Search Results (219)

Acute myocardial infarction (AMI) is a rapidly progressing cardiovascular condition associated with high mortality. Myoglobin is an early biomarker of AMI; however, its detection using conventional methods is limited by complex workflows and low resistance to interference. In this study, we developed an integrated myoglobin detection platform that combined magneto-immunoassay with microfluidic technology. A giant magnetoresistance (GMR) sensor was fabricated using micro-electro-mechanical systems (MEMS). The designed microfluidic chip integrated sample pretreatment, immunoreaction, and magnetic signal capture functionalities. Its built-in GMR sensor, labeled with magnetic nanoparticles, directly converted the “antigen–antibody” biochemical signal into detectable magnetoresistance changes, thereby enabling the indirect detection of myoglobin. A magneto-immunoassay analysis system consisted of a fluidic drive, magnetic field control, and data acquisition functions. Various key parameters were optimized, including EDC/NHS concentration, antibody concentration, and magnetic bead size. Under the optimal conditions and using 1 μm magnetic beads as labels and an external detection magnetic field of 60 Oe, the platform successfully detected myoglobin at 75 ng/mL with ∆MR ≥ 0.202%. Specificity tests demonstrated that the platform had high specificity for myoglobin and could effectively distinguish myoglobin from bovine serum albumin (BSA) and troponin I. This study presents a rapid, accurate myoglobin detection platform that can be applied for the early diagnosis of AMI. Full article

Our team has initiated work to determine residual stresses by means of monitoring magnetic properties, namely differential permeability, magnetoacoustic emission, and surface field components. Concerning surface field measurements, Hall, AMR, and TMR sensors have been used, with AMR and TMR sensors enabling 3D field determination. In this paper, we compare the surface magnetic field components with residual stresses in 2 mm thick AISI 4130 steel coupons. The steel samples were in a dog-bone structure with residual stresses induced by localized RF induction heating to create a temperature gradient, followed by quenching to transform the temperature gradient into a residual stress one. GMI and AMR sensors were used to determine the localized magnetic field component distribution on the surface of the steel coupons and at the same areas where the residual stresses were determined. The GMI sensor was able to monitor the field component perpendicular to the surface of the steel coupon, while the AMR sensor was able to monitor the three field components at the same points. The results illustrated that both sensors were able to monitor residual stresses, with the GMI sensor illustrating better sensitivity at a higher cost, while the AMR sensor had a lower sensitivity with a significantly lower cost as an integrated sensor. Full article

This paper proposes an integrated sensor for voltage and current distribution network insulators, based on electric field coupling and TMR magnetic sensing, to address the issues of traditional voltage and current separation measurement, insulator safety after primary and secondary fusion, uncertainty in voltage measurement gain, and interference resistance in TMR current measurements. Through simulation and optimization, the design of the embedded voltage-sensing unit in the insulator is achieved, ensuring uniform electric field distribution, determining the transfer function, and minimizing partial discharge, thereby ensuring insulator safety and improving voltage measurement accuracy. Additionally, a self-integrating circuit design is used to widen the low-frequency dynamic range and increase the voltage division ratio. Moreover, an open-type two-stage magnetic ring current sensor based on TMR is proposed, with optimized magnetic ring dimensions to detect currents from low to medium ranges, addressing eccentricity errors and improving sensitivity, immunity to interference, and magnetic field uniformity. The experimental results show that this integrated sensor can effectively ensure measurement accuracy, stability, and dynamic range. Full article

A state-of-the-art tunnel magnetoresistance (TMR) sensor architecture, which is based on the perpendicularly magnetized magnetic tunnel junction (pMTJ), is introduced and engineered for ultrafast, high thermal stability, and linearity for magnetic field detection. Limitations in high-frequency environments, stemming from insufficient thermal stability and slow recovery times in conventional TMR sensors, are overcome by this approach. The standard MRAM structure is modified, and the Ruderman–Kittel–Kasuya–Yosida (RKKY) interaction is employed to give a strong, internal restoring torque to the storage layer magnetization. Sensor linearity is also ensured by this RKKY mechanism, and rapid relaxation to the initial spin state is observed when an external field is removed. The structural and magnetic properties of the multilayer stack are experimentally demonstrated. Robust synthetic antiferromagnetic (SAF) coupling is confirmed by using polar MOKE spectroscopy with an optimal Ru insertion layer thickness (0.6 nm), which is essential for high thermal stability. Subsequently, an ultrafast response of this TMR sensor architecture is probed by micromagnetic simulations. The storage layer magnetization rapidly recovers to the SAF state within an ultrashort time of 5.78 to 5.99 ns. This sub-6 ns recovery time scale suggests potential operation into the hundreds of MHz range. Full article

