Preparation of nanocrystalline nickel oxide from nickel hydroxide using spark plasma sintering and inverse Hall-Petch related densification

Nanocrystalline nickel oxide (NiO) was prepared from nickel hydroxide by Spark plasma sintering (SPS) and the mechanisms involved in the densification of NiO were studied. Reverse precipitated nickel hydroxide powders were SPS processed at 400, 600 and 700?°C with 70?MPa pressure. Pure NiO with 12?nm crystallite size formed after 400?°C sintering process. However NiO grains had grown to 18 and 38?nm after 600 and 700?°C sintering respectively. NiO pellets prepared using 600 and 700?°C SPS sintering schedules had relative densities of 83% and 94% respectively. Two displacement rate regimes were observed during densification of NiO in both 600 and 700?°C sintering processes. Decomposition of nickel hydroxide and particle sliding of NiO led to first displacement rate maximum while inverse Hall-Petch based plastic deformation facilitated densification during the constant second displacement rate regime. No densification occurred during sintering holding times indicating the limited role that diffusion played during densification.     

Estimation of the Stress-Strength Reliability for Exponentiated Pareto Distribution Using Median and Ranked Set Sampling Methods

In reliability analysis, the stress-strength model is often used to describe the life of a component which has a random strength (X) and is subjected to a random stress (Y). In this paper, we considered the problem of estimating the reliability R=P [Y<X] when the distributions of both stress and strength are independent and follow exponentiated Pareto distribution. The maximum likelihood estimator of the stress strength reliability is calculated under simple random sample, ranked set sampling and median ranked set sampling methods. Four different reliability estimators under median ranked set sampling are derived. Two estimators are obtained when both strength and stress have an odd or an even set size. The two other estimators are obtained when the strength has an odd size and the stress has an even set size and vice versa. The performances of the suggested estimators are compared with their competitors under simple random sample via a simulation study. The simulation study revealed that the stress strength reliability estimates based on ranked set sampling and median ranked set sampling are more efficient than their competitors via simple random sample. In general, the stress strength reliability estimates based on median ranked set sampling are smaller than the corresponding estimates under ranked set sampling and simple random sample methods.     

Self-repair of structural and functional composites with intrinsically self-healing polymer matrices: A review

Self-healing is a smart and promising way to make materials more reliable and longer lasting. In the case of structural or functional composites based on a polymer matrix, very often mechanical damage in the polymer matrix or debonding at the matrix–filler interface is responsible for the decrease in intended properties. This review describes the healing behavior in structural and functional polymer composites with a so-called intrinsically self-healing polymer as the continuous matrix. A clear similarity in the healing of structural and functional properties is demonstrated which can ultimately lead to the design of polymer composites that autonomously restore multiple properties using the same self-healing mechanism.     

古建筑木结构透榫节点力学模型研究

为研究古建筑木结构透榫节点的M-θ力学模型，在分析透榫节点构造特征与受力机理的基础上，建立其数值模型，用透榫节点的试验数据验证了该数值模型的正确性，并分析了节点缝隙、木材横纹弹性模量和大榫头长度对透榫节点受弯承载力的影响。根据受力分析结果，建立以弹性点、屈服点与极限点为特征点的三折线多参数M-θ力学模型，其结果与多数的试验结果基本吻合，并将该力学模型应用于木构架的受力分析。研究结果表明：透榫节点的滞回耗能能力强，节点的变形主要集中在榫头处。当榫头与卯口之间的缝隙增大时，节点的受弯承载力降低。随木材横纹弹性模量的提高和大榫头长度的增加，节点的受弯承载力有一定提高。文章建立的M-θ力学模型能较好反映透榫节点的受力过程，适用于木构架的受力分析，其荷载 位移骨架曲线与试验结果基本吻合。研究成果可为古建筑木结构的维修与保护提供参考。     

Aqueous One-pot Synthesis of Glycopolymers by Glycosidase-catalyzed Glycomonomer Synthesis Using 4,6-Dimetoxy Triazinyl Glycoside Followed by Radical Polymerization

Glycopolymers have attracted increased attention as functional polymeric materials, and simple methods for synthesizing glycopolymers remain needed. This paper reports the aqueous one-pot and chemoenzymatic synthesis of four types of glycopolymers via two reactions: the β-galactosidase-catalyzed glycomonomer synthesis using 4,6-dimetoxy triazinyl β-D-galactopyranoside and hydroxy group-containing (meth)acrylamide and (meth)acrylate derivatives as the activated glycosyl donor substrate and as the glycomonomer precursors, respectively, followed by radical copolymerization of the resulting glycomonomer and excess glycomonomer precursor without isolating the glycomonomers. The resulting glycopolymers bearing galactose moieties exhibited specific and strong interactions with the lectin peanut agglutinin as glycoclusters.     

