Giant Magnetoresistive Sensors Research Articles

Real-time biomolecule detection using GMR chip-based sensor with green-synthesized Fe3O4/rGO nanocomposites as magnetic labels

The availability of a rapid, low-cost, and easy-to-use device to monitor the bovine serum albumin (BSA) level in human blood and urine is vital in early disease detection. This work reports a biosensor system based on a giant magnetoresistance (GMR) chip as a transducer integrated with Fe3O4/rGO magnetic labels for BSA protein detection. The commercial chip AAL024 is utilized as the GMR sensor, combined with an Arduino microcontroller (AM) and a basic differential amplifier to acquire the digital output voltage. The Fe3O4/rGO nanocomposites were synthesized by a hybrid process based on the green synthesis route utilizing plant extracts. The nanocomposites exhibit superparamagnetic behavior, affecting the magnetic label detection quality. In investigating sensor performance, Fe3O4/rGO nanocomposites can generate sufficient stray fields under a 4 Oe of bias magnetic field (HB). A larger net stray field is produced by a higher concentration of magnetic labels, which suggests that there are more Fe3O4 nanoparticles attached to the sensor surface. Further, the effectiveness of the biosensor was evaluated by detecting the BSA protein. As a result, a high sensitivity of 22.98 mV/(mg/mL) and a low limit of detection (LOD) of 0.3 mg/mL were obtained in detecting Fe3O4/rGO(5:1)/BSA with a voltage signal that can be collected in 30 s. Besides its high sensitivity, low LOD, and fast detection, the sensor exhibits remarkable reproducibility and stability, as evidenced by the relative signal deviation (RSD) range of 1.1 – 5.6%. These findings demonstrate that the GMR chip-based sensor integrated with Fe3O4/rGO magnetic labels provides a simple biosensor system with real-time electronic readout.

A GMR enzymatic assay for quantifying nuclease and peptidase activity.

Hydrolytic enzymes play crucial roles in cellular processes, and dysregulation of their activities is implicated in various physiological and pathological conditions. These enzymes cleave substrates such as peptide bonds, phosphodiester bonds, glycosidic bonds, and other esters. Detecting aberrant hydrolase activity is vital for understanding disease mechanisms and developing targeted therapeutic interventions. This study introduces a novel approach to measuring hydrolase activity using giant magnetoresistive (GMR) spin valve sensors. These sensors change resistance in response to magnetic fields, and here, they are functionalized with specific substrates for hydrolases conjugated to magnetic nanoparticles (MNPs). When a hydrolase cleaves its substrate, the tethered magnetic nanoparticle detaches, causing a measurable shift in the sensor's resistance. This design translates hydrolase activity into a real-time, activity-dependent signal. The assay is simple, rapid, and requires no washing steps, making it ideal for point-of-care settings. Unlike fluorescent methods, it avoids issues like autofluorescence and photobleaching, broadening its applicability to diverse biofluids. Furthermore, the sensor array contains 80 individually addressable sensors, allowing for the simultaneous measurement of multiple hydrolases in a single reaction. The versatility of this method is demonstrated with substrates for nucleases, Bcu I and DNase I, and the peptidase, human neutrophil elastase. To demonstrate a clinical application, we show that neutrophil elastase in sputum from cystic fibrosis patients hydrolyze the peptide-GMR substrate, and the cleavage rate strongly correlates with a traditional fluorogenic substrate. This innovative assay addresses challenges associated with traditional enzyme measurement techniques, providing a promising tool for real-time quantification of hydrolase activities in diverse biological contexts.

MEMS Package for an Iron–Gallium Nanowire-Based Acoustic Sensor

A novel nanowire-based acoustic sensor incorporating cilia-like nanowires made of magnetostrictive iron–gallium (Galfenol) alloy has been designed and fabricated using micromachining techniques. The sensor and its package design are analogous to the structural design and the transduction process of a human-ear cochlea. The sensor responds when nanowires shear against the fixed membrane, in response to the motion of the flexible membrane on interaction with the acoustic waves. This results in a change in the magnetic flux in the nanowires, which is converted into electrical voltage by a giant magnetoresistive (GMR) sensor. As the acoustic sensor is designed for underwater applications, packaging is a key issue for the effective working of this sensor. A good package should provide a suitably protective environment to the sensor, while allowing sound waves to reach the sensing element with a minimal attenuation. In this paper, design efforts aimed at producing this microelectromechanical (MEMS) bio-inspired acoustic transducer have been detailed along with the process sequence for its fabrication. Package materials including external enclosure and fluid medium have been identified based on their acoustic performance in water by conducting several experiments to compare their impedance and attenuation characteristics and moisture absorption properties.

