Magnetometer Research Articles

Reducing equivalent magnetic noise by electrode design and magnetic annealing in Quartz/Metglas magnetoelectric sensors

Magnetoelectric (ME) composites are promising for the development of high-performance magnetometers due to their high sensitivity, low cost, low power consumption, and small size. Enhancing the ME coefficient while reducing the background noise is an effective method to improve the performance of ME sensors, which remains challenging. In this work, we propose a method to reduce the equivalent magnetic noise by optimizing the electrode design and the magnetic annealing process in magnetoelectric quartz/Metglas composites. Compared with the non-optimized ME composites, the ME coefficient increases by 1.38 times while the background noise decreases by about 0.78 times, resulting in a LoD of 10 fT at resonance. Due to the high ME coefficient and low background noise, the equivalent magnetic noise from 20 kHz to 50 kHz was less than 6.10 pT/Hz1/2. The results show that proper annealing treatment of Metglas is beneficial for improving the soft magnetic properties. Meanwhile, the hollow electrode of quartz can reduce the equivalent capacitance and enhance the quality factor of the piezoelectric layer. This work demonstrates a feasible way to enhance the performance of ME magnetic field sensors.

A Robust Tri-Electromagnet-Based 6-DoF Pose Tracking System Using an Error-State Kalman Filter.

Magnetic pose tracking is a non-contact, accurate, and occlusion-free method that has been increasingly employed to track intra-corporeal medical devices such as endoscopes in computer-assisted medical interventions. In magnetic pose-tracking systems, a nonlinear estimation algorithm is needed to recover the pose information from magnetic measurements. In existing pose estimation algorithms such as the extended Kalman filter (EKF), the 3-DoF orientation in the S3 manifold is normally parametrized as unit quaternions and simply treated as a vector in the Euclidean space, which causes a violation of the unity constraint of quaternions and reduces pose tracking accuracy. In this paper, a pose estimation algorithm based on the error-state Kalman filter (ESKF) is proposed to improve the accuracy and robustness of electromagnetic tracking systems. The proposed system consists of three electromagnetic coils for magnetic field generation and a tri-axial magnetic sensor attached to the target object for field measurement. A strategy of sequential coil excitation is developed to separate the magnetic fields from different coils and reject magnetic disturbances. Simulation and experiments are conducted to evaluate the pose tracking performance of the proposed ESKF algorithm, which is also compared with standard EKF and constrained EKF. It is shown that the ESKF can effectively maintain the quaternion unity and thus achieve a better tracking accuracy, i.e., a Euclidean position error of 2.23 mm and an average orientation angle error of 0.45°. The disturbance rejection performance of the electromagnetic tracking system is also experimentally validated.

Cilia-Inspired Magnetic Flexible Shear Force Sensors for Tactile and Fluid Monitoring.

Recently, there has been a burgeoning interest in flexible shear force sensors capable of precisely detecting both magnitude and direction. Despite considerable efforts, the challenge of achieving accurate direction recognition persists, primarily due to the inherent structural characteristics and sensing mechanisms. Here, we present a shear force sensor constructed by a magnetically induced assembled Ni/PDMS composite membrane, which is magnetized and integrated with a three-axis Hall sensor, facilitating its ability to simultaneously monitor both shear force magnitude (0.7-87 mN) and direction (0-360°). The cilia-inspired shear force magnetic sensor (CISFMS) exhibits admirable attributes, including exceptional flexibility, high sensitivity (0.76 mN-1), an exceedingly low detection limit (1° and 0.7 mN), and remarkable durability (over 10,000 bending cycles). Further, our results demonstrate the capacity of the CISFMS in detecting tactile properties, fluid velocity, and direction, offering substantial potential for future developments in wearable electronics.