The intrinsic noise of giant magnetoresistive (GMR) sensors is large at low frequencies, and their resolution is inevitably significantly limited. Investigation of GMR noise requires the use of measurement systems that have lower noise than the sample. In this context, the main purpose of this study is to evaluate the effectiveness of two electronic noise measurement configurations of a single GMR sensing element. The first method connects the sample in a voltage divider configuration and the second method connects in a Wheatstone bridge configuration. Three amplification set-ups were investigated: a low-noise amplifier, an ultra-low-noise amplifier and an instrumentation amplifier. Using cross-correlation, the noise of the measurement system introduced by the amplifiers was reduced. Noise spectra were recorded at room temperature in the frequency range of 0.5 Hz to 10 kHz, under different sample bias voltages. The measurements were performed in zero applied magnetic field and in a field corresponding to the maximum sensitivity of the sensor. From the noise spectra, the detectivity of the sensor was determined to be in the 200–300 nT/√Hz range. Good agreement was observed between the results obtained using all three set-ups, suggesting the effectiveness of the noise measurement systems applied to the magnetoresistive sensor. Full article

Tree diameter at breast height (DBH) and tree height are important quantitative attributes in forestry surveys. They serve as essential data for calculating forest stock, growth, and carbon sequestration, and are of significant research value for forest health assessments and other research outcomes. To improve the efficiency of forest resource inventories and to reduce labor costs, a forestry survey device integrating multiple sensors has been developed. Based on the principles of laser ranging and the tunnel magnetoresistance effect, this device integrates both the DBH and tree height measurements. Compared to traditional measurement methods, it boasts a compact size, low cost, and high measurement accuracy. Experimental applications have shown that the average root mean square error (RMSE) of tree height measurements ranges from 31 to 55 cm, while the DBH measurement accuracy reaches 98%, We acknowledge that, although this accuracy meets the requirements for general forestry surveys, it still falls short of the accuracy required for high-precision forest resource surveys (<20 cm), which points to a direction for future improvement. Full article

This article introduces a novel, cost-effective, noninvasive sensing mechanism for measuring water flow rate. It employs two tunneling magnetoresistance (TMR) sensors (analog and bi-polar), a magnet, and a stainless-steel cantilever. The TMR sensors are installed outside the insulating water pipe. A magnet is fixed at the free end of the cantilever and integrated into the pipe system. The cantilever’s deflection corresponds to the flow rate, with an analog TMR sensor measuring the bending angle. This bending angle, in either direction of the cantilever’s deflection, is captured through the analog voltage from the TMR sensor. The output from the analog TMR sensor is an analog voltage that directly reflects the strength of the magnetic field. An ESP32 microcontroller records the voltage from the analog TMR sensor, converts it to flow rates, and utilizes the bi-polar TMR sensor to ascertain the flow direction. A prototype sensor was developed and tested in a laboratory-scale setup to validate the effectiveness of the sensing mechanism. This prototype demonstrated a worst-case accuracy of 1.0% across flow rates of 0 to 1.5 m³/h for both the forward and reverse flow directions. The response and recovery times of the sensor are approximately 470 ms and 592 ms for forward and 487 ms and 625 ms for reverse direction flow. Also, hysteresis errors of 1.84% and 2.06% have been calculated for both flow directions. Notably, the sensing element does not contain any rotating components or require electrical connections to the cantilever for measurement. These attributes potentially lead to lower maintenance requirements and a longer lifespan for the sensor. Full article

Magnetic tunnel junctions (MTJs) are pivotal for spintronic applications such as magneto resistive memory and sensors. Two-dimensional van der Waals heterostructures offer a promising platform for miniaturizing MTJs while enabling the twist-angle engineering of their properties. Here, we investigate the impact of twisting the insulating barrier layer on the performance of a van der Waals MTJ with the structure graphene/1T-VSe₂/h-BN/1T-VSe₂/graphene, where 1T-VSe₂ serves as the ferromagnetic electrodes and the monolayer h-BN acts as the tunnel barrier. Using first-principles calculations based on density functional theory (DFT) combined with the non-equilibrium Green’s function (NEGF) formalism, we systematically calculate the spin-dependent transport properties for 18 distinct rotational alignments of the h-BN layer (0° to 172.4°). Our results reveal that the tunneling magnetoresistance (TMR) ratio exhibits dramatic, rotation-dependent variations, ranging from 2328% to 24,608%. The maximum TMR occurs near 52.4°. An analysis shows that the twist angle modifies the d-orbital electronic states of interfacial V atoms in the 1T-VSe₂ layers and alters the spin polarization at the Fermi level, thereby governing the spin-dependent transmission through the barrier. This demonstrates that rotational manipulation of the h-BN layer provides an effective means to engineer the TMR and performance of van der Waals MTJs. Full article