A development of high sensitivity magnetic sensor based on giant magnetoresistance with simple implementation on smartphone

In this paper, the magnetic field-based sensor that can connect with smartphones through Bluetooth connectivity was developed. The design of this high sensitivity magnetic sensor system used Giant Magnetoresistance (GMR) sensors in the form of SOIC8 with AA002-02 series from NVE Corp. The results obtained from the measurements show that the sensor is able to work well when connected to an Android-based smartphone. Measurements were carried out by placing a magnet with a magnetic field strength of 0.4 T in the direction of the sensitivity plane of the GMR sensor. The result showed that the closer the magnet distance relative to the GMR sensor the more voltage signal output from the sensor. Since this developed method is simple but effective for detecting position of magnetic object, the further development of this method will be benefit for many applications.

Distributed point source method for eddy current modelling

ABSTRACT Distributed point source method (DPSM) has been gradually applied to the field of nondestructive testing (NDT). As a semi-analytical modelling technique, DPSM is extremely powerful and straightforward for solving various engineering problems, such as ultrasonic fields and electromagnetic field. In this paper, the technique is extended to model the eddy current field including sweep frequency measurement and scanning defect. The configuration of eddy current sensors consists of excitation coil and solid-state magnetic field measurement sensors such as Hall device and giant magnetoresistive sensor. Besides that, the wave propagation has been described and magnetic field created by eddy current has been calculated. The results obtained by DPSM is compared with that calculated by finite element method (FEM) in terms of accuracy and computation time, which indicates DPSM can improve calculation speed while ensuring calculation accuracy.

Comprehensive Introspection of Magnetoresistive sensors applied in biomedical diagnostics.

Over the recent years, magnetoresistive (MR) sensors in biosensing technologies have played a pivotal role in detecting and quantifying biomarkers. The article highly focuses on the potential implications of tunneling magnetoresistance (TMR), giant magnetoresistance (GMR), anisotropic magnetoresistance (AMR), and hybrid MR sensors over conventional prototypes. The study mainly elaborates on the sensor characteristics and their implementation in the biomedical domain. The encompassing evaluation reveals the findings that the TMR sensors are remarkably stable and sensitive, whereas the GMR sensors are highly robust and inexpensive, as determined by the detection level, accuracy, sensing distance, and sensitivity. In addition, it is stated that hybrid MR sensors have lower error rates than AMR sensors utilized in the limited research area.

A dual-binding magnetic immunoassay to predict spontaneous preterm birth.

Complications posed by preterm birth (delivery before 37weeks of pregnancy) are a leading cause of newborn morbidity and mortality. The previous discovery and validation of an algorithm that includes maternal serum protein biomarkers, sex hormone-binding globulin (SHBG), and insulin-like growth factor-binding protein 4 (IBP4), with clinical factors to predict preterm birth represents an opportunity for the development of a widely accessible point-of-care assay to guide clinical management. Toward this end, we developed SHBG and IBP4 quantification assays for maternal serum using giant magnetoresistive (GMR) sensors and a self-normalizing dual-binding magnetic immunoassay. The assays have a picomolar limit of detections (LOD) with a relatively broad dynamic range that covers the physiological level of the analytes as they change throughout gestation. Measurement of serum from pregnant donors using the GMR assays was highly concordant with those obtained using a clinical mass spectrometry (MS)-based assay for the same protein markers. The MS assay requires capitally intense equipment and highly trained operators with a few days turnaround time, whereas the GMR assays can be performed in minutes on small, inexpensive instruments with minimal personnel training and microfluidic automation. The potential for high sensitivity, accuracy, and speed of the GMR assays, along with low equipment and personnel requirements, make them good candidates for developing point-of-care tests. Rapid turnaround risk assessment for preterm birth would enable patient testing and counseling at the same clinic visit, thereby increasing the timeliness of recommended interventions.

Development of a Microfluidic Chip System with Giant Magnetoresistance Sensor for High-Sensitivity Detection of Magnetic Nanoparticles in Biomedical Applications.