Epitaxial growth of quasi-2D van der Waals ferromagnets on crystalline substrates

Intrinsic magnetism in van der Waals materials has instigated interest in exploring magnetism in the 2D limit for potential applications in spintronics and also in understanding novel control of 2D magnetism via variation of layer thickness, gate tunability and magnetoelectric effects. The chromium telluride (CrxTey) family is an interesting subsection of ferromagnetic materials with highTCvalues, also presenting diverse stoichiometry arising from self-intercalation of Cr. Apart from the layered CrTe2system, the other non-layered CrxTeycompounds also offer exceptional magnetic properties, and a novel growth technique to grow thin films of these non-layered compounds offers exciting possibilities for ultra-thin spin-based electronics and magnetic sensors. In this work, we discuss the role of crystalline substrates in chemical vapor deposition growth of non-layered 2D ferromagnets, where the crystal symmetry of the substrate as well as the misfit and strain are the key players governing the growth mechanism of ultra-thin Cr5Te8, a non-layered ferromagnet. The magnetic studies of the as-grown Cr5Te8reveal the signatures of co-existing soft and hard ferromagnetic phases, which makes this system an intriguing system to search for emergent topological phases, such as magnetic skyrmions.

Unusual inverse spin Hall effect in Pt/Co/Pt multilayers on single-crystalline YIG

The inverse spin Hall effect (ISHE) is a significant phenomenon that enables the conversion of spin current into charge current, offering promising applications in novel spintronic devices. In conventional ISHE measurements, it is widely recognized that the spin polarization, spin current, and generated charge current are mutually perpendicular. This study systematically investigates the ISHE in Pt/Co/Pt multilayers grown on a single-crystalline yttrium iron garnet (YIG) layer. A non-zero ISHE voltage was obtained along the direction parallel to the external magnetic field within the YIG coercive field range, deviating from the classical ISHE behavior. Our investigation revealed that the in-plane magnetic anisotropy of single-crystalline YIG plays a crucial role, as the easy axis of YIG and the external magnetic field collaboratively determine the polarization direction of the spin current, especially when the external magnetic field is smaller than the YIG coercive force. Furthermore, by tuning the small in-plane magnetization component of the Pt/Co/Pt multilayers, which couples with the YIG magnetization, we were able to control the shape and reversal path of the ISHE voltage loop. These findings deepen our understanding of how magnetic order affects charge current flow in ISHE measurements. The variety of ISHE voltage loop shapes and reversal paths observed suggest potential applications for this device as a magnetic field sensor.

Magnetic induction sensor based on a dual-frequency atomic magnetometer

Magnetic induction sensor based on a dual-frequency atomic magnetometer

Recording of ultra-low frequency electromagnetic emission during loading of a rock sample

The review of publications devoted to the study and features of the registration of electromagnetic emission observed during the loading of samples of rocks, metals, composite materials in laboratory conditions, as well as in areas of disintegration of rock massifs at mining sites is given. Electromagnetic emission observed during the destruction of rock samples in laboratory experiments and field conditions can appear itself not only in the high and low frequency ranges (1000–3·106 Hz and 500–1000 Hz, respectively), but also in the very low and ultra-low frequency (200–500 Hz and 0.01–200.00 Hz, respectively) ranges. However, the overwhelming majority of experimental studies of rock samples under the influence of a destructive load in laboratory conditions are aimed at measuring electromagnetic emission of the high frequency range. An instrumentation and measurement complex is described that allows recording electromagnetic emission in the ultra-low frequency range. The composition of the instrumentation and measurement complex includes magnetic modulation transducers of magnetic induction as magnetic field sensors. The methodology of laboratory experiments on recording electromagnetic signals arising from the influence of an external load on rock samples using an instrumentation and measuring complex is presented. An example of uniaxial loading of a basalt sample is given. When loading the sample under consideration, the amplitude of the electromagnetic emission pulses exceeds the background values of technogenic magnetic noise by two orders of magnitude. The high sensitivity of the magnetic modulation transducer of magnetic induction allows it to be used to register the components of magnetic induction in the process of destruction of rock samples in conditions of interference from technogenic magnetic noise. The results obtained are important for monitoring and forecasting the process of cracking before mining impacts, as well as for studying the geological environment and processes that generate low-frequency electromagnetic emission in the mining areas.

