Influence of temperature on acoustic emission source location accuracy in underground structure

An acoustic emission (AE) experiment was carried out to explore the AE location accuracy influenced by temperature. A hollow hemispherical specimen was used to simulate common underground structures. In the process of heating with the flame, the pulse signal of constant frequency was stimulated as an AE source. Then AE signals received by each sensor were collected and used for comparing localization accuracy at different temperatures. Results show that location errors of AE keep the same phenomenon in the early and middle heating stages. In the later stage of heating, location errors of AE increase sharply due to the appearance of cracks. This provides some beneficial suggestions on decreasing location errors of structural cracks caused by temperature and improves the ability of underground structure disaster prevention and control.     

Achieving excellent energy storage density of Pb0.97La0.02(ZrxSn0.05Ti0.95-x)O3 ceramics by the B-site modification

The applications of antiferroelectric (AFE) materials in miniaturized and integrated electronic devices are limited by their low energy density. To address the above issue, the antiferroelectricity of the reinforced material was designed to improve its AFE-ferroelectric (FE) phase transition under electric fields. In this present study, the composition of Zr⁴⁺ (0.72 Å) and Ti⁴⁺ (0.605 Å) at B-site of Pb_0.97La_0.02(Zr_xSn_0.05Ti_0.95-x)O₃ ceramics with orthogonal reflections are synthesized via the tape-casting method. These ceramics are modified to enhance their antiferroelectricity by reducing their tolerance factor. A recoverable energy storage density W_rec 12.1 J/cm³ was obtained for x = 0.93 under 376 kV/cm, which is superior value than reported until now in lead-based energy storage systems. Moreover, the discharge energy density can reach 10.23 J/cm³, and 90 % of which can be released within 5.66 μs. This work provides a new window and potential materials for further industrialization of pulse power capacitors.     

不同盐沼湿地类型脱氮除磷效能及影响因素分析

采用沉水植物表面流湿地(沉水组)、挺水植物表面流湿地(挺水组)和浮床湿地(浮床组)3种盐沼湿地对长江口近岸低污染水体进行脱氮除磷效能的研究。结果表明,HRT为3 d时,水组、挺水组、浮床组对NO3^--N的去除率在高温时段分别为79.9%±13.2%、71.8%±15.2%、77.2%±13.2%,中温时段分别为39.4%±13.7%、31.5%±8.5%、18.4%±16.6%,低温时段分别为15.6%±14.6%、19.7%±8.6%、2.%5±8.6%。沉水组和挺水组对TP的去除率受温度影响较小,分别为66.4%±32.4%、55.5%±29.4%;而浮床组除磷效果受温度影响较大。当HRT缩短为1.5 d时,3组湿地系统在高温时段仍可达到相近的脱氮除磷效果,在中低温时段脱氮除磷效果都有不同程度的下降。     

高熵形状记忆合金的研究进展

高熵形状记忆合金是在等原子比NiTi合金的基础上,结合高熵合金的概念,逐渐发展起来的一种新型高温形状记忆合金。近年来,已开发出了综合性能优异的(TiZrHf)50(NiCoCu)50系和(TiZrHf)50(NiCuPd)50系高熵形状记忆合金,引起了广泛的关注和研究兴趣。本文从物相组成、微观组织、马氏体相变行为、形状记忆效应和超弹性等角度出发,综述了高熵形状记忆合金的研究进展,并对高熵形状记忆合金未来的研究重点进行了展望。     

Synthesis,characterization and charge transport properties of Pr–Ni Co-doped SrFe2O4 spinel for high frequency devices applications