Magnetic nanoparticles (MNPs) have been widely utilized in the biomedical field for numerous years, offering several advantages such as exceptional biocompatibility and diverse applications in biology. However, the existing methods for quantifying magnetic labeled sample assays are scarce. This research presents a novel approach by developing a microfluidic chip system embedded with a giant magnetoresistance (GMR) sensor. The system successfully detects low concentrations of MNPs with magnetic particle velocities of 20 mm/s. The stray field generated by the magnetic subject flowing through the microchannel above the GMR sensor causes variations in the signals. The sensor's output signals are appropriately amplified, filtered, and processed to provide valuable indications. The integration of the GMR microfluidic chip system demonstrates notable attributes, including affordability, speed, and user-friendly operation. Moreover, it exhibits a high detection sensitivity of 10 μg/μL for MNPs, achieved through optimizing the vertical magnetic field to 100 Oe and the horizontal magnetic field to 2 Oe. Additionally, the study examines magnetic labeled RAW264.7 cells. This quantitative detection of magnetic nanoparticles can have applications in DNA concentration detection, protein concentration detection, and other promising areas of research.

Classification of hysteresis loops for exchange biased F/NM/F trilayer with antiferromagnetic interlayer coupling

Major hysteresis loops of the F/NM/F/AF structure are classified according to the magnetization process, with the assumption of coherent rotation for each F component and antiferromagnetic coupling between the two F layers. Magnetic stable states of the system as well as specific reversal modes of magnetization during each stage of the major hysteresis cycle are studied in detail based on energetics analysis, in the whole range of exchange bias field and interlayer antiferromagnetic coupling strength. The analysis shows 12 different types of major hysteresis loops for this system and is confirmed by simulation. Strategies to determine key material parameters for the F/NM/F/AF structure from major hysteresis loops are proposed and illustrated by numerical simulation. The research shows a subtle tuning of the magnetization process in the F/NM/F/AF structure, collectively by exchange biasing and interlayer antiferromagnetic coupling. Practically, this serves as a theoretical grounding for the identification of root causes of failure in the product analysis of GMR (giant magnetoresistance) sensors.

Research about passivation layer of SiO2 in GMR sensors for magnetic bead detection

More and more research has been conducted on the detection of biomolecules by using magnetic beads as magnetic tags combined with a giant magneto resistance (GMR) sensor. In studies that involve detection using magnetic particles, larger particle sizes are preferred due to their larger magnetic moment, which facilitates detection. Hence, micrometer-scaled magnetic beads are commonly utilized as detection targets. However, in this study, the thickness of the passivation layer was reduced to enable the detection of magnetic beads with a particle size of 200 nm, which is smaller than the usual size. Magnetic beads with an average particle size of 200 nm and high saturation magnetization were synthesized. The impact of magnetic bead size on the sensor surface was investigated by simulating the stray magnetic field generated by magnetic beads ranging from 100 to 1000 nm, taking into account the properties of the magnetic beads. The simulation results reveal that the presence of magnetic beads reduces the total magnetic field on sensor surface, necessitating thinner passivation layers for smaller particle sizes. For the self-developed magnetic beads used in this study, a passivation layer thickness within 200 nm is necessary. To detect the 200 nm magnetic beads, a GMR sensor with a passivation layer thickness of 10–40 nm was fabricated using MEMS technology. The experimental results show that the sensor signal is maximized at an external magnetic field of –20 Oe, and the sensor signal output increases with decreasing passivation layer thickness.

Partial discharge detection on power equipment using a magneto-resistive sensor

Partial discharges (PD) detection is an effective diagnostic method to assess the insulation condition of electrical power equipment in the high-voltage laboratory or field tests. This paper presents a non-contacting PD detection method for power equipment. The method is based on an extra high-sensitivity adapted giant magneto-resistive (xMR) sensor that measures the magnetic field produced by the PD currents. Firstly, this paper describes the sensor’s relevant principle and signal conditioning circuit. Next, the sensor’s typical performance, including the frequency response and time-domain response to calibrator PD pulses, is measured and compared with our previous work. The results indicate that the xMR system’s bandwidth is improved to the MHz range. Finally, PD experiments are carried out and compared with measurements using a commercially available high-frequency current transformer (HFCT), which allows for verification of the coherence of the results concerning the PD pulses and phase-resolved PD (PRPD) patterns. The results show that PD in a cross-linked polyethylene (XLPE) cable or a gas-insulated system (GIS) with artificial discharging defects is successfully measured, demonstrating the sensitivity and performance of the xMR system for PD detection.

Analytical Validation of a Laboratory-Developed Lung Nodule Risk Reclassifier Assay.