Vector magnetic field measurement based on fiber ring microwave photonic filter with the Vernier effect

A vector magnetic field sensor based on enhanced Vernier effect is experimentally demonstrated. The Vernier effect is generated from two microwave photonic filters (MPFs) with close free spectral range (FSR), which is constructed by the fiber ring (FR) and the optical carrier microwave interferometry (OCMI). Linear chirped fiber Bragg grating (LCFBG) is inserted in the FR to act as the dispersion element to provide time delay. By attaching the fiber Bragg grating (FBG) on the magnetostrictive material (MA), the magnetic field can be transferred into the wavelength shift, as well as the time delay of the FR and the frequency response of the FR-MPF. By choosing opposite dispersion of LCFBGs and closer FSRs, cascaded FR-MPFs based sensor can greatly improve the sensitivity. The sensitivities for the magnetic field intensity and direction are 127.71 kHz/Oe, the magnification factor of which is 432, and 418.16 kHz/deg. The proposed scheme has merits of high sensitivity and interference immunity, which is suitable for high precision measurement.

Low Temperature Plasma-Assisted Double Anodic Dissolution: A New Approach for the Synthesis of GdFeO3 Perovskite Nanoparticles.

Orthorhombic perovskite GdFeO3 nanostructures are promising materials with multiferroic properties. In this study, a new low-temperature plasma-assisted approach is developed via dual anodic dissolution of solid metallic precursors for the preparation of perovskite GdFeO3 nanoparticles (NPs) that can be collected both as colloids as well as deposited as a thin film on a substrate. Two solid metallic foils of Gd and Fe are used as precursors, adding to the simplicity and sustainability of the method. The formation of the orthorhombic perovskite GdFeO3 phase is supported by high-resolution transmission electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, and Raman measurements, while a uniform elemental distribution of Gd, Fe, and O is confirmed by energy dispersive X-ray spectroscopy, proving the successful preparation of ternary compound NPs. The magnetic properties of the NPs show zero remnant magnetization typical of antiferromagnetic materials, and saturation at high fields that can be caused by spin interaction between Gd and Fe magnetic sublattices. The formation mechanism of ternary compound NPs in this novel plasma-assisted method is also discussed. This method is also modified to demonstrate the direct one-step deposition of thin films, opening up opportunities for their future applications in the fabrication of magnetic memory devices and gas sensors.

Micro magnetic field sensor based on bifunctional diodes

Multiple-quantum well (MQW) diodes can be used as bifunctional diodes due to the emission-detection spectral overlap. When integrated with magnetic fluids (MFs) that have tunable refractive index, they can be designed as micro magnetic field sensors. The sapphire substrate of the MQW diode chip that consists of an MQW transmitter and receiver that is directly exposed to the MF, and the external magnetic field strength is used to change the refractive index at the boundary between the sapphire and the MF, thus modulating the reflected light and realizing external magnetic field sensing. Verified by experimental measurements, the micromagnetic field sensor has a detection range of 0.001-0.05 T, a sensitivity of 127.3 µA/T, and a resolution of 4.5×10−5 T, with excellent stability and repeatability. Additionally, the sensor demonstrates good velocity resolution under dynamic magnetic fields and can detect the direction of magnetic field motion, providing significant application value.

Magnetic field sensor based on one-dimensional binary photonic crystal

The work describes the study of a 1D photonic crystal to detect the magnetic fluid as a function of temperature and magnetic field. The structural dimensions are designed by incorporating alternating layers in a periodic way. Each layer is formed as a pair, in which a combination of two materials, PbS and air, is made with a thickness of 91 nm and 387 nm. Along with the structure, there is another mode called the defect mode, with a thickness of 277.5 nm, where the detecting magnetic fluid is injected. The overall PC structure is characterized by the transfer matrix method (TMM), whose results in the transmission spectrum as a function of wavelength are analyzed theoretically. In response to the magnetic fluid, the defect mode is generated and meets resonance at a particular wavelength. The change in shift for magnetic fluid gives the results for sensor performances. In particular, the proposed sensor is optimized by its structural perceptions, and its sensitivity is identified for both magnetic field and temperature through the absorption of magnetic fluid. The study of the temperature dependence of magnetic fluid is carried out at high temperatures up to 500 K. The sensitivity is calculated by noting the shift in defect mode for various incident angles, thicknesses, and temperatures. An increase in the angle of incidence improves both the sensitivity and FOM. The maximum sensitivity achieved, which depends on magnetic field and temperature, is 31.2 pm Oe−1 and 6.46 pm K−1, respectively, for a thickness of 305.25 nm at an angle of incidence of 50°. A maximum FOM of 57.884 Oe−1 is also achieved at an incident angle of 50° and a temperature 300 K. The work’s findings suggest developing prospective photonic devices, and the proposed PC has dual sensor characteristics that may be tuned.

