Rapid Synthesis of Ruthenium-Copper Nanocomposites as High-Performance Bifunctional Electrocatalysts for Electrochemical Water Splitting.

Development of high-performance, low-cost catalysts for electrochemical water splitting is key to sustainable hydrogen production. Herein, ultrafast synthesis of carbon-supported ruthenium-copper (RuCu/C) nanocomposites is reported by magnetic induction heating, where the rapid Joule's heating of RuCl3 and CuCl2 at 200 A for 10 s produces Ru-Cl residues-decorated Ru nanocrystals dispersed on a CuClx scaffold, featuring effective Ru to Cu charge transfer. Among the series, the RuCu/C-3 sample exhibits the best activity in 1 m KOH toward both the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER), with an overpotential of only -23 and +270 mV to reach 10 mA cm-2, respectively. When RuCu/C-3 is used as bifunctional catalysts for electrochemical water splitting, a low cell voltage of 1.53 V is needed to produce 10 mA cm-2, markedly better than that with a mixture of commercial Pt/C+RuO2 (1.59 V). In situ X-ray absorption spectroscopy measurements show that the bifunctional activity is due to reduction of the Ru-Cl residues at low electrode potentials that enriches metallic Ru and oxidation at high electrode potentials that facilitates the formation of amorphous RuOx. These findings highlight the unique potential of MIH in the ultrafast synthesis of high-performance catalysts for electrochemical water splitting.

Performance of a Radio-Frequency Two-Photon Atomic Magnetometer in Different Magnetic Induction Measurement Geometries.

Measurements monitoring the inductive coupling between oscillating radio-frequency magnetic fields and objects of interest create versatile platforms for non-destructive testing. The benefits of ultra-low-frequency measurements, i.e., below 3 kHz, are sometimes outweighed by the fundamental and technical difficulties related to operating pick-up coils or other field sensors in this frequency range. Inductive measurements with the detection based on a two-photon interaction in rf atomic magnetometers address some of these issues as the sensor gains an uplift in its operational frequency. The developments reported here integrate the fundamental and applied aspects of the two-photon process in magnetic induction measurements. In this paper, all the spectral components of the two-photon process are identified, which result from the non-linear interactions between the rf fields and atoms. For the first time, a method for the retrieval of the two-photon phase information, which is critical for inductive measurements, is also demonstrated. Furthermore, a self-compensation configuration is introduced, whereby high-contrast measurements of defects can be obtained due to its insensitivity to the primary field, including using simplified instrumentation for this configuration by producing two rf fields with a single rf coil.

Image Reconstruction Requirements for Short-Range Inductive Sensors Used in Single-Coil MIT.

MIT (magnetic induction tomography) image reconstruction from data acquired with a single, small inductive sensor has unique requirements not found in other imaging modalities. During the course of scanning over a target, measured inductive loss decreases rapidly with distance from the target boundary. Since inductive loss exists even at infinite separation due to losses internal to the sensor, all other measurements made in the vicinity of the target require subtraction of the infinite-separation loss. This is accomplished naturally by treating infinite-separation loss as an unknown. Furthermore, since contributions to inductive loss decline with greater depth into a conductive target, regularization penalties must be decreased with depth. A pair of squared L2 penalty norms are combined to form a 2-term Sobolev norm, including a zero-order penalty that penalizes solution departures from a default solution and a first-order penalty that promotes smoothness. While constraining the solution to be non-negative and bounded from above, the algorithm is used to perform image reconstruction on scan data obtained over a 4.3 cm thick phantom consisting of bone-like features embedded in agarose gel, with the latter having a nominal conductivity of 1.4 S/m.

Balancing of Resonant Differential Coils for Broadband Inductive Sensor Systems.

