Differences between internal and external hydrogen effects on slow strain rate tensile test of iron-based superalloy A286

To investigate the evaluation method of hydrogen compatibility of A286 superalloy in high pressure hydrogen gas, SSRT tests of hydrogen-charged specimens were conducted at ambient temperature at various strain rates. The relative reduction in area (RRA), one of the ductility parameters, was determined. The hydrogen content in the hydrogen-charged specimen was the same as the equilibrium hydrogen content on the specimen surface at 150 °C in 70 MPa hydrogen gas. The strain rate dependence of RRA was smaller than that of RRA obtained in 70 MPa hydrogen gas at 150 °C. All the hydrogen-charged specimens showed slip-plane fractures in the grains in their cores. However, the specimens in 70 MPa hydrogen gas at 150 °C showed fracture surfaces morphology ranging from dimples to quasi-cleavages and intergranular fractures with decreasing strain rate. These dissimilarities are expected to arise from differences in the hydrogen concentration behaviors of the specimens during the deformation process.     

基于改进残差特征蒸馏的轻量级超分辨率网络

基于深度学习的图像超分辨率算法通常采用递归的方式或参数共享的策略来减少网络参数，这将增加网络的深度，使得运行网络花费大量的时间，从而很难将模型部署到现实生活中。为了解决上述问题，本文设计一种轻量级超分辨率网络，对中间特征的关联性及重要性进行学习，且在重建部分结合高分辨率图像的特征信息。首先，引入层间注意力模块，通过考虑层与层之间的相关性，自适应地分配重要层次特征的权重。其次，使用增强重建模块提取高分辨率图像中更精细的特征信息，以此得到更加清晰的重建图片。通过大量的对比实验表明，本文设计的网络与其他轻量级模型相比，有更小的网络参数量，并且在重建精度和视觉效果上都有一定的提升。     

ZnO·2.7Al2O3 nanocomposite with high optical transparency

Here we report a transparent dual-phase ZnO·2.7Al₂O₃ ceramic. The composite is pore-free and consists of thin nanosheets with a spinel phase and a hexagonal phase, while the two phases match closely in both lattice and refractive index. Such features result in excellent optical transmittance (maximum value >80% in the visible spectrum) at comparable phase volume. This work may provide a new thought for the rational structural design of optical nanocomposites.     

Influence of CO2 inleakage on the slight-alkalization of generator internal cooling water

The slight-alkalization of generator internal cooling water (GICW) is widely used to inhibit the corrosion of hollow copper conductor and thereby ensure the safe operation of the generator. CO₂ inleakage is increasingly identified as a potential security risk for GICW system. In this paper, the influence of CO₂ inleakage on the slight-alkalization of GICW was theoretically discussed. Based on the equilibriums of the CO₂-NaOH-H₂O system, CO₂ inleakage saturation was derived to quantify the amount of the dissolved CO₂ in GICW. This parameter can be directly calculated with the measured conductivity and the [Na⁺] of GICW. The influence of CO₂ inleakage on the slight-alkalization conditioning of GICW and the measurement of its water quality parameters were then analyzed. The more severe the inleakage, the narrower the water quality operation ranges of GICW, resulting in the more difficult the slight-alkalization conditioning of GICW. The temperature calibrations of the conductivity and the pH value of GICW show non-linear correlations with the amount of CO₂ inleakage and the NaOH dosage. This study provides insights into the influence of CO₂ inleakage on the slight-alkalization of GICW, which can serve as the theoretical basis for the actual slight-alkalization when CO₂ inleakage occurs.     

Improving accuracy of automatic optical inspection with machine learning

Electronic devices require the printed circuit board(PCB)to support the whole structure,but the assembly of PCBs suffers from welding problem of the electronic components such as surface mounted devices(SMDs)resistors.The automated optical inspection(AOI)machine,widely used in industrial production,can take the image of PCBs and examine the welding issue.However,the AOI machine could commit false negative errors and dedicated technicians have to be employed to pick out those misjudged PCBs.This paper proposes a machine learning based method to improve the accuracy of AOI.In particular,we propose an adjacent pixel RGB value based method to pre-process the image from the AOI machine and build a customized deep learning model to classify the image.We present a practical scheme including two machine learning procedures to mitigate AOI errors.We conduct experiments with the real dataset from a production line for three months,the experimental results show that our method can reduce the rate of misjudgment from 0.3%–0.5%to 0.02%–0.03%,which is meaningful for thousands of PCBs each containing thousands of electronic components in practice.     