Biosensing Technologies for Detecting Legionella in Environmental Samples: A Systematic Review.

The detection of Legionella in environmental samples, such as water, is crucial for public health monitoring and outbreak prevention. Although effective, traditional detection methods, including culture-based techniques and polymerase chain reaction, have limitations such as long processing times, trained operators, and the need for specialized laboratory equipment. Biosensing technologies offer a promising alternative due to their rapid, sensitive, cost-effectiveness, and on-site detection capabilities. To summarize the current advancements in biosensor development for detecting Legionella in environmental samples, we used 'Legionella' AND 'biosensors' NEAR 'environmental samples' OR 'water' as keywords searching through the most relevant biomedical databases for research articles. After removing duplicates and inadequate articles from the n.1268 records identified using the PRISMA methodology exclusion criteria, we selected n.65 full-text articles which suited the inclusion criteria. Different results between the studies describing the current biosensing techniques, including optical, electrochemical, magnetic, and mass-sensitive sensors were observed. For each biosensing technique, sensitivity, specificity, and detection limits were evaluated. Furthermore, the integration of nanomaterials, microfluidics, and portable devices in biosensor systems' design were discussed, highlighting their role in enhancing detection performance. The potential challenges and future directions in the field of Legionella biosensing were also addressed, providing insights into the feasibility of implementing these technologies in routine environmental monitoring. Undoubtedly, biosensors can play a crucial role in the early detection and management of Legionella infections and outbreaks, ultimately protecting public health and safety.

Magnetic Sensor Array for Electric Arc Reconstruction in Circuit Breakers.

Noninvasive imaging of circuit breakers under short-circuit testing is addressed by recording the magnetic field produced over an array of external sensors and by solving an inverse problem to identify the causing current distribution. The temporal and spatial resolution of the sensing chain are studied and implemented in a physical set-up. A wire model is adopted to describe electrical current distribution. Additionally, the simpler, more direct approach to evaluating the passage of electric current in front of sensors is proposed. The dynamics of suitable approximating models of the electric arc that forms across contacts is obtained and agrees with multi-physical simulations and with experimental time histories of current and voltage. The two methods are flexible and allow the analysis of different types of circuit breakers.

Void fraction measurement of slug flow using electromagnetic wave phase sensor based on optimized hybrid dielectric constant

The void fraction is one of the basic parameters to study the gas-liquid two-phase flow, which has great significance to the transportation of oil pipelines and the design of nuclear reactor cooling towers. However, due to the complex and variable nature of gas-liquid two-phase flow, accurately measurement of the void fraction has remained a challenging task in both scientific research and industrial applications. According to the principle of electromagnetic wave propagation, a coaxial line phase sensor was designed, a hybrid dielectric constant model based on the homogeneous flow was established and a void fraction based on hybrid dielectric constant model was proposed. The experiments were carried out on the high-precision gas-liquid two-phase flow simulation experimental setup at Hebei University, China (70 data points), and the void fraction model was inspected and verified. Five typical hybrid dielectric constant correlations were compared. Introducing the frequency weight, optimizing the hybrid dielectric constant model based on the Series – Parallel correlation, a new void fraction prediction correlation of slug flow was proposed and evaluated. The results indicated that the mean absolute percentage error (MAPE) of the new void fraction correlation is 1.02 % and the all of the relative errors are within ±5 % error band.

A quantum-enhanced magnetometer using a single high-spin nucleus in silicon

Abstract Quantum enhanced metrology has the potential to go beyond the standard quantum limit and eventually to the ultimate Heisenberg bound. In particular, quantum probes prepared in nonclassical coherent states have recently been recognized as a useful resource for metrology. Hence, there has been considerable interest in constructing magnetic quantum sensors that combine high resolution and high sensitivity. Here, we explore a nanoscale magnetometer with quantum-enhanced sensitivity, based on 123Sb (I = 7/2) nuclear spin doped in silicon, that takes advantage of techniques of spin-squeezing and coherent control. With the optimal squeezed initial state, the magnetic field sensitivity may be expected to approach 6 aT⋅Hz−1/2⋅cm−3/2 and 603 nT⋅Hz−1/2 at the single-spin level. This magnetic sensor may provide a novel sensitive and high-resolution route to microscopic mapping of magnetic fields as well as other applications.

