Large domain-wall currents in epitaxial Au/BiFeO3/SrRuO3 thin-film capacitors with modulated oxygen vacancy and wall densities

Large domain wall (DW) conductivity in an insulating ferroelectric plays an important role in the future nanosensors and nonvolatile memories. However, the wall current was usually too small to drive high-speed memory circuits and other agile nanodevices requiring high output-powers. Here, a large domain-wall current of 67.8 μA in a high on/off ratio of ~4460 was observed in an epitaxial Au/BiFeO₃/SrRuO₃ thin-film capacitor with the minimized oxygen vacancy concentration. The studies from read current-write voltage hysteresis loops and piezo-response force microscope images consistently showed remaining of partially unswitched domains after application of an opposite poling voltage that increased domain wall density and wall current greatly. A theoretical model was proposed to explain the large wall current. According to this model, the domain reversal occurs with the appearance of head-to-head and tail-to-tail 180° domain walls (DWs), resulting in the formation of highly conductive wall paths. As the applied voltage increased, the domain-wall number increased to enhance the on-state current, in agreement with the measurements of current-voltage curves. This work paves a way to modulate DW currents within epitaxial Au/BiFeO₃/SrRuO₃ thin-film capacitors through the optimization of both oxygen vacancy and domain wall densities to achieve large output powers of modern domain-wall nanodevices.     

Facile synthesis of MgO–Mg2SiO4 composite ceramics with high strength and low thermal conductivity

The recycling of solid waste is a win-win solution for humans and nature. For this purpose, magnesite tailings and silicon kerf waste were employed to prepare MgO–Mg₂SiO₄ composite ceramics by solid-state reaction synthesis in the present work. Then, effects of sintering temperature and raw material ratio on as-prepared ceramics were systematically studied. As-prepared ceramics showed improvement in their relative density (from 47.55%–68.12% to 90.96%–95.25%) and cold compressive strength (from 7.34–118.66 MPa to 303.39–546.65 MPa) with the increase in sintering temperature from 1300 to 1600 °C. In addition, it was found that Si promoted synthesis process of Mg₂SiO₄ phase through transient liquid phase sintering and Fe₂O₃ accelerated sintering process through activation sintering. Consequently, the presence of Mg₂SiO₄ phase effectively improved the density and strength of MgO–Mg₂SiO₄ composite ceramic, while reducing its thermal conductivity. This work provides a potential reutilization strategy for magnesite tailings, and as-prepared products are expected to be applied in fields of construction, metallurgy, and chemical industry.     

Self-healing,elastic and deformable novel composite phase change polymer based on thermoplastic elastomer SEBS for wearable devices

Journal of Materials Science - Form-stable composite phase change materials (C-PCMs) prepared by microencapsulation method and porous matrix adsorption method need for compression molding after...     

Theoretical estimation of dielectric loss of oxide glasses using nonequilibrium molecular dynamics simulations

To theoretically explore amorphous materials with a sufficiently low dielectric loss, which are essential for next-generation communication devices, the applicability of a nonequilibrium molecular dynamics simulation employing an external alternating electric field was examined using alkaline silicate glass models. In this method, the dielectric loss is directly evaluated as the phase shift of the dipole moment from the applied electric field. This method enabled us to evaluate the dielectric loss in a wide frequency range from 1 GHz to 10 THz. It was observed that the dielectric loss reaches its maximum at a few THz. The simulation method was found to qualitatively reproduce the effects of alkaline content and alkaline type on the dielectric loss. Furthermore, it reasonably reproduced the effect of mixed alkalines on the dielectric loss, which was observed in our experiments on sodium and/or potassium silicate glasses. Alkaline mixing was thus found to reduce the dielectric loss.     