Differential coils are frequently implemented in inductive sensing systems. They can be considered as a single coil that is made up of two or more subcoils, wound in series opposition. They can be used on the transmit or receive side of measurement systems, and, if designed correctly, ensure no coupling between coils under background conditions. By cancelling background coupling, the receive electronics only needs to be able to measure the change in coupling produced by a target. This allows for a more efficient use of the dynamic range, and for larger receive-side amplifier gain, thereby improving SNR. When subcoils are not electrically similar, it can be hard to engineer the coil to be perfectly balanced across a wide bandwidth. This paper presents an analytical model of a resonant differential coil pair that is tested and applied on a planar metal detector for the detection of buried objects. The model demonstrates the capability to balance an arbitrary differential coil pair, which has a broad applicability across a range of inductive sensor applications such as metal detection and non-destructive testing. The method is applied to the practical system. The results show that the correction resulting from this method ensures a stable balance across a significantly enhanced bandwidth. In the case studied here, the bandwidth of the experimental system is increased from 20 kHz to 90 kHz.

Strategic Fast Induction Heating to Combat Hysteresis Barriers in a Flexible MOF for Rapid CO2 Desorption in Biogas Upgrading.

A major challenge in Cyclic Swing Separation using flexible adsorbents that have high equilibrium CO2  adsorption capacity is their very low-pressure hysteresis that hinders efficient desorption. Mg-Gallate MOF is such a flexible adsorbent that only begins to release CO2 at its pore closing pressure at 0.08 bar and 30 °C, showing very slow and inefficient desorption in pressure or temperature swing. Therefore, a novel strategy is presented that combines state of art technique Magnetic Induction Heating with a vacuum swing for fast and efficient CO2 desorption from flexible adsorbents at a moderately elevated temperature (70 °C).

Magnetic Field-Assisted Interface Embedding Strategy to Construct 2D/3D Composite Structure for Stable Perovskite Solar Cells with Efficiency Over 24.

Perovskite solar cells (PSCs) based on 2D/3D composite structure have shown enormous potential to combine high efficiency of 3D perovskite with high stability of 2D perovskite. However, there are still substantial non-radiative losses produced from trap states at grain boundaries or on the surface of conventional 2D/3D composite structure perovskite film, which limits device performance and stability. In this work, a multifunctional magnetic field-assisted interfacial embedding strategy is developed to construct 2D/3D composite structure. The composite structure not only improves crystallinity and passivates defects of perovskite layer, but also can efficiently promote vertical hole transport and provide lateral barrier effect. Meanwhile, the composite structure also forms a good surface and internal encapsulation of 3D perovskite to inhibit water diffusion. As a result, the multifunctional effect effectively improves open-circuit voltage and fill factor, reaching maximum values of 1.246 V and 81.36%, respectively, and finally achieves power conversion efficiency (PCE) of 24.21%. The unencapsulated devices also demonstrate highly improved long-term stability and humidity stability. Furthermore, an augmented performance of 21.23% is achieved, which is the highest PCE of flexible device based on 2D/3D composite perovskite films coupled with the best mechanical stability due to the 2D/3D alternating structure.

Conductivity reactivity index for monitoring of cerebrovascular autoregulation in early cerebral ischemic rabbits.

BACKGROUND: Cerebrovascular autoregulation (CVAR) is the mechanism that maintains constant cerebral blood flow by adjusting the caliber of the cerebral vessels. It is important to have an effective, contactless way to monitor and assess CVAR in patients with ischemia. METHODS: The adjustment of cerebral blood flow leads to changes in the conductivity of the whole brain. Here, whole-brain conductivity measured by the magnetic induction phase shift method is a valuable alternative to cerebral blood volume for non-contact assessment of CVAR. Therefore, we proposed the correlation coefficient between spontaneous slow oscillations in arterial blood pressure and the corresponding magnetic induction phase shift as a novel index called the conductivity reactivity index (CRx). In comparison with the intracranial pressure reactivity index (PRx), the feasibility of the conductivity reactivity index to assess CVAR in the early phase of cerebral ischemia has been preliminarily confirmed in animal experiments. RESULTS: There was a significant difference in the CRx between the cerebral ischemia group and the control group (p = 0.002). At the same time, there was a significant negative correlation between the CRx and the PRx (r = - 0.642, p = 0.002) after 40 min after ischemia. The Bland-Altman consistency analysis showed that the two indices were linearly related, with a minimal difference and high consistency in the early ischemic period. The sensitivity and specificity of CRx for cerebral ischemia identification were 75% and 20%, respectively, and the area under the ROC curve of CRx was 0.835 (SE = 0.084). CONCLUSION: The animal experimental results preliminarily demonstrated that the CRx can be used to monitor CVAR and identify CVAR injury in early ischemic conditions. The CRx has the potential to be used for contactless, global, bedside, and real-time assessment of CVAR of patients with ischemic stroke.

