimental and theoretical results were compared. The depths of defects ranged from 20 to 60 µm, with one sample having a depth exceeding 75 µm. The calculated threshold of 10.18% closely aligns with the set threshold of 10%, with a difference of only 1.77%. The resulting root mean square error (RMSE) was found to be 10.53 degrees, equivalent to 3.49 µm for the difference in depth and phase between measured results and estimated results. This underscores the methodology's accuracy and its applicability across diverse manufacturing industries.

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Pore and crack formation in parts produced by additive manufacturing (AM) processes, such as laser powder bed fusion, is one of the issues associated with AM technology. Surface and subsurface cracks and pores are induced during the printing process, undermining the printed part durability. In-situ detection of defects will enable the real-time or intermittent control of the process, resulting in higher product quality. In this paper, a new eddy current-based probe design is proposed to detect these defects in parts with various defects that mimic pores and cracks in additively manufactured parts. Electromagnetic finite element analyses were carried out to optimize the probe geometry, followed by fabricating a prototype. Artificial defects were seeded in stainless steel plates to assess the feasibility of detecting various flaws with different widths and lengths. The smallest defect detected had a 0.17 mm radius for blind holes and a 0.43 mm notch with a 5 mm length. All the defects were 0.5 mm from the surface, and the probe was placed on the back surface of the defects. The surface roughness of the tested samples was less than 2 µm. The results show promise for detecting defects, indicating a potential application in AM.

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The detection of defects in aluminium alloys using eddy current testing (ECT) can be restricted by higher electrical conductivity. Considering the occurrence of discontinuities during the selective laser melting (SLM) process, checking the ability of the ECT method for the mentioned purpose could bring simple and fast material identification. The research described here is focused on the application of three ECT probes with different frequency ranges (0.3-100 kHz overall) for the identification of artificial defects in SLM aluminium alloy AlSi10Mg. Standard penetration depth for the mentioned frequency range and identification abilities of used probes expressed through lift-off diagrams precede the main part of the research. Experimental specimens were designed in four groups to check the signal sensitivity to variations in the size and depth of cavities. The signal behavior was evaluated according to notch-type and hole-type artificial defects' presence on the surface of the material and spherical cavities in subsurface layers, filled and unfilled by unmolten powder. The maximal penetration depth of the identified defect, the smallest detectable notch-type and hole-type artificial defect, the main characteristics of signal curves based on defect properties and circumstances for distinguishing between the application of measurement regime were stated. These conclusions represent baselines for the creation of ECT methodology for the defectoscopy of evaluated material.

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Additive Manufacturing (AM) Direct Laser Fabrication (DLF) of Ti-5Al-5V-5Mo-3Cr (Ti5553) is being developed as a method for producing aircraft components. The additive manufacturing process can produce flaws near the surface, such as porosity and material voids, which act as stress raisers, leading to potential component failure. Eddy current testing was investigated to detect flaws on or near the surface of DLF Ti5553 bar samples. For this application, the objective was to develop an eddy current probe capable of detecting flaws 500 µm in diameter, located 1 mm below the component's surface. Two initial sets of coil parameters were chosen: The first, based on successful experiments that demonstrated detection of a near surface flaw in Ti5553 using a transmit-receive array probe, and the second, derived from simulation by Finite Element Method (FEM). An optimized transmit receive coil design, based on the FEM simulations, was constructed. The probe was evaluated on Ti5553 samples containing sub-surface voids of the target size, as well as samples with side-drilled holes and samples with holes drilled from the opposing inspection surface. The probe was able to effectively detect 80% of the sub-surface voids. Limitations included the probe's inability to detect sub-surface voids near sample edges and a sensitivity to surface roughness, which produces local changes in lift-off. Multifrequency mixing improved signal-to-noise ratio when surface roughness was present on average by 22%. A probe based on that described in this paper could benefit quality assurance of additively manufactured aircraft components.

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This paper introduces an LC resonator-based single-frequency eddy current (EC) sensor designed for corrosion detection in reinforcing bars (rebars) embedded within concrete structures. The work addresses the challenges of the limited detection ranges and reduced sensitivity over longer distances, prevalent in current EC sensor applications. The sensor development process involved a systematic experimental approach to carefully selecting each parameter in the LC resonator. The sensor design aimed to assess the condition of the rebar from a distance of up to 5-6 cm outside the concrete and provide insights into different corrosion levels. By examining the characteristics of the inductors, the parallel resistance Rp of the eddy current coil was identified as a key parameter reflecting the corrosion conditions in the rebar. The relationship between the Rp fluctuations and temperature variations was investigated, with the data indicating that an approximately 155 Ω variation can be expected per 1 °C change within the temperature range of 20-25 °C, allowing for temperature compensation if necessary. Subsequently, the sensor's performance was evaluated by placing a rebar within a concrete block, where controlled mechanical degradation cycles were applied to simulate uniform corrosion in the rebar. The experimental results show that our EC sensor can detect material loss around the rebar with accuracy of approximately 0.17 mm.