Lung cancer is the second leading cause of death in the United States. Lung cancer is often diagnosed in its late stage leading to a poor prognosis. Lung nodules are often described as indeterminate from CT scans resulting in lung biopsies that are invasive and may lead to complications. The need for noninvasive methods to assess malignancy risk in lung nodules is great. The lung nodule risk reclassifier assay consists of 7 protein biomarkers: Carcinoembryonic Antigen (CEA), C-X-C Motif Chemokine Ligand 10 (CXCL10), Epidermal Growth Factor Receptor (EGFR), Neutrophil Activating Protein-2 (NAP2), Pro-surfactant Protein B (ProSB), Receptor for Advanced Glycation Endproducts (RAGE), and Tissue Inhibitor of Metalloproteinase Inhibitor 1 (TIMP1) and 6 clinical factors (subject age, smoking pack years, and sex, and lung nodule size, location, and spiculated appearance). The protein biomarker assays comprise a multiplex immunoassay panel printed on giant magnetoresistance (GMR) sensor chips as components of a printed circuit board (PCB) run on the MagArray MR-813 instrument system. The analytical validation consisted of imprecision, accuracy, linearity, limits of blank, and limits of detection studies for each biomarker. Several reagents, as well as PCBs, were used in these studies. The entire validation study also assessed multiple users. This laboratory-developed test (LDT), using the MagArray platform, meets the manufacturer's specifications for imprecision, analytical sensitivity, linearity, and recovery. Common biological interferents are known to interfere with the detection of each biomarker. The lung nodule risk reclassifier assay performed as required to be offered as an LDT in the MagArray CLIA-certified laboratory.

Eddy Current Testing Methods and Design for Pipeline Inspection System: A Review

Non-destructive testing and complex systems integration are commonly used in transportation, aircraft, automotive, manufacturing, petrochemical, and defence. Eddy current testing (ECT) is a common non-destructive evaluation technique, especially in the coating, nuclear, and oil and gas industries. However, the eddy current testing method must continue to focus on the probe’s construction and application. It ascribed noisy data to inadequate detection and a severe false alarm problem. Nonetheless, only few academics have elaborated on the intelligent ECT crack detection method. This study provides an overview of the eddy current testing technique and the probe structure design elements that influence fracture detection accuracy. The first section describes the Eddy current testing by encircling coil system for a differential probe (ECDP) and an encircling coil for an absolute probe design (ECDP). The explanations focus mostly on the probe’s creation and detection in Rotating electromagnetic field eddy current (RoFEC). The advantages and disadvantages of eddy current testing surrounding probes are analysed. In addition, a summary of prior studies investigating testing samples of ferromagnetic pipe, steel rod, and wire rope is presented. The second segment focuses on Eddy current testing employing a Giant Magnetoresistance (GMR) sensor system, with a particular emphasis on sensor arrays, GMR, and conventional eddy current coils for crack identification. Finally, a comprehensive overview of eddy current testing methods and design for non-destructive pipeline inspection systems is presented.

Implementation of a full Wheatstone-bridge GMR sensor by utilizing spin–orbit torque induced magnetization switching in synthetic antiferromagnetic layer

A giant magnetoresistance (GMR) sensor with a Wheatstone bridge structure and an out-of-plane linear response was developed. The spin-valve structure consists of a synthetic antiferromagnetic [(Co/Pt)n/Ru/(Pt/Co)n] reference layer with perpendicular magnetic anisotropy, a Cu spacer layer, and a Co-free layer with in-plane easy magnetization. By utilizing the spin–orbit torque induced magnetization switching in the synthetic antiferromagnetic layer, the magnetization of the reference layers in the adjacent bridge arms is set to the opposite direction, achieving a GMR sensor with a full Wheatstone bridge structure. The sensor exhibits linear response to the out-of-plane magnetic field with adjustable dynamic ranges from hundreds to thousands of Oe, depending on the thickness of the Co-free layer. A similar Wheatstone bridge sensor consisting of magnetic tunnel junctions was also proposed. The sensor with out-of-plane linear response may have promising applications in three-dimensional magnetic field detection and current sensing field.

Dynamic electrical compact model of GMR sensors for neuromorphically inspired applications

Neuromorphism is a state-of-the-art paradigm driving the design of many novel devices, including sensors. The development of such systems, usually involving the implementation of complex mixed CMOS/sensors chips, is constrained by the lack of compact electrical models compatible with the most utilized design tools. This paper proposes a dynamic compact electrical model specifically conceived for bio-inspired applications of giant magnetoresistance (GMR) based magnetic scanning sensors. The model includes blocks for static analysis, frequency sweeps, and transient simulations. The model, written in Verilog-A high-level language, can be directly used in most of the standard CMOS design platforms, such as Cadence.