Application of a new self-regulating temperature magnetic material Fe83Zr10B7 in magnetic induction hyperthermia.

INTRODUCTION: The temperature control of magnetic hyperthermia therapy mainly relies on circulating water cooling and regulating magnetic field intensity, which increases complexity in clinical applications. Using magnetic materials with appropriate Curie temperature has become an effective means to solve temperature monitoring and potentially achieve self-regulating temperature. METHODS: A self-temperature-regulating Fe83Zr10B7 magnetic material was prepared. Based on this material, a simplified model of magnetic hyperthermia for arm tumors was established and verified using the finite- element method. The influence of magnetic field intensity and frequency on the heating power and temperature rise rate of different-sized and shaped magnetic media was studied. Additionally, factors such as the size, quantity, and spatial arrangement of the magnetic media were analyzed for their impact on the damage to tumors with different volumes and shapes. RESULTS: Spherical shape is the most suitable for magnetic hyperthermia media, and the radius of the spherical magnetic media can be chosen according to the size of the tumor. For tumors with a radius below 10 mm, using magnetic media with a particle size of 3.5 mm is recommended. The optimal magnetic field conditions are H0 (10-12 kA/m) and f (110-120 kHz). CONCLUSION: Based on the good magnetic properties and heating performance of the Fe83Zr10B7 magnetic material, it is feasible to use it as a magnetic medium for magnetic hyperthermia. The results of this study provide references for the selection of thermal seed size and magnetic field parameters in magnetic hyperthermia.

Magnetic induction heating and drug release properties of magnetic carbon nanotubes.

AIM: The use of magnetic carbon nanotubes for multi-modal cancer treatment, incorporating both hyperthermia and drug delivery functions, has drawn substantial interest. Yet, the present method of regulating hyperthermia temperature involves manually adjusting the magnetic field intensity, adding to the complexity and difficulty of clinical applications. This study seeks to design novel magnetic carbon nanotubes capable of self-temperature regulation, and investigate their drug loading and release characteristics. METHODS: Using the co-precipitation method, we synthesized magnetic carbon nanotubes with a Curie temperature of 43 °C. A comprehensive investigation was conducted to analyze their morphology, crystal structure, and magnetic characteristics. To enhance their functionality, chitosan and sodium alginate modifications were introduced, enabling the loading of the antitumor drug doxorubicin hydrochloride (DOX) into these magnetic carbon nanotubes. Subsequently, the loading and release properties of DOX were investigated within the modified magnetic nanotubes. RESULTS: Under alternating magnetic field, magnetic carbon nanotubes exhibit self-regulating properties by undergoing a magnetic phase transition, maintaining temperatures around 43 °C as required for hyperthermia. On the other hand, during magnetic induction heating, the release percentage of DOX reached 23.5% within 2 h and 71.7% within 70 h at tumor pH conditions, indicating their potential for sustained drug release. CONCLUSIONS: The prepared magnetic carbon nanotubes can effectively regulate the temperature during hyperthermia treatment while ensuring controlled drug release, which presents a promising method for preparing nanomaterials that synergistically enhance magnetic hyperthermia and chemotherapy drugs.

Magnetic Induction Tomography: Separation of the Ill-Posed and Non-Linear Inverse Problem into a Series of Isolated and Less Demanding Subproblems.