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A reliable and efficient rail track defect detection system is essential for maintaining rail track integrity and avoiding safety hazards and financial losses. Eddy current (EC) testing is a non-destructive technique that can be employed for this purpose. The trade-off between spatial resolution and lift-off should be carefully considered in practical applications to distinguish closely spaced cracks such as those caused by rolling contact fatigue (RCF). A multi-channel eddy current sensor array has been developed to detect defects on rails. Based on the sensor scanning data, defect reconstruction along the rails is achieved using an inverse algorithm that includes both direct and iterative approaches. In experimental evaluations, the EC system with the developed sensor is used to measure defects on a standard test piece of rail with a probe lift-off of 4-6 mm. The reconstruction results clearly reveal cracks at various depths and spacings on the test piece.

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BACKGROUND: Golden angle (GA) radial trajectory is advantageous for dynamic magnetic resonance imaging (MRI). Recently, several advanced algorithms have been developed based on navigator-interleaved GA trajectory to realize free-running cardiac MRI. However, navigator-interleaved GA trajectory suffers from the eddy-current effect, which reduces the image quality. PURPOSE: This work aims to integrate the navigator-interleaved GA trajectory with clinical cardiac MRI acquisition, with the minimum eddy-current artifacts. The ultimate goal is to realize a high-quality free-running cardiac imaging technique. METHODS: In this paper, we propose a new "swing golden angle" (swingGA) radial profile order. SwingGA samples the k-space by rotating back and forth at the generalized golden ratio interval, with smoothly interleaved navigator readouts. The sampling efficiency and angle increment distributions were investigated by numerical simulations. Static phantom imaging experiments were conducted to evaluate the eddy current effect, compared with cartesian, golden angle radial (GA), and tiny golden angle (tGA) trajectories. Furthermore, 12 heart-healthy subjects (aged 21-25 years) were recruited for free-running cardiac imaging with different sampling trajectories. Dynamic images were reconstructed by a low-rank subspace-constrained algorithm. The image quality was evaluated by signal-to-noise-ratio and spectrum analysis in the heart region, and compared with traditional clinical cardiac MRI images. RESULTS: SwingGA pattern achieves the highest sampling efficiency (mSE > 0.925) and the minimum azimuthal angle increment (mAD < 1.05). SwingGA can effectively suppress eddy currents in static phantom images, with the lowest normalized root mean square error (nRMSE) values among radial trajectories. For the in-vivo cardiac images, swingGA enjoys the highest SNR both in the blood pool and myocardium, and contains the minimum level of high-frequency artifacts. The free-running cardiac images have good consistency with traditional clinical cardiac MRI, and the swingGA sampling pattern achieves the best image quality among all sampling patterns. CONCLUSIONS: The proposed swingGA sampling pattern can effectively improve the sampling efficiency and reduce the eddy currents for the navigator-interleaved GA sequence. SwingGA is a promising sampling pattern for free-running cardiac MRI.

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In the course of this investigation, we undertook the contemplation of a green chemistry paradigm with the express intent of procuring valuable metal, namely gold, from electronic waste (e-waste). In pursuit of this overarching objective, we conceived a procedural framework consisting of two pivotal stages. As an initial stage, we introduced a physical separation procedure relying on the utilization of the Eddy current separator, prior to embarking on the process of leaching from e-waste. Subsequent to the partitioning of metals from the non-metal constituents of waste printed circuit boards (PCB), we initiated an investigation into the hydrogel derived from basil seeds (Ocimum basilicum L.), utilizing it as a biogenic sorbent medium. The thorough characterization of hydrogel extracted from basil seeds involved the application of an array of analytical techniques, encompassing FTIR, XRD, SEM, and BET. The batch sorption experiments show more than 90% uptake in the pH range of 2-5. The sorption capacity of the hydrogel material was evaluated as 188.44 mg g-1 from the Langmuir Isotherm model. The potential interference stemming from a spectrum of other ions, encompassing Al, Cu, Ni, Zn, Co, Cr, Fe, Mn, and Pb was systematically examined. Notably, the sole instance of interference in the context of adsorption of gold ions was observed to be associated with the presence of lead. The application of the hydrogel demonstrated a commendable efficiency in the recovery of Au(III) from the leached solution derived from the waste PCB.

