Dual-phase rare-earth-zirconate high-entropy ceramics with glass-like thermal conductivity

A series of rare earth zirconates (RE₂Zr₂O₇) high-entropy ceramics with single- and dual-phase structure were prepared. Compared with La₂Zr₂O₇ and Yb₂Zr₂O₇, the smaller “rattling” ions (Yb³⁺, Er³⁺, Y³⁺) have been incorporated into pyrochlore lattice in (La_0.2Nd_0.2Y_0.2Er_0.2Yb_0.2)₂Zr₂O₇ (LNYEY) while larger ions (La³⁺, Nd³⁺, Sm³⁺, Eu³⁺) incorporated into fluorite lattice in (La_0.2Nd_0.2Sm_0.2Gd_0.2Yb_0.2)₂Zr₂O₇ (LNSGY). Due to high-entropy lattice distortion and resonant scattering derived from smaller ions Yb³⁺, Er³⁺, and Y³⁺, LNYEY shows a lower glass-like thermal conductivity (1.62-1.59 W m^-1 K^-1, 100-600℃) than LNSGY (1.74-1.75 W m^-1 K^-1, 100-600℃). Moreover, LNYEY and LNSGY exhibit enhanced Vickers’ hardness (LNYEY, H_v = 11.47 ± 0.41 GPa; LNSGY, H_v = 10.96 ± 0.26 GPa) and thermal expansion coefficients (LNYEY, 10.45 × 10^-6 K^-1, 1000℃; LNSGY, 11.02 × 10^-6 K^-1, 1000℃). These results indicate that dual-phase rare-earth-zirconate high-entropy ceramics could be desirable for thermal barrier coatings.     

Inconel 690传热管GTAW对接焊接头组织及力学性能研究

对Inconel 690传热管材进行钨极气体保护焊(GTAW)对接焊,采用拉伸试验机、压扁试验机和光学显微镜测试和分析传热管焊接接头,同时利用ANSYS软件开展焊接接头在设计工况失压时的一次应力强度校核。研究结果表明:焊缝中心为树枝胞状晶,熔合线附近为粗大柱状晶。室温时接头的平均抗拉强度为619 MPa,平均屈服强度为292 MPa,350℃时接头平均抗拉强度为475 MPa,平均屈服强度为206 MPa,拉伸接头断裂从熔合区开始贯穿整个焊缝组织,呈塑性断裂。压扁试验和反向压扁试验结果表明管接头完好。通过ANSYS分析可知,设计工况下传热管接头350℃许用应力强度150 MPa限值可满足其一次应力强度要求,且裕量较大。     

某微细粒嵌布磁铁矿选矿工艺研究

针对某微细粒磁铁矿进行了全磁选流程和磁选-反浮选流程对比试验研究。结果表明,在最终磨矿细度相当的情况下,2种工艺流程都获得了产率48%左右、TFe品位66%左右、回收率80%左右的铁精矿指标,而采用磁选-反浮选流程的第三段磨矿量比全磁选流程减少了2/3。磁选-反浮选流程具有显著的节能降耗优势。     

地应力条件下的凿岩爆破数值模拟

为了研究地应力对凿岩爆破的影响,采用DDA方法模拟爆炸应力波作用下考虑地应力条件时的单孔和多孔凿岩爆破破岩过程。模拟发现,随着初始地应力水平的增加,裂纹扩展半径和破岩区域面积减小,裂纹发育主方向趋于地应力的最大主应力方向,初始地应力对裂纹的抑制和引导作用明显;初始地应力水平的增加,对拉伸裂纹的抑制作用更为显著,从而降低了拉伸破坏对爆破破岩的贡献。模拟也表明,在初始地应力存在的条件下,通过对爆破载荷和炮孔布置进行针对性的优化,可以克服地应力带来的影响,并取得预期的爆破效果。本研究对地应力条件下的凿岩爆破工程具有理论和参考意义。     

离子型稀土矿山淋洗及尾水富集试验研究

对浸矿后离子型稀土原地浸矿场采用清水进行淋洗，在184天的清水淋洗过程中，尾水氨氮值从最开始的507mg/L，降低至140mg/L，淋洗尾水pH4.52~3.10。淋洗尾水采用两级反渗透膜分离，既回收有价资源稀土，又能使出水氨氮达标。结果表明，产水氨氮浓度稳定低于15mg/L，对稀土的截留率高于98.25%，浓水中稀土离子平均浓度313.4mg/L，可进一步回收稀土资源。     

Improved photoluminescence and multi-mode optical thermometry of Er3+/Yb3+ co-doped (Ba,Sr)3Lu4O9 phosphors

Contactless optical thermometers have attracted extensive attentions for applications in scientific research and technological fields due to their apparent advantages. Herein, a novel sequence of Ba_3-xSr_xLu₄O₉ (B_3-xS_xLO):Er³⁺/Yb³⁺ phosphors were successfully prepared to investigate the temperature sensing property. By establishing energy transfer from Yb³⁺ to Er³⁺ and regulating the local lattice environment, up-conversion luminescence of Er³⁺ is dramatically improved when excited by 980 nm laser. This can effectively promote signal-noise ratio and reduce the errors in temperature detection. Furthermore, a multi-mode optical thermometry, which includes the fluorescence intensity ratio (FIR) from two thermally coupled levels of ²H_11/2/⁴S_3/2, FIR based on non-thermally coupled system of ²H_11/2/⁴F_9/2 and fluorescence lifetime of ⁴S_3/2 state of Er³⁺, was explored systematically. The fabricated samples exhibit the superior temperature measurement performances containing wide temperature-sensing range, superior signal discriminability, high sensitivity and favorable repeatability, indicative of the enormous utilization prospects of B_3-xS_xLO:Er³⁺/Yb³⁺ for thermometry.     