Magnetic induction tomography (MIT) is based on remotely excited eddy currents inside a measurement object. The conductivity distribution shapes the eddies, and their secondary fields are detected and used to reconstruct the conductivities. While the forward problem from given conductivities to detected signals can be unambiguously simulated, the inverse problem from received signals back to searched conductivities is a non-linear ill-posed problem that compromises MIT and results in rather blurry imaging. An MIT inversion is commonly applied over the entire process (i.e., localized conductivities are directly determined from specific signal features), but this involves considerable computation. The present more theoretical work treats the inverse problem as a non-retroactive series of four individual subproblems, each one less difficult by itself. The decoupled tasks yield better insights and control and promote more efficient computation. The overall problem is divided into an ill-posed but linear problem for reconstructing eddy currents from given signals and a nonlinear but benign problem for reconstructing conductivities from given eddies. The separated approach is unsuitable for common and circular MIT designs, as it merely fits the data structure of a recently presented and planar 3D MIT realization for large biomedical phantoms. For this MIT scanner, in discretization, the number of unknown and independent eddy current elements reflects the number of ultimately searched conductivities. For clarity and better representation, representative 2D bodies are used here and measured at the depth of the 3D scanner. The overall difficulty is not substantially smaller or different than for 3D bodies. In summary, the linear problem from signals to eddies dominates the overall MIT performance.

A Portable Multi-Modal Cushion for Continuous Monitoring of a Driver's Vital Signs.

With higher levels of automation in vehicles, the need for robust driver monitoring systems increases, since it must be ensured that the driver can intervene at any moment. Drowsiness, stress and alcohol are still the main sources of driver distraction. However, physiological problems such as heart attacks and strokes also exhibit a significant risk for driver safety, especially with respect to the ageing population. In this paper, a portable cushion with four sensor units with multiple measurement modalities is presented. Capacitive electrocardiography, reflective photophlethysmography, magnetic induction measurement and seismocardiography are performed with the embedded sensors. The device can monitor the heart and respiratory rates of a vehicle driver. The promising results of the first proof-of-concept study with twenty participants in a driving simulator not only demonstrate the accuracy of the heart (above 70% of medical-grade heart rate estimations according to IEC 60601-2-27) and respiratory rate measurements (around 30% with errors below 2 BPM), but also that the cushion might be useful to monitor morphological changes in the capacitive electrocardiogram in some cases. The measurements can potentially be used to detect drowsiness and stress and thus the fitness of the driver, since heart rate variability and breathing rate variability can be captured. They are also useful for the early prediction of cardiovascular diseases, one of the main reasons for premature death. The data are publicly available in the UnoVis dataset.

Classification of Shredded Aluminium Scrap Metal Using Magnetic Induction Spectroscopy.

Recycling aluminium is essential for a circular economy, reducing the energy required and greenhouse gas emissions compared to extraction from virgin ore. A 'Twitch' waste stream is a mix of shredded wrought and cast aluminium. Wrought must be separated before recycling to prevent contamination from the impurities present in the cast. In this paper, we demonstrate magnetic induction spectroscopy (MIS) to classify wrought from cast aluminium. MIS measures the scattering of an oscillating magnetic field to characterise a material. The conductivity difference between cast and wrought makes it a promising choice for MIS. We first show how wrought can be classified on a laboratory system with 89.66% recovery and 94.96% purity. We then implement the first industrial MIS material recovery solution for sorting Twitch, combining our sensors with a commercial-scale separator system. The industrial system did not reflect the laboratory results. The analysis found three areas of reduced performance: (1) metal pieces correctly classified by one sensor were misclassified by adjacent sensors that only captured part of the metal; (2) the metal surface facing the sensor can produce different classification results; and (3) the choice of machine learning algorithm is significant with artificial neural networks producing the best results on unseen data.

Development of an HTS-SQUID-Based Receiver for Long-Range Magnetic Induction Communication in Extreme Environments.