Measuring weak magnetic fields proposes significant challenges to the sensing capabilities of magnetic field sensors. The magnetic field detection capacity of tunnel magnetoresistance (TMR) sensors is often insufficient for such applications, necessitating targeted optimization strategies to improve their performance in weak-field measurements. Utilizing magnetic flux concentrators (MFCs) offers an effective approach to enhance TMR sensitivity. In this study, the finite element method was employed to analyze the effects of different MFC geometric structures on the uniformity of the magnetic field in the air gap and the magnetic circuit gain (MCG). It was determined that the MCG of the MFC is not directly related to the absolute values of its parameters but rather to their ratios. Simulation analyses evaluated the impact of these parameter ratios on both the MCG and its spatial distribution uniformity, leading to the formulation of MFC design optimization principles. Building on these simulation-derived principles, several MFCs were fabricated using the 1J85 material, and an experimental platform was established to validate the simulation findings. The fabricated MFCs achieved an MCG of 7.325 times. Based on the previously developed TMR devices, a detection sensitivity of 2.46 nT/$\sqrt{\mathrm{Hz}}$ @1Hz was obtained. By optimizing parameter configurations, this work provides theoretical guidance for further enhancing the performance of TMR sensors in magnetic field measurements. Full article

Magnetocardiography (MCG) provides a non-invasive, contactless technique for evaluating the magnetic fields generated by cardiac electrical activity, offering unique spatial insights into cardiac electrophysiology. However, conventional MCG systems depend on superconducting quantum interference devices that require cryogenic cooling and magnetic shielded environments, posing considerable impediments to widespread clinical adoption. In this study, we present a novel MCG system utilizing a high-sensitivity, wide-dynamic-range magnetoresistive sensor array operating at room temperature. To mitigate environmental interference, identical sensors were deployed as reference channels, enabling adaptive noise cancellation (ANC) without the need for traditional magnetic shielding. MCG recordings were obtained from 40 healthy participants, with signals processed using ANC, R-peak-synchronized averaging, and Bayesian spatial signal separation. This approach enabled the reliable detection of key cardiac components, including P, QRS, and T waves, from the unshielded MCG recordings. Our findings underscore the feasibility of a cost-effective, portable MCG system suitable for clinical settings, presenting new opportunities for noninvasive cardiac diagnostics and monitoring. Full article

Mechanical defects and sensor failures can substantially undermine the reliability of low-cost sensors, especially in applications where measurement inaccuracies or malfunctions may lead to critical outcomes, including system control disruptions, emergency scenarios, or safety hazards. To overcome these challenges, this paper presents a novel Self-X architecture with sensor redundancy, which incorporates dynamic calibration based on multidimensional mapping. By extracting reliable sensor readings from imperfect or defective sensors, the system utilizes Self-X principles to dynamically adapt and optimize performance. The approach is initially validated on synthetic data from tunnel magnetoresistance (TMR) sensors to facilitate method analysis and comparison. Additionally, a physical measurement setup capable of controlled fault injection is described, highlighting practical validation scenarios and ensuring the realism of synthesized fault conditions. The study highlights a wide range of potential TMR sensor failures that compromise long-term system reliability and demonstrates how multidimensional mapping effectively mitigates both static and dynamic errors, including offset, amplitude imbalance, phase shift, mechanical misalignments, and other issues. Initially, four individual TMR sensors exhibited mean absolute error (MAE) of 4.709°, 5.632°, 2.956°, and 1.749°, respectively. To rigorously evaluate various dimensionality reduction (DR) methods, benchmark criteria were introduced, offering insights into the relative improvements in sensor array accuracy. On average, MAE was reduced by more than 80% across sensor combinations. A clear quantitative trend was observed: for instance, the MAE decreases from 4.7°–5.6° for single sensors to 0.111° when the factor analysis method was applied to four sensors. This demonstrates the concrete benefit of sensor redundancy and DR algorithms for creating robust, fault-tolerant measurement systems. Full article

