Thanks to high sensitivity, excellent scalability, and low power consumption, magnetic tunnel junction (MTJ)-based tunnel magnetoresistance (TMR) sensors have been widely implemented in various industrial fields. In nondestructive magnetic flux leakage testing, the magnetic sensor plays a significant role in the detection results. As highly sensitive sensors, integrated MTJs can suppress frequency-dependent noise and thereby decrease detectivity; therefore, serial MTJ-based sensors allow for the design of high-performance sensors to measure variations in magnetic fields. In the present work, we fabricated serial MTJ-based TMR sensors and connected them to a full Wheatstone bridge circuit. Because noise power can be suppressed by using bridge configuration, the TMR sensor with Wheatstone bridge configuration showed low noise spectral density (0.19 μV/Hz^0.5) and excellent detectivity (5.29 × 10⁻⁸ Oe/Hz^0.5) at a frequency of 1 Hz. Furthermore, in magnetic flux leakage testing, compared with one TMR sensor, the Wheatstone bridge TMR sensors provided a higher signal-to-noise ratio for inspection of a steel bar. The one TMR sensor system could provide a high defect signal due to its high sensitivity at low lift-off (4 cm). However, as a result of its excellent detectivity, the full Wheatstone bridge-based TMR sensor detected the defect even at high lift-off (20 cm). This suggests that the developed TMR sensor provides excellent detectivity, detecting weak field changes in magnetic flux leakage testing.

We report a detailed spin-dependent tunneling spectroscopy in single-crystal $\mathrm{Fe}\left(001\right)∕\mathrm{Mg}\mathrm{O}\left(001\right)∕\mathrm{Fe}\left(001\right)$ magnetic tunnel junctions (MTJs) that show a giant tunnel magnetoresistance effect. Spectra for antiparallel magnetic configurations show asymmetry because of extrinsic electron scatterings caused by structural defects at the barrier/electrode interfaces. Surprisingly, spectra for parallel magnetic configurations exhibit a complex oscillatory structure that has never been observed in conventional MTJs with an aluminum-oxide tunnel barrier. The complex spectra reflect the tunneling process via interface resonant states. These results provide some information that helps to elucidate the physics of spin-dependent electron tunneling and to further enhance magnetoresistance.

The line width of the ferromagnetic resonance (FMR) spectrum of Cu/CoFeB/Cu/Co/Cu is studied. Analyzing the FMR spectrum by the theory of spin pumping, we determined the penetration depth of the transverse spin current in the Co layer. The obtained penetration depth of Co is 1.7 nm.

Thanks to their high magnetoresistance and integration capability, magnetic tunnel junction-based magnetoresistive sensors are widely utilized to detect weak, low-frequency magnetic fields in a variety of applications. The low detectivity of MTJs is necessary to obtain a high signal-to-noise ratio when detecting small variations in magnetic fields. We fabricated serial MTJ-based sensors with various junction area and free-layer electrode aspect ratios. Our investigation showed that their sensitivity and noise power are affected by the MTJ geometry due to the variation in the magnetic shape anisotropy. Their MR curves demonstrated a decrease in sensitivity with an increase in the aspect ratio of the free-layer electrode, and their noise properties showed that MTJs with larger junction areas exhibit lower noise spectral density in the low-frequency region. All of the sensors were able detect a small AC magnetic field (H_rms = 0.3 Oe at 23 Hz). Among the MTJ sensors we examined, the sensor with a square-free layer and large junction area exhibited a high signal-to-noise ratio (4792 $\pm$ 646). These results suggest that MTJ geometrical characteristics play a critical role in enhancing the detectivity of MTJ-based sensors.

Remote health monitoring has become a necessity due to reduced healthcare access resulting from pandemic lockdowns and the increasing aging population. Electrocardiography (ECG) is the standard for cardiac monitoring and arrhythmia identification, but it is inconvenient for long-time remote monitoring. Recently, Magnetocardiography (MCG) sensors that operate at room temperature became available based on spintronic sensors. However, MCG analysis is affected by the low-frequency noise present at the sensors. In this paper, we present an artificial intelligence (AI)-aided multi-model pipeline combining two AI architectures, defined as model-M1 and model-M2, targeted for ultra-edge Internet of Things (IoT) sensors to simulate arrhythmia detection. Model-M1 is a denoising preprocessor based on a sliding-window assisted deep-learning (DL) model. We investigate various methods to achieve high accuracy with lightweight computation. Model-M2 is a lightweight DL model that analyzes denoised ECG output from model-M1 to identify arrhythmia. We use multiple publicly available clinically annotated datasets to evaluate our proposal. We find that denoising by model-M1 retains the features, which assist the model-M2 in achieving high classification accuracy, compared to using a conventional moving average filter. This AI pipeline architecture is promising for privacy-preserving ultra-edge medical sensing devices.

The magnetic properties of CoFeB buffered [Co(0.3 nm)Pd(x nm)]₆ multilayer films have been investigated. It is found that the magnetic properties of the multilayer depended on the Pd thickness and for thickness below 0.5 nm no perperdicular anisotropy is observed. Magnetization dynamics in perpendicularly magnetized CoFeB-[Co/Pd] multilayer films are investigated using time-resolved magneto-optical Kerr effect (TRMOKE). The variation of precession frequency with external magnetic field for different palladium thickness is quantitatively understood using the macrospin approximation of the Landau-Lifshitz-Gilbert equation of motion. The Gilbert damping constant ¿, in the range 0.04-0.1, varying with the palladium thickness is reported. The observed ¿ value is comparable to the damping coefficient of bulk Ni, and much lower than the reported values for perpendicularly magnetized films. The CoFeB buffer layer with in-plane anisotropy appears to significantly affect the precession frequency and thus the damping constant of the films.