Microstructure and electric properties of Pr-doped Pb(Zr0.52Ti0.48)O3 ceramics

Improving the piezoelectric activity of lead zirconate titanate (PZT) ceramics is of great importance for practical applications. In this study, the influence of Pr³⁺ doping on the ferroelectric phase composition, microstructure, and electric properties on the A-site of (Pb_1-1.5xPr_x)(Zr_0.52Ti_0.48)O₃ is extensively investigated. A dense and fine microstructural sample is obtained with the introduction of Pr³⁺. The results show that the morphotropic phase boundary (MPB) moves to the rhombohedral phase region. The rhombohedral and tetragonal phases exhibit an ideal coexistence in the 4 mol.% Pr³⁺ doped (PPZT4) samples. Lead vacancy and the reduction of the potential energy barrier are considered to be the key mechanisms for donor doping, which is upheld by the Pr³⁺ doping. Combining the I-E hysteresis loops with the P-E hysteresis loops, it becomes apparent that both contribution maximums of the domain switching and residual polarisation are in PPZT4. Moreover, the thermal aging resistance of PZT is improved by doping, and the temperature stability is optimised from 83% in PZT to 96% in PPZT4. Hence, an appropriate amount of Pr³⁺ doping can effectively improve the piezoelectric activity of PZT ceramics in the MPB area and optimise the performance stability of the material under application temperatures.     

Rheological phase reaction synthesis and electrochemical performance of LiFe2/3Mn1/3PO4/C cathode for lithium-ion batteries

LiFe_2/3Mn_1/3PO₄/C composite was prepared by the rheological phase reaction using LiH₂PO₄, Li₂CO₃, FePO₄, Mn(Ac)₂·4H₂O and ascorbic acid as starting materials. The crystal structure and morphology of as-synthesized sample were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM). The analysis of XRD results showed that the obtained sample was single-phase with orthorhombic olivine-type structure (Pnma space group). SEM micrographs revealed that the sample was aggregates, with an irregular morphology. The initial discharge capacity was 166.9, 149.1, 139.6, 112.8, 82.93 mAh g^??1 at the rate of 0.1, 0.5, 1, 2, and 10 C, respectively. And when the rate was 0.1, 0.5, 1, 2, and 10 C, the capacity retention was 92.2%, 90%, 92.9%, 97.6%, 91.5% after 50, 100, 200, 200, 500 cycles, respectively.

     

A Novel LRRK2 Variant p.G2294R in the WD40 Domain Identified in Familial Parkinson’s Disease Affects LRRK2 Protein Levels

Leucine-rich repeat kinase 2 (LRRK2) is a major causative gene of late-onset familial Parkinson’s disease (PD). The suppression of kinase activity is believed to confer neuroprotection, as most pathogenic variants of LRRK2 associated with PD exhibit increased kinase activity. We herein report a novel LRRK2 variant—p.G2294R—located in the WD40 domain, detected through targeted gene-panel screening in a patient with familial PD. The proband showed late-onset Parkinsonism with dysautonomia and a good response to levodopa, without cognitive decline or psychosis. Cultured cell experiments revealed that p.G2294R is highly destabilized at the protein level. The LRRK2 p.G2294R protein expression was upregulated in the patient’s peripheral blood lymphocytes. However, macrophages differentiated from the same peripheral blood showed decreased LRRK2 protein levels. Moreover, our experiment indicated reduced phagocytic activity in the pathogenic yeasts and α-synuclein fibrils. This PD case presents an example wherein the decrease in LRRK2 activity did not act in a neuroprotective manner. Further investigations are needed in order to elucidate the relationship between LRRK2 expression in the central nervous system and the pathogenesis caused by altered LRRK2 activity.     

基于大数据深度学习的输电塔结构抗风易损性评估

为了有效预测输电网系统在强风作用下的响应，并开展高效精准的性能评估，文章提出了基于深度学习模型的风致易损性评估框架。以某具备健康监测系统的输电塔结构为例，首先对监测数据进行清洗和重构，通过大数据深度学习建立荷载输入和响应输出的等效映射模型，然后通过数值模拟生成灾害强度均匀的风场数据并由深度学习模型预测输电塔关键杆件响应，计算不同性能水准的易损性曲线。研究结果表明，经训练的深度学习模型可以涵盖实际工程中存在的各类不确定性因素，有效映射复杂风环境下输电塔结构的动力响应。提出的框架方法可以避免单纯通过数值模型制备大量动态响应数据，更高效地进行输电网系统风致易损性评估。