Touch is a crucial sense for advanced organisms, particularly humans, as it provides essential information about the shape, size, and texture of contacting objects. In robotics and automation, the integration of tactile sensors has become increasingly relevant, enabling devices to properly interact with their environment. This study aimed to develop a biomimetic, skin-inspired tactile sensor device capable of sensing applied force, characterizing it in three dimensions, and determining the point of application. The device was designed as a 4 × 4 matrix of tunneling magnetoresistive sensors, which provide a higher sensitivity in comparison to the ones based on the Hall effect, the current standard in tactile sensors. These detect magnetic field changes along a single axis, wire-bonded to a PCB and encapsulated in epoxy. This sensing array detects the magnetic field from an overlayed magnetorheological elastomer composed of Ecoflex and 5 µm neodymium–iron–boron ferromagnetic particles. Structural integrity tests showed that the device could withstand forces above 100 N, with an epoxy coverage of 0.12 mL per sensor chip. A 3D movement stage equipped with an indenting tip and force sensor was used to collect device data, which was then used to train neural network models to predict the contact location and 3D magnitude of the applied force. The magnitude-sensing model was trained on 31,260 data points, being able to accurately characterize force with a mean absolute error ranging between 0.07 and 0.17 N. The spatial sensitivity model was trained on 171,008 points and achieved a mean absolute error of 0.26 mm when predicting the location of applied force within a sensitive area of 25.5 mm × 25.5 mm using sensors spaced 4.5 mm apart. For points outside the testing range, the mean absolute error was 0.63 mm. Full article

Gear condition monitoring is predominantly executed through the utilization of acceleration sensors positioned on the housing. However, recent advancements have identified measuring the instantaneous angular speed as a compelling alternative as it shortens the transmission path and therefore provides high-quality rotational angle information that can be used to increase damage prediction accuracy, particularly under transient operating conditions. Additionally, there are a variety of methodologies for integrating sensors into gears, which underscores the necessity for high-quality condition data. However, it should be noted that a significant amount of effort is required to successfully integrate these sensors into the rotating system. This publication uses a gear wheel sensor that employs the gear itself as a material measure to acquire rotational angle data and to deduce the damage condition. A magnetoresistive sensor is integrated into the gearbox housing radially facing a ferromagnetic gear and measures the rotational angle by the gear teeth. Various artificial tooth flank damages are applied to the pinion. The rotational angle is measured with the gear sensor, and the damage state is classified with a random forest classifier using established evaluations in the time and frequency domains. The tests are conducted under stationary operating conditions at an array of speed and torque levels. Additionally, they are performed under transient operating conditions, employing speed ramps at constant torque. The results of the classification are evaluated by means of classification accuracy and confusion matrices and compared with those obtained via a classic encoder at the pinion shaft and an acceleration sensor at the gearbox housing. Full article

The anisotropic magnetoresistance (AMR) effect is widely used in microscale and nanoscale magnetic sensors. In this study, we investigate the correlation between AMR and the crystal structure, epitaxial relationship, and magnetic properties of Co₅₀Fe₅₀ thin films deposited on rigid MgO and flexible mica substrates. The AMR ratio is approximately 1.6% for CoFe films on mica, lower than the 2.5% observed in epitaxially grown films on MgO substrates. The difference is likely due to the well-defined easy axis in the single domain epitaxial thin films on MgO, which enhances the AMR ratio. Microscopic strain induced by lattice mismatch and bending on flexible substrates were determined using grazing incidence X-ray diffraction and extended X-ray absorption fine structure techniques. These results showed that neither microscopic nor macroscopic strain (below 0.5%) affects the AMR ratio on mica, suggesting its suitability for magnetic sensors in flexible and wearable devices. Additionally, investigating M-H loops under various growth temperatures, lattice mismatch conditions, and bending strains could further benefit the fabrication and integration of the micro-scale magnetic sensors in the microelectronic industry. Full article

This study presents a novel dual phase-locked loop two-dimensional synchronized motion modulation (TDSMM-DPLL) system designed to enhance the low-frequency detection capability of magnetoresistive (MR) sensors by effectively mitigating 1/f noise. The TDSMM-DPLL system integrates a comb-driven resonator and a piezoelectric cantilever beam resonator, achieving synchronized magnetic field modulation through a DPLL circuit that adjusts the resonant frequency of the comb-driven resonator to twice that of the cantilever beam resonator. Theoretical analysis and finite element simulations demonstrate a modulation efficiency of 38.98%, which is significantly higher than that of traditional one-dimensional modulation methods. Experimental validation confirms the system’s effectiveness, showing a 3.13-fold reduction in frequency Allan variance, decreasing from 217.32 ppb to 69.46 ppb, indicating substantial noise suppression. These results highlight the TDSMM-DPLL system’s potential to improve the performance of MR sensors in low-frequency applications, making it a promising solution for high-precision magnetic field detection. Full article