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The electromagnetic eddy current non-destructive testing system enables the non-destructive analysis of surface defect information on tested materials. Based on the principles of eddy current detection, this paper presents a digital eddy current detection method using high-speed sampling based on STM32. A differential eddy current coil is used as the detection probe, and the combination of a differential bridge and a differential amplifier circuit helps to reduce common-mode noise interference. The detection signal is collected via an STM32-based acquisition circuit and transmitted to the host computer through Ethernet for digital demodulation processing. The host computer performs operations such as smoothing averaging, sinusoidal fitting, and outlier removal to extract the amplitude and phase of the detection signal. The system also visually displays the condition of the tested object's surface in real time through graphical visualization. Testing showed that this system can operate at frequencies up to 8.84 MHz and clearly identify defects as narrow as 1 mm on the surface of the tested steel plate.

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This paper describes a position sensor with six degrees of freedom (DoF) measurement capability. This sensor is designed for the position sensing of the rotor in a bearingless slice motor to enable active control. The sensor is designed to fit entirely under the rotor and operates by accessing the rotor bottom surface only, enabling packaging of the pump on the top of the rotor. The sensor has two parts; both operate using eddy currents. One of these parts measures the two radial DoF of the rotor. The other part measures the axial, angular rotation and tip/tilt DoF. The sensor utilizes a conductive target fixed to the underside of the rotor. Motion of this target varies the magnetic fields which can then be measured by the sensor as variation in either induced voltage or inductance value. The design and fabrication of the sensor along with the signal processing methods are presented in detail. The radial position measurements are the most critical for active levitation due to the small working gaps in these DoF, hence a resolution of < 1.2 ​ µ m and bandwidth of 1 kHz is achieved. This paper also describes the closed-loop behavior of a bearingless motor using this sensor.

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Bimetallic lined pipe (BLP) has been increasingly used in offshore and subsea oil and gas structures, but how to identify the invisible inner defects such as liner wall thinning and interface debonding is a challenge for future development. A nondestructive testing (NDT) method based on pulsed eddy current testing (PECT) has been proposed to face these difficulties. The inspection of the BLP specimen (AISI1020 base tube and SS304 liner) is implemented from outside of the pipe by using a transmitter-receiver-type PECT probe consisting of two induction coils. By simplifying the BLP specimen to stratified conductive plates, the electromagnetic field interaction between the PECT probe and specimen is analytically modeled, and the probe inspection signals due to liner wall thinning and interface debonding are calculated. In order to highlight the weak response (in microvolts) from the liner, the inspection signals are subtracted by the signal, which is calculated in the case of only having a base tube, yielding differential PECT signals. The peak voltage of the differential signal is selected to characterize the liner wall thinning and interface debonding due to its distinguishable and linear variation. Experiment verification is also carried out on a double-walled specimen simulated by a combination of a Q235 casing pipe and SS304 tubes of different sizes. The experimental results basically agree with the analytical predictions. The peak value of the PECT signal has an ascending and descending variation with the increase in the remaining liner wall thickness and debonding gap, respectively, while the negative peak value shows opposite changes. The peak value exhibits a larger sensitivity than the negative peak value. The proposed method shows potential promise in practical applications for the evaluation of the inner defects in BLP lines.

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Eddy current testing (ECT) is commonly used for the detection of defects inside metallic materials. In order to achieve the effective testing of CFRP materials, increasing the operating frequency or improving the coil structure is a common method used by researchers. Higher or wider operating frequencies make the design of the ADC's conditioning circuit complex and difficult to miniaturize. In this paper, an LC resonator based on inductance-to-digital converters (LDCs) is designed to easily detect the resonant frequency response to the state of the material under test. The reasonableness of the coil design is proven by simulation. The high signal-to-noise ratio (SNR) and detection sensitivity of the LC resonator are demonstrated through comparison experiments involving multiple probes. The anti-interference capability of the LC resonator in CFRP defect detection is demonstrated through various interference experiments.

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Enhancing the recovery efficiency of non-ferrous metals in eddy current separation is of great significance. In this study, the accuracy of the simulation model was verified by comparing the eddy current force. The transformation mechanism of the Lorentz forces into the eddy current force and torque in non-ferrous metal particles was revealed by analyzing various physical fields. Then, the influence of magnetic field parameters on eddy current, eddy current force, and torque was studied. It shows that the eddy current force and torque are affected by the vector gradient of the magnetic field and the magnetic flux density, respectively. Additionally, the time derivative of the magnetic field impacts the magnitude of the eddy current force and torque by controlling the eddy current. On this basis, the empirical models of eddy current force and torque were established by similarity theory. The results obtained can improve and expand the application of eddy current separation.