Application of artificial neural network method to predict the breakage properties of PGE bearing chromite ore

In the present investigation, systematic grinding experiments were conducted in a laboratory ball mill to determine the breakage properties of low-grade PGE bearing chromite ore. The population balance modeling technique was used to study the breakage parameters such as primary breakage distribution (B_{i, j}) and the specific rates of breakage (S_i). The breakage and selection function values were determined for six feed sizes. The results stated that the breakage follows the first-order grinding kinetics for all the feed sizes. It was observed that the coarser feed sizes exhibit higher selection function values than the finer feed size. Further, an artificial neural network was used to predict breakage characteristics of low-grade PGE bearing chromite ore. The predicted results obtained from the neural network modeling were close to the experimental results with a correlation of determination R² = 0.99 for both product size and selection function.     

Double emulsion (W/O/W) gel stabilised by polyglycerol polyricinoleate and calcium caseinate as mangiferin carrier: insights on formulation and stability properties

Mangiferin (MGF) is a phenolic compound isolated from mango, but its poor solubility significantly limits its use. In this study, MGF was embedded into the inner aqueous phase of W₁/O/W₂ emulsions. Firstly, the dissolution method of MGF was determined. MGF remained stable in solution with pH 13 at 30 min, and its solubility reached 10 mg mL⁻¹. When the pH of MGF solutions was adjusted from pH 13 to pH 6, MGF did not immediately crystallise, providing sufficient time to construct the MGF-loaded W₁/O/W₂ emulsions. Subsequently, the MGF-loaded W₁/O/W₂ emulsions were constructed using polyglycerol polyricinoleate (PGPR) and calcium caseinate (CAS). The formation and stability of the W₁/O/W₂ emulsions were investigated. The MGF-loaded W₁/O/W₂ emulsions stabilised with 1% PGPR and 1% – 3% CAS exhibited a low viscosity, limited loading capacity, and poor stability. Conversely, the MGF-loaded W₁/O/W₂ emulsions stabilised by 3%PGPR–3%CAS exhibited optimal loading capacity (encapsulation efficiency = 95.31% and loading efficiency = 0.91%) and stability, which was attributed to the fact that high viscosity and gel state retarded the migration of inner aqueous phase. These results indicated that the W₁/O/W₂ emulsions stabilised by PGPR and CAS may be a potential alternative for encapsulating mangiferin.     

Numerical investigation of a convective hybrid nanofluids around a rotating sheet

Hybrid nanofluids are formulated with various kinds of base fluids. They are designed to provide good heat transfer performance. They can achieve this by dispersing various kinds of nanoparticles in the base materials. This new technology of formulating hybrid nanofluids has a wide range of applications in various industries such as solar energy, medical equipment, and aerospace. Keeping these applications in view, this study provides an insight into the effects of convective heat transport on a Hybrid nanofluid, across a rotating sheet with a variable heat source. In this investigation, the governing boundary layer partial differential equations were modified into the ordinary differential equations, by using the proper similarity transformations. Later, they were solved numerically, with the support of the Lobatto IIIA technique in MATLAB. The influence of the Richardson number on flow parameters was studied, and it was discovered that increasing Ri increases the velocity while decreasing temperature and concentration profiles. The impact of various other flow parameters on the flow fields and also on the behavior of Nusselt number, coefficient skin friction, and Sherwood number were studied and represented graphically. The outcomes were found to be in excellent accord when compared with quoted studies.     

Fabrication of high-efficiency Yb:Y2O3 laser ceramics without photodarkening

High-efficiency Yb:Y₂O₃ laser ceramics were fabricated using the vacuum-sintering plus hot isostatic pressing (HIP) without sintering additives. High-purity well-dispersed nanocrystalline Yb:Y₂O₃ powder was synthesized using a modified co-precipitation method in-house. The green bodies were first vacuum sintered at a temperature as low as 1430°C and then HIPed at 1450°C. Finally, the samples were air annealed at 800°C for 10 h. Although no sintering aids were used, full density of the samples with excellent optical homogeneity and an inline transmission of 80% at 400 nm could be obtained. Moreover, photodarkening phenomenon was not detected in the ceramics. Preliminary laser experiment with the fabricated ceramics in a two-mirror cavity has demonstrated 32 W continuous-wave (CW) output at ∼1077 nm with an optical-to-optical conversion efficiency of 58.2%. To the best of our knowledge, this is so far the highest CW output power and optical-to-optical conversion efficiency achieved with the Yb³⁺-doped sesquioxide ceramics in a simple two-mirror cavity.