The communication range of magnetic-induction (MI) technology in extreme environments such as underwater or underground is limited by the dipole-like attenuation behavior of the magnetic field as well as the eddy current induced loss in conductive media, and therefore a highly sensitive receiver is generally required. In this work, we propose the use of a highly sensitive superconducting quantum interference device (SQUID) in MI communication and try to provide a comprehensive investigation on developing a SQUID-based receiver for practical MI applications. A portable receiver scheme integrating a SQUID sensor and a coil-based flux transformer was proposed. The high sensitivity and long-range communication capability of the proposed receiver was experimentally demonstrated by spectroscopic measurements and reception experiments on a receiver prototype. Based on the experimental demonstrations, the sensitivity optimization of the proposed scheme was further investigated by simulation studies, which suggest that a communication distance exceeding 100 m and a channel capacity of ∼20 kb/s in underwater environment could be achieved based upon the optimization of the developed prototype. The results presented in this work have highlighted the potential of deploying SQUID sensors for long-range MI applications in extreme environments.

Vestibular Extremely Low-Frequency Magnetic and Electric Stimulation Effects on Human Subjective Visual Vertical Perception.

Electric fields from both extremely low-frequency magnetic fields (ELF-MF) and alternating current (AC) stimulations impact human neurophysiology. As the retinal photoreceptors, vestibular hair cells are graded potential cells and are sensitive to electric fields. Electrophosphene and magnetophosphene literature suggests different impacts of AC and ELF-MF on the vestibular hair cells. Furthermore, while AC modulates the vestibular system more globally, lateral ELF-MF stimulations could be more utricular specific. Therefore, to further address the impact of ELF-MF-induced electric fields on the human vestibular system and the potential differences with AC stimulations, we investigated the effects of both stimulation modalities on the perception of verticality using a subjective visual vertical (SVV) paradigm. For similar levels of SVV precision, the ELF-MF condition required more time to adjust SVV, and SVV variability was higher with ELF-MF than with AC vestibular-specific stimulations. Yet, the differences between AC and ELF-MF stimulations were small. Overall, this study highlights small differences between AC and ELF-MF vestibular stimulations, underlines a potential utricular contribution, and has implications for international exposure guidelines and standards. © 2022 Bioelectromagnetics Society.

A Review on Magnetic Induction Spectroscopy Potential for Fetal Acidosis Examination.

Fetal acidosis is one of the main concerns during labor. Currently, fetal blood sampling (FBS) has become the most accurate measurement of acidosis detection. However, it is invasive and does not provide a real time measurement due to laboratory procedures. Delays in diagnosis of acidosis have caused serious injury to the fetus, especially for the brain and the heart. This paper reviews the new technique in diagnosis of acidosis non-invasively. Magnetic Induction Spectroscopy (MIS) has been proposed to be a new device for acidosis detection in recent years. This paper explains the basic principle of MIS and outlines the design specifications and design considerations for a MIS pH probe. It is expected that readers will gain a basic understanding of the development of a MIS pH probe from this review.

A Deep Residual Neural Network for Image Reconstruction in Biomedical 3D Magnetic Induction Tomography.

In recent years, it has become increasingly popular to solve inverse problems of various tomography methods with deep learning techniques. Here, a deep residual neural network (ResNet) is introduced to reconstruct the conductivity distribution of a biomedical, voluminous body in magnetic induction tomography (MIT). MIT is a relatively new, contactless and noninvasive tomography method. However, the ill-conditioned inverse problem of MIT is challenging to solve, especially for voluminous bodies with conductivities in the range of biological tissue. The proposed ResNet can reconstruct up to two cuboid perturbation objects with conductivities of 0.0 and 1.0 S/m in the whole voluminous body, even in the difficult-to-detect centre. The dataset used for training and testing contained simulated signals of cuboid perturbation objects with randomised lengths and positions. Furthermore, special care went into avoiding the inverse crime while creating the dataset. The calculated metrics showed good results over the test dataset, with an average correlation coefficient of 0.87 and mean squared error of 0.001. Robustness was tested on three special test cases containing unknown shapes, conductivities and a real measurement that showed error results well within the margin of the metrics of the test dataset. This indicates that a good approximation of the inverse function in MIT for up to two perturbation objects was achieved and the inverse crime was avoided.

Communication System Based on Magnetic Coils for Underwater Vehicles.