Ultra‐Flexible Giant Magnetoresistance Biosensors for Lab‐on‐a‐Needle Biosensing

AbstractFlexible biosensors exhibit great potential for the detection of various biomarkers with the ability to adapt to different surface textures. Here, a lab‐on‐a‐needle biosensing platform based on ultra‐flexible giant magnetoresistance (GMR) biosensors is developed. The fabricated flexible GMR sensors exhibit a MR ratio of 5.2% and a sensitivity of 0.13%/Oe in the linear region, which are comparable to their rigid counterparts. It is found that the magnetic properties of the flexible GMR sensors remain unchanged after 500 cycles of compressive and tensile stress, indicating strong robustness even when applied to a surface that is constantly in motion. The developed platform is then employed for the detection of different concentrations of canine osteosarcoma (OSCA‐8) cells with a limit of detection (LOD) of 200 cells in 20 µL sample (104 cells per mL), which demonstrate the ability to perform real‐time, sensitive, and quantitative cell detection.

Achieving Low-Noise, High-Bandwidth, Nanoscale-Resolution Position Sensing With GMR Sensors

This article presents a low-noise high-bandwidth giant magnetoresistance (GMR) sensor-readout circuit for nanometer resolution position sensing, a critical requirement in several precision applications such as Atomic Force Microscopy (AFM). The main impediment to performance is the GMR sensor’s significantly higher 1/f noise extending over large bandwidths, thereby limiting the achievable SNR. Therefore, the sensing system needs to be designed at the system level in order to minimize excess intrinsic noise generation and transmission, as well as external noise pickup. The noise characteristics of the GMR sensor and its readout circuit components, and their effect on SNR, are investigated analytically and experimentally. A general process for designing the readout circuit, applicable not just to GMR sensors but also to other high-1/f-noise sensors, is presented. A resolution of 2.5 nm over a bandwidth of 100 kHz is demonstrated on an AFM nanopositioner, a ten-fold improvement over previously reported GMR sensor performance and comparable to the state-of-the-art, but more complex, capacitive sensors. The readout scheme is simple to implement using COTS components and easily extendable to even higher bandwidths, unlike other schemes, such as modulation/demodulation, where the requirement for increasingly higher carrier frequencies renders further improvements in bandwidth impractical.

A Magnetic Feedback-Based Δ–Σ Digitizing Interface for Giant Magnetoresistance Sensors

Giant magnetoresistance sensors are popular for measurement of low magnetic fields due to their low-cost, easy-to-use, high-sensitivity design. However, the GMR sensors exhibit omnipolar, non-linear, and hysteretic voltage versus field characteristics, and operate over a limited range of input fields. In this brief, a simple digitizing interface, based on magnetic-feedback-based Delta-Sigma modulation, is proposed to overcome the aforementioned limitations of GMR sensors. The proposed interface operates the sensor at a quiescent magnetic field and renders a linear direct-digital output. The scheme is designed to measure bipolar fields. The methodology, analysis, and performance verification of the proposed interface are brought out in this brief. Experimental results of the developed interface show a non-linearity (N.L.) of just 0.52% over an enhanced measuring field range and significantly reduced hysteresis.

Giant Magneto-Resistive (GMR) Sensors for Non-Contacting Partial Discharge Detection

Partial discharge (PD) detection is a standardized technique to qualify the insulation condition in power equipment. The main purpose of the paper is to evaluate the performance of an extra high-sensitivity adapted giant magneto-resistive (xMR) sensor for non-contacting PD detection. Firstly, compensation and signal conditioning circuits of the sensor are designed. Frequency response and time-domain response to fast calibrator pulses of the sensor with the implemented circuit are measured. Besides, PD experiments based on corona and surface models are carried out and compared with measurements using a high-frequency current transformer (HFCT). The results show that the xMR system can measure the magnetic fields produced by the PDs at distances up to 50 cm. The correlation between the HFCT and xMR signals is proportional under different voltages, showing that PDs can be effectively detected and evaluated by this method. PDs in a cross-linked polyethylene (XLPE) cable with an artificial discharging defect are successfully measured, demonstrating the sensitivity and performance of the xMR system.

Smart Current Measurement in Modern Power Grids with a Raspberry Pi and GMR Effect-Based Sensor

The Giant magnetoresistance (GMR) effect has been presented as a highly viable current measurement alternative in electrical systems due to its low cost, versatility and high precision. This paper shows how the GMR effect can be used in current measurement in smart grids. The study contributes to the construction of a current measurement prototype which works by using the GMR effect. Subsequently, a data storage and processing server is created using a Raspberry Pi. Finally, a graphical interface capable of real-time monitoring of the data acquired by the sensor is designed and implemented. Different tests were carried out successfully, showing not only the viability of the GMR sensor as a current meter, but also the possibility of using other tools as a complement in order to create a product of great utility in intelligent measurement of smart grids.