Rare earth metals co-doped ZnO/CNTs composite as high performance photocatalyst for hydrogen production from water_triethanolmine mixture

This study investigated the zinc oxide (ZnO) based heterojunction photocatalysts for improved hydrogen production from water splitting. A sol-gel route was adopted to produce terbium (Tb) and samarium (Sm) co-doped ZnO/CNTs composites where CNTs worked as a support material. The built-in redox couples of lanthanides in co-doped TS-ZnO/CNTs composite showed higher hydrogen evolution activity than Sm doped (Sm-ZnO/CNTs) and Tb doped (Tb–ZnO/CNTs) photocatalysts. When triethanolamine was utilized as a sacrificial agent, the TS-ZnO/CNTs photocatalyst result in a remarkable hydrogen evolution rate of 2683 molh^?1g^?1 under visible light illumination. The optimum photocatalyst also showed high stability over five successive hydrogen evolution cycles. The better hydrogen evolution rate with TS-ZnO/CNTs was referred to its fine particle size, high reactive surface area, small optical band gap, suppressed reunification of charge carriers and built-in redox couples. The photocatalytic mechanism, involved in water splitting with TS-ZnO/CNTs photocatalyst, is also deduced in this study. This study can stimulate the attempts towards construction of lanthanides based co-doped semiconductor photocatalysts for efficient hydrogen evolution.     

基于卷积神经网络的5G蜂窝网络无线定位方法

5G蜂窝网络发展迅猛，其覆盖面积将逐渐增大，因此使用5G蜂窝网络进行定位是有研究潜力的研究方向。本文提出一种新的深度学习技术来实现高效、高精度和低占用的定位，以代替传统指纹定位过程中繁重的指纹库生成以及距离计算。该方法建立了一个特殊的卷积神经网络，并根据5G天线信号的接收信号强度指示、相位和到达角等特征量，选择合适的输入数据格式构造样本组建训练集，对该卷积神经网络进行训练。训练得到的卷积神经网络可以替代指纹定位中的庞大指纹库，非常有利于直接在5G移动设备端实现定位。虽然卷积神经网络在训练过程中需要大量时间，但在训练完毕后直接进行分类定位的速度非常快，可以保障定位实现的实时性。本文所实现的卷积神经网络权重与偏置所占内存不到0.5 MB，且能够在实际应用环境中以95%的定位准确率以及0.1 m的平均定位精度实现高精度定位。     

成分配比对稀土钨电极材料组织及力学性能影响

通过固液掺杂、等静压压制、中频烧结的方法，制备了不同的氧化镧、氧化钇、氧化锆三元掺杂成分比例的钨电极材料烧结棒材，探究了不同成分配比对样品显微组织、第二相粒子分布以及宏观力学性能的影响。结果表明，氧化镧、氧化钇、氧化锆三元复合添加能够有效改善第二相粒子在钨基体中的分布形态，降低第二相在晶界的过度富集，提高钨电极材料的综合力学性能。并且当添加成分镧、钇、锆质量比为3:1:1时，材料具有最好的综合力学性能，致密度可达96.04%，显微硬度可达549.37HV0.3，抗压强度可达3785MPa，原因是此配比下第二相粒子最为细小均匀，弥散程度最高，对基体晶粒的细化作用最好，该配比下钨基体平均晶粒尺寸达到10.3μm。     

Prediction of mode I fracture toughness of rock using linear multiple regression and gene expression programming

Prediction of mode I fracture toughness (K_IC) of rock is of significant importance in rock engineering analyses. In this study, linear multiple regression (LMR) and gene expression programming (GEP) methods were used to provide a reliable relationship to determine mode I fracture toughness of rock. The presented model was developed based on 60 datasets taken from the previous literature. To predict fracture parameters, three mechanical parameters of rock mass including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), and elastic modulus (E) have been selected as the input parameters. A cluster of data was collected and divided into two random groups of training and testing datasets. Then, different statistical linear and artificial intelligence based nonlinear analyses were conducted on the training data to provide a reliable prediction model of K_IC. These two predictive methods were then evaluated based on the testing data. To evaluate the efficiency of the proposed models for predicting the mode I fracture toughness of rock, various statistical indices including coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE) were utilized herein. In the case of testing datasets, the values of R², RMSE, and MAE for the GEP model were 0.87, 0.188, and 0.156, respectively, while they were 0.74, 0.473, and 0.223, respectively, for the LMR model. The results indicated that the selected GEP model delivered superior performance with a higher R² value and lower errors.