Ferrites are materials of interest due to their broad applications in high technological devices and a lot of research has been focused to synthesize new ferrites. In this regard, an effort has been devoted to synthesize spinel Pr–Ni co-substituted strontium ferrites with a nominal formula of Sr_1-xPr_xFe_2-yNi_yO₄ (0.0 ≤ x ≤ 0.1, 0.0 ≤ y ≤ 1.0). The cubic structure of pure and Pr–Ni co-substituted strontium ferrite samples calcinated at 1073 K for 3 h has been confirmed through X-ray diffraction (XRD). Average sizes of crystallites (18–25 nm) have been estimated from XRD analysis and nanometer particle sizes of synthesized ferrites have been further verified by scanning electron microscopy (SEM). SEM results have also shown that particles are mostly agglomerated and all the samples possess porosity. It has been observed that at 298 K, the values of resistivity (ρ) increase, while that of AC conductivity, dielectric loss, and dielectric constants decrease with increasing amounts of Pr³⁺ and Ni²⁺ ions. The values of dielectric parameters initially decrease with frequency and later become constant and can be explained on the basis of dielectric polarization. Electrochemical impedance spectroscopy (EIS) studies show that the charge transport phenomenon in ferrite materials is mainly controlled via grain boundaries. Overall, synthesized ferrite materials own enhanced resistivity values in the range of 1.38 × 10⁹–1.94 × 10⁹ Ω cm and minimum dielectric losses, which makes them suitable candidates for high frequency devices applications.     

一种新型的室温快速固化胶黏剂的研制

本文开发了一种新型的方舱夹芯板用室温固化高强度环氧结构胶黏剂,验证了其物化特性、相关力学性能和环境适应性。结果表明此胶黏剂具有优良性能,可以满足方舱用大板胶黏剂的使用需求。     

Thiol-Functionalized Covalent Organic Frameworks as Thermal History Indictor for Temperature and Time History Monitoring

Various products, including foods and pharmaceuticals, are sensitive to temperature fluctuations. Thus, temperature monitoring during production, transportation, and storage is critical. Facile indicators are required to monitor temperature conditions via color changes in real time. This study aimed to prepare and apply thiol-functionalized covalent organic frameworks (COFs) as a novel indicator for monitoring thermal history and temperature abuse. The COFs underwent obvious color changes from bright yellow to purple after exposure to different temperatures for varying durations. The reaction kinetics are analyzed under isothermal conditions, which reveal that the order of reaction rates is k_−20°C < k_4°C < k_20°C < k_35°C < k_55°C. The activation energy (E_a) of the COFs is calculated using the Arrhenius equation as 50.71 kJ moL⁻¹. The COFs are capable of sensitive color changes and offer a broad temperature tracking range, thereby demonstrating their application potential for the monitoring of temperature and time exposure history during production, transportation, and storage. This excellent performance thermal history indicator also shows promise for expanding the application field of COFs.     

高温气冷球床堆有效导热系数模型的改进

有效导热系数是高温气冷球床堆热工设计和安全分析程序中的基本参数，ZBS模型广泛应用于球床结构有效导热系数的预测。本文针对ZBS模型中的关键经验型参数——接触面积系数φ进行了分析，通过对不同堆积结构球床有效导热系数的数值分析，获得了12组接触直径比和配位数及其对应的φ值，然后通过多元线性分析获得φ的计算公式。与德国SANA实验结果进行比较，发现改进后的ZBS模型预测能力优于其他模型。改进后的ZBS模型的计算结果与先前实验测量的球床主体区域的有效导热系数吻合也很好。本文研究结果可为高温气冷球床堆的设计和安全分析提供理论支持。     

Machine learning of phases and mechanical properties in complex concentrated alloys

The mechanical properties of complex concentrated alloys (CCAs) depend on their formed phases and corresponding microstructures.The data-driven prediction of the phase formation and associated mechanical properties is essential to discovering novel CCAs.The present work collects 557 samples of various chemical compositions,comprising 61 amorphous,167 single-phase crystalline,and 329 multi-phases crystalline CCAs.Three classification models are developed with high accuracies to category and understand the formed phases of CCAs.Also,two regression models are constructed to predict the hard-ness and ultimate tensile strength of CCAs,and the correlation coefficient of the random forest regression model is greater than 0.9 for both of two targeted properties.Furthermore,the Shapley additive expla-nation (SHAP) values are calculated,and accordingly four most important features are identified.A significant finding in the SHAP values is that there exists a critical value in each of the top four fea-tures,which provides an easy and fast assessment in the design of improved mechanical properties of CCAs.The present work demonstrates the great potential of machine learning in the design of advanced CCAs.