The rectangular magnetoelectric (ME) composites of Metglas/PZT and Terfenol-D/PZT are prepared, and the effects of a magnetostrictive layer’s material characteristics on the magnetoimpedance of ME composite are discussed and experimentally investigated. The theoretical analyses show that the impedance is not only dependent on Young’s modulus and the magnetostrictive strain of magnetostrictive material but is also influenced by its relative permeability. Compared with Terfenol-D, Metglas possesses significantly higher magnetic permeability and larger magnetostrictive strain at quite low Hdc due to the small saturation field, resulting in the larger magnetoimpedance ratio. The experimental results demonstrate that the maximum magnetoimpedance ratios (i.e., ΔZ/Z) of Metglas/PZT composite are about 605.24% and 239.98% at the antiresonance and resonance, respectively. Specifically, the maximum ΔZ/Z of Metglas/PZT is 8.6 times as high as that of Terfenol-D/PZT at the antiresonance. Such results provide the fundamental guidance in the design and fabrication of novel multifunction devices based on the magnetoimpedance effect of ME composites.
A magnetically tunable magnetoelectric transducer consisting of rectangular Fe82Ga18(FeGa)/Pb(Zr,Ti)O3(PZT) composites is developed, and their magnetoimpedance and magnetocapacitance effects are investigated under bending and longitudinal modes. Specifically, the composites’ impedance and capacitance are found to vary with dc magnetic field Hdc, which results from the varied effective dielectric permittivity of the FeGa/PZT composite with Hdc due to the delta E effect, magnetostrictive effect of FeGa and mechanism responsible for ME coupling between the FeGa and PZT layers. Furthermore, the FeGa/PZT bilayered composite exhibits both bending and longitudinal vibration modes due to the asymmetrical stress distributions. The maximum ΔZ/Z of the FeGa/PZT composite is about 215% at the antiresonance frequency fa = 28.78 kHz of the bending-mode, which is 2.53 times as high as that at the antiresonance frequency fa = 107.9 kHz of the longitudinal mode, while the maximum ΔC/C of the FeGa/PZT composite is about 406% at the resonance frequency fr = 28.5 kHz of the bending mode, which is 3.5 times as high as that at the antiresonance frequency fa = 106.6 kHz of the longitudinal mode. This study plays a guiding role for the design and corresponding application of magnetic sensors, magnetic-field-tuned electronic devices and multiple frequency ultrasonic transducers.
Heat assisted interlaced magnetic recording (HIMR) is a promising candidate for the nextgeneration of magnetic recording technology to further increase the area density beyond 1Tb/in 2 . Specifically, the high temperature and low temperature tracks are written in an interlaced order to improve the recording performance. However, the inter-track interference (ITI), inter-symbol interference (ISI) and thermal jitters brought by the increased recording density and Curie temperature variations are severe in HIMR, which degrade the bit error rate (BER) performance obviously. In this study, we propose a multitrack detection scheme with joint intertrack interference and media noise mitigations. Here a multi-task neural network (MTNN) is designed to simultaneously predict ITI pattern and residual media noise, then the 2D variable equalizers corresponding to different ITI patterns are implemented and predicted residual media noises are embedded into the branch metrics of modified Bahl-Cocke-Jelinek-Raviv (BCJR) detector to mitigate ITI and whiten media noise. The simulation demonstrates that the proposed MTNN with variable equalizer and modified BCJR detector (MTNN+VE+MB) algorithm mitigates the ITI and media noise effectively. At the channel bit density of 3.10 Tb/in 2 , it provides 2.6 dB signal-to-noise ratio (SNR) gain compared to that of conventional 2D fixed equalizer with pattern dependent noise prediction detector (FE+PDNP) for the low temperature (LT) tracks with 4% Curie temperature variance.INDEX TERMS Intertrack interference (ITI), Media noise, Heat assisted interlaced magnetic recording (HIMR), Neural network, Multitrack detection.
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