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学者姓名：梁中宇
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Abstract ：
Rare-earth transition-metal (R-T) intermetallic compounds with planar magnetocrystalline anisotropy exhibit enhanced high-frequency magnetic properties and superior microwave absorption performance compared to compounds with uniaxial magnetocrystalline anisotropy, due to their higher Snoek limit resulting from high saturation magnetization (Ms) and large anisotropy factor. In this work, we investigated the structure, magnetic, and microwave absorbing properties of Y2Fe17-xSix (0≤x≤2) with planer anisotropy and their paraffin composites. Neutron powder diffraction (NPD) indicates that Y2Fe17-xSix compounds all possess a disordered Th2Ni17-type hexagonal structure as the primary phase, and the preferential order for Si substituting Fe crystallographic sites is: 12k, 6g, 12j1, 12j2, 4f, and 4e. At room temperature (RT), the 57Fe Mössbauer spectra reveal that the average hyperfine field increases with increasing Si content, which is proportional to the average atomic magnetic moment of Fe. Magnetic measurements show that Si substitution significantly raises the Curie temperature (Tc) of Y2Fe17-xSix compounds, while also increasing the Ms at RT. By studying the high-frequency electromagnetic properties of Y2Fe17-xSix/paraffin composites, it was found that the real part of permittivity (ɛ′) at 1 GHz decreases with increasing Si content, reducing by approximately 40% for x=2 compared to x=0. Meanwhile, the real part of permeability (μ′) at 1 GHz initially increases and then decreases with increasing Si content, reaching a maximum at x=1.5. Therefore, Si substitution is advantageous to enhance the impedance matching of the composites, leading to better microwave absorption performance. Among all the compositions, the Y2Fe15Si2/paraffin composite exhibits a minimum reflection loss (RL) of -53.3 dB with a thickness of 3.0 mm, and a maximum effective absorption bandwidth (EAB, RL © 2025 Elsevier B.V.
Keyword ：
Iron oxides Iron oxides Magnetic resonance measurement Magnetic resonance measurement Magnetocrystalline anisotropy Magnetocrystalline anisotropy Magnetometry Magnetometry Molybdenum compounds Molybdenum compounds Mossbauer spectroscopy Mossbauer spectroscopy Neutron powder diffraction Neutron powder diffraction Pyrites Pyrites Thorium alloys Thorium alloys Thorium compounds Thorium compounds Yttrium iron garnet Yttrium iron garnet
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| GB/T 7714 | Zhang, Pengyu , Wang, Yuankang , Lin, Zhongchong et al. Effects of Si substitution on the magnetic and microwave absorbing properties of Y2Fe17-xSix and their composites [J]. | Journal of Alloys and Compounds , 2025 , 1031 . |
| MLA | Zhang, Pengyu et al. "Effects of Si substitution on the magnetic and microwave absorbing properties of Y2Fe17-xSix and their composites" . | Journal of Alloys and Compounds 1031 (2025) . |
| APA | Zhang, Pengyu , Wang, Yuankang , Lin, Zhongchong , Sun, Xutao , Li, Kewei , Qian, Huidong et al. Effects of Si substitution on the magnetic and microwave absorbing properties of Y2Fe17-xSix and their composites . | Journal of Alloys and Compounds , 2025 , 1031 . |
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Abstract ：
Deep neural networks (DNNs) have proved to be remarkably successful in various domains, in particular for implementing complex functions and performing sophisticated tasks. However, their vulnerability to adversarial noise undermines their reliability for safety-critical tasks. Despite attempts to improve the robustness using algorithmic approaches, an effective hardware implementation is still lacking. Here an artificial probabilistic neuron device is proposed based on arrays of coupled nanomagnets, referred to as artificial spin ices, which return a nonlinear function with built-in stochasticity in response to an ultrafast laser-induced excitation. By exploiting solid-state ionic gating, the magnetic coupling is electrically modulated, as a result of the magnetic anisotropy-mediated competition of the symmetric exchange interaction and Dzyaloshinskii-Moriya interaction, and hence tune the stochastic property of the neuron device at run-time. Stochastic DNNs are then constructed with an output layer comprising several of probabilistic neuron devices. Compared to conventional DNNs, the stochastic DNNs exhibit an order of magnitude greater resistance to adversarial noise, providing a significant improvement in robustness. This approach opens the way to more secure and reliable DNNs, enabling broader uses in real-world applications.
Keyword ：
artificial spin ice artificial spin ice nanomagnet nanomagnet neuromorphic computing neuromorphic computing probabilistic computing probabilistic computing ultrafast spin dynamics ultrafast spin dynamics
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| GB/T 7714 | Liang, Zhongyu , Bu, Tong , Lyu, Zijian et al. Ultrafast Probabilistic Neuron in an Artificial Spin Ice for Robust Deep Neural Networks [J]. | ADVANCED FUNCTIONAL MATERIALS , 2024 , 35 (11) . |
| MLA | Liang, Zhongyu et al. "Ultrafast Probabilistic Neuron in an Artificial Spin Ice for Robust Deep Neural Networks" . | ADVANCED FUNCTIONAL MATERIALS 35 . 11 (2024) . |
| APA | Liang, Zhongyu , Bu, Tong , Lyu, Zijian , Liu, Zhentao , Hrabec, Ales , Wang, Leran et al. Ultrafast Probabilistic Neuron in an Artificial Spin Ice for Robust Deep Neural Networks . | ADVANCED FUNCTIONAL MATERIALS , 2024 , 35 (11) . |
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