Artificial Intelligence Using FFNN Models for Computing Soil Complex Permittivity and Diesel Pollution Content

Soil pollution caused by hydrocarbons, such as diesel, poses significant risks to both human health and the ecosystem. The evaluation of soil pollution and various soil engineering applications often relies on the analysis of complex permittivity, encompassing parameters such as dielectric constant and dielectric loss. Various computational models, including theoretical physics-based models, mixture theory models, statistical empirical models, and artificial neural network (ANN) models, have been explored for computing soil complex permittivity and predicting water and pollutant content. Theoretical models require detailed data that is often unavailable, and thus have limited applicability. Mixture models tend to underestimate soil characteristics due to inaccuracies in permittivity estimation of soil phases. While empirical models are widely used, their applicability is restricted to specific soil types, datasets, and locations. ANN models offer promising predictions, accommodating nonlinear phenomena and allowing for missing information and variables. In this study, capacitive electromagnetic electrode sensors were utilized to determine the complex permittivity of soil contaminated with varying levels of diesel at different moisture levels. Theoretical mixture, empirical, and Feed Forward Neural Network (FFNN) models were employed to compute the permittivity of polluted soil based on its phases and to predict the level of diesel pollution. A comparison of these modeling approaches revealed that the FFNN model exhibited the best performance. The ANN model demonstrated superior performance metrics, including a high correlation coefficient and lower mean square error. Specifically, the correlation coefficients for the FFNN model were 0.9942 for training samples, 0.9967 for validation samples, and 0.9977 for test samples. Additionally, the ANN model yielded the lowest mean square error compared to the other three models. Doi: 10.28991/CEJ-2024-010-09-018 Full Text: PDF

Monte Carlo simulations unveil magnetic differences in honeycomb, kagome, and triangular nanolattices

Monte Carlo simulations reveal distinct magnetic behaviors in honeycomb, kagome, and triangular nanolattices, crucial for magnetic material development. The honeycomb nanolattice shows the earliest magnetization decline, followed by the kagome and triangular nanolattices, due to differences in atomic arrangement and geometry. Increasing the linear coupling interaction (J), biquadratic coupling interaction (K), and external magnetic field raises the blocking temperature, while a higher crystal field (∣D∣) lowers it. These findings are pivotal for optimizing magnetic stability and behavior in applications like magnetic storage, sensors, and nanotechnologies.

Fiber Magnetic Field Sensor With Extended Linear Measuring Range Based on Magneto-Shape Effect

Fiber Magnetic Field Sensor With Extended Linear Measuring Range Based on Magneto-Shape Effect

Magnetic Porous Hydrogel-Enhanced Wearable Patch Sensor for Sweat Zinc Ion Monitoring.

Wearable sensors for sweat trace metal monitoring have the challenges of effective sweat collection and the real-time recording of detection signals. The existing detection technologies are implemented by generating enough sweat through exercise, which makes detecting trace metals in sweat cumbersome. Generally, it takes around 20 min to obtain enough sweat, resulting in dallied and prolonged detection signals that cannot reflect the endogenous fluctuations of the body. To solve these problems, we prepared a multifunctional hydrogel as an electrolyte and combined it with a flexible patch electrode to realize real-time monitoring of sweat Zn2+. Such hydrogel has magnetic and porous properties, and the porous structure of hydrogel enables a fast absorption of sweat, and the magnetic property of the addition of fabricated Fe3O4 NPs not only improves the conductivity but also ensures the adjustable internal structures of the hydrogel. Such a sensing platform for sweat Zn2+ monitoring shows a satisfied linear relationship in the concentration range of 0.16-16 µg/mL via differential pulsed anodic striping voltammetry (DPASV) and successfully detects the sweat Zn2+ of four volunteers during exercise and resting, displaying a promising path for commercial application.

Research and Improvement in Magnetic Field Sensors Using Mach–Zehnder Interferometer with Cobalt Ferrite Nanoparticles

Research and Improvement in Magnetic Field Sensors Using Mach–Zehnder Interferometer with Cobalt Ferrite Nanoparticles