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Steel Plate Cold-Rolled Commercial (SPCC) steel is known to have long-term durability. However, it still undergoes corrosion when exposed to corrosive environments. This paper proposes an evaluation method for assessing the corrosion level of SPCC steel samples using eddy current testing (ECT), along with two different machine learning approaches. The objective is to classify the corrosion of the samples into two states: a less corroded state (state-1) and a highly corroded state (state-2). Generative and discriminative models were implemented for classification. The generative classifier was based on the Gaussian mixture model (GMM), while the discriminative model was based on the logistic regression model. The features used in the classification models are the peaks of the perturbated magnetic fields at two different frequencies. The performance of the classifiers was evaluated using metrics such as absolute error, accuracy, precision, recall, and F1 score. The results indicate that the GMM model is more conducive to categorizing states with higher levels of corrosion, while the logistic regression model is helpful in estimating states with lower levels of corrosion. Meanwhile, high classification accuracy can be achieved based on both methods using eddy current testing.

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To measure the micro-displacement reliably with high precision, a single-ended eddy current sensor based on temperature compensation was studied in detail. At first, the principle of the eddy current sensor was introduced, and the manufacturing method of the probe was given. The overall design plan for the processing circuit was induced by analyzing the characteristics of the probe output signal. The variation in the probe output signal was converted to pulses with different widths, and then it was introduced to the digital phase discriminator along with a reference signal. The output from the digital phase discriminator was processed by a low-pass filter to obtain the DC component. At last, the signal was amplified and compensated to reduce the influence of temperature. The selection criteria of the frequency of the exciting signal and the design of the signal conditioning circuit were described in detail, as well as the design of the temperature-compensating circuit based on the digital potentiometer with an embedded temperature sensor. Finally, an experimental setup was constructed to test the sensor, and the results were given. The results show that nonlinearity exists in the single-ended eddy current sensor with a large range. When the range is 500 µm, the resolution can reach 46 nm, and the repeatability error is ±0.70% FR. Within the temperature range from +2 °C to +58 °C, the voltage fluctuation in the sensor is reduced to 44 mV after temperature compensation compared to the value of 586 mV before compensation. The proposed plan is verified to be feasible, and the measuring range, precision, and target material should be considered in real-world applications.

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Eddy current displacement sensors (ECDSs) are widely used for the noncontact position measurement of small displacements (lift-offs). Challenges arise with larger displacements as the sensitivity of the ECDSs decreases. This leads to a more pronounced impact of temperature variations on the inductance and, consequently, an increased position error. Design solutions often rely on multiple coils, suitable coil carrier materials, and compensation measures to address the challenges. This study presents a single-coil ECDS for large displacement ranges in environments with high temperatures and temperature variations. The analysis is based on a sensor model derived from an equivalent circuit model (ECM). We propose design measures for both the sensing coil and the target, focusing on material selection to handle the impact of temperature variations. A key part of improving performance under varying temperatures includes model-based temperature compensation for the inductance of the sensing coil. We introduce a method to calibrate the sensor for large displacements, using a modified coupling coefficient based on field simulation data. Our analysis shows that this single-coil ECDS design maintains a position error of less than 0.2% full-scale for a temperature variation of 100 K for the sensing coil and 110 K for the target.

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A large portion of the pipe infrastructure used in the chemical processing industry is susceptible to corrosion under insulation (CUI). Eddy current-based magnetic sensing is one of the methods that can be used as an early detector of this corrosion. However, the large sensor-to-pipe distances used in this method, due to the presence of insulation, limits the sensitivity to corrosion. This paper will describe the development of instrumentation and methods based on eddy current sensing with thin-film magnetic sensors. In particular, it focuses on the influence of the sensor angle relative to the radial magnetic field. The influence of this parameter on the amplitude of the measured signal was investigated by both finite element simulations and experimental observations. The measured magnetic field was found to be highly sensitive to small changes in sensor angle, with the estimated depth of a defect changing at a rate of 11.2 mm/degree of sensor rotation for small angles. It is also shown that a sensor aligned with the radial direction should be avoided, with an optimal sensor angle between 0.5 and 4 degrees. With the sensor in this angle range, the simulations have shown it should be possible to resolve the depth of corrosion to a resolution of 0.1 mm.