In this work, a wireless communication system based on magnetic coils for underwater vehicles is presented. Firstly, the mathematical model of magnetic field induction using magnetic coils is discussed. Then, a description of the proposed communication system is presented, including the main components of the transmitter and receiver module. The experimental results show that due to the properties of the magnetic field, the proposed communication system can work properly in different environments such as air or water with the same efficiency. Underwater tests were carried out in different water circumstances: varying the temperature in a range from 10 °C to 35 °C, varying concentrations of clay in a range from 0% to 10%, and varying the salinity concentration in a range from 1000 ppm ( parts per million) to 35,000 ppm. It was observed that these conditions do not affect the information transfer. Finally, the advantages of using the proposed system compared to existing submarine communication systems are discussed.

Multi-Frequency Magnetic Induction Tomography System and Algorithm for Imaging Metallic Objects.

Magnetic induction tomography (MIT) is largely focused on applications in biomedical and industrial process engineering. MIT has a great potential for imaging metallic samples; however, there are fewer developments directed toward the testing and monitoring of metal components. Eddy-current non-destructive testing is well established, showing that corrosion, fatigue and mechanical loading are detectable in metals. Applying the same principles to MIT would provide a useful imaging tool for determining the condition of metal components. A compact MIT instrument is described, including the design aspects and system performance characterisation, assessing dynamic range and signal quality. The image rendering ability is assessed using both external and internal object inclusions. A multi-frequency MIT system has similar capabilities as transient based pulsed eddy current instruments. The forward model for frequency swap multi-frequency is solved, using a computationally efficient numerical modelling with the edge-based finite elements method. The image reconstruction for spectral imaging is done by adaptation of a spectrally correlative base algorithm, providing whole spectrum data for the conductivity or permeability.

Application of a Generative Adversarial Network in Image Reconstruction of Magnetic Induction Tomography.

Image reconstruction of Magnetic induction tomography (MIT) is an ill-posed problem. The non-linear characteristics lead many difficulties to its solution. In this paper, a method based on a Generative Adversarial Network (GAN) is presented to tackle these barriers. Firstly, the principle of MIT is analyzed. Then the process for finding the global optimum of conductivity distribution is described as a training process, and the GAN model is proposed. Finally, the image was reconstructed by a part of the model (the generator). All datasets are obtained from an eight-channel MIT model by COMSOL Multiphysics software. The voltage measurement samples are used as input to the trained network, and its output is an estimate for image reconstruction of the internal conductivity distribution. The results based on the proposed model and the traditional algorithms were compared, which have shown that average root mean squared error of reconstruction results obtained by the proposed method is 0.090, and the average correlation coefficient with original images is 0.940, better than corresponding indicators of BPNN and Tikhonov regularization algorithms. Accordingly, the GAN algorithm was able to fit the non-linear relationship between input and output, and visual images also show that it solved the usual problems of artifact in traditional algorithm and hot pixels in L2 regularization, which is of great significance for other ill-posed or non-linear problems.

Induced Magnetic Field-Based Indoor Positioning System for Underwater Environments.

Autonomous underwater vehicles (AUV) are seen as an emerging technology for maritime exploration but are still restricted by the availability of short range, accurate positioning methods necessary, e.g., when docking remote assets. Typical techniques used for high-accuracy positioning in indoor use case scenarios, such as systems using ultra-wide band radio signals (UWB), cannot be applied for underwater positioning because of the quick absorption of the positioning medium caused by the water. Acoustic and optic solutions for underwater positioning also face known problems, such as the multi-path effects, high propagation delay (acoustics), and environmental dependency. This paper presents an oscillating magnetic field-based indoor and underwater positioning system. Unlike those radio wave-based positioning modalities, the magnetic approach generates a bubble-formed magnetic field that will not be deformed by the environmental variation because of the very similar permeability of water and air. The proposed system achieves an underwater positioning mean accuracy of 13.3 cm in 2D and 19.0 cm in 3D with the multi-lateration positioning method and concludes the potential of the magnetic field-based positioning technique for underwater applications. A similar accuracy was also achieved for various indoor environments that were used to test the influence of cluttered environment and of cross environment. The low cost and power consumption system is scalable for extensive coverage area and could plug-and-play without pre-calibration.