Bearing Failure Optimization of Composite Double-Lap Bolted Joints Based on a Three-Step Strategy Marked By Feasible Region Reduction and Model Decoupling

To minimize the mass and increase the bearing failure load of composite doublelap bolted joints, a three-step optimization strategy including feasible region reduction, optimization model decoupling and optimization was presented. In feasible region reduction, the dimensions of the feasible design region were reduced by selecting dominant design variables from numerous multilevel parameters by sensitivity analyses, and the feasible regions of variables were reduced by influence mechanism analyses. In model decoupling, the optimization model with a large number of variables was divided into various sub-models with fewer variables by variance analysis. In the third step, the optimization sub-models were solved one by one using a genetic algorithm, and the modified characteristic curve method was adopted as the failure prediction method. Based on the proposed optimization method, optimization of a double-lap single-bolt joint was performed using the ANSYS^® code. The results show that the bearing failure load increased by 13.5% and that the mass decreased by 8.7% compared with those of the initial design of the joint, which validated the effectiveness of the three-step optimization strategy.     

Tribological behavior of Zr-based bulk metallic glass sliding against polymer,ceramic, and metal materials

The tribological properties of zirconium-based bulk metallic glass (BMG) sliding against polymers, steels, and ceramics at different loads and speeds were investigated. Acoustic emission (AE) technology was used to analyze wear states. The frictional coefficients of the BMG slid against the steel and ceramic balls were high but decreased with increased applied normal load and sliding speed. As the steel balls were more ductile than the ceramic ones, the steel–BMG sliding pairs generated weaker AE signals and exhibited larger wear rates. The BMG tested against the polymer balls had much lower and more stable frictional coefficients than the ones against the steel or ceramic balls because of transferred polymer layers on the BMG surfaces. The BMG against the polymer balls also exhibited the highest AE signals among the three types of counter materials used, indicating that abrasive wear dominated in the polymer-BMG sliding pairs. These results demonstrated the potential application of the BMG as a new tribomaterial that could be an alternative to the traditional crystalline metals for various counter materials.     

Formation of ST12 phase Ge nanoparticles in ZnO thin films

In this work, we focus on the Ge nanoparticles (Ge-np) embedded ZnO multilayered thin films. Effects of reactive and nonreactive growth of ZnO layers on the rapid thermal annealing (RTA) induced formation of Ge-np have been specifically investigated. The samples were deposited by sequential r.f. and d.c. sputtering of ZnO and Ge thin film layers, respectively on Si substrates. As-prepared thin film samples have been exposed to an ex-situ RTA at 600 °C for 60 s under forming gas atmosphere. Structural characterizations have been performed by X-ray Diffraction (XRD), Raman scattering, Secondary Ion Mass Spectroscopy (SIMS), and Scanning Electron Microscopy (SEM) techniques. It has been realized that reactive or nonreactive growth of ZnO layers significantly influences the morphology of the ZnO: Ge samples, most prominently the crystal structure of Ge-np. XRD and Raman analysis have revealed that while reactive growth results in a mixture of diamond cubic (DC) and simple tetragonal (ST12) Ge-np, nonreactive growth leads to the formation of only DC Ge-np upon RTA process. Formation of ST12 Ge-np has been discussed based on structural differences due to reactive and nonreactive growth of ZnO embedding layer.     

Plasmonic-excitonic multi-hybrid glass-based nanocomposites incorporating Ag plus core-shell CdSe/CdS and alloyed CdSxSe1−x nanoparticles

Successful fabrication of glass-based hybrid nanocomposites (GHNCs) incorporating Ag, core-shell CdSe/CdS and CdS_xSe_1?x nanoparticles (NPs) is herein reported. Both metallic (Ag) and semiconductor (CdSe/CdS) NPs were pre-synthesized, suspended in colloids and added into the sol-gel reaction medium which was used to fabricate the GHNCs. During fabrication of the nanocomposites a fraction (20–60%) of core-shell CdSe/CdS NPs was alloyed into CdS_xSe_1?x (0.20 < x < 0.35) NPs without changing morphology. Modulation of in situ alloying is possible via the relative content of organics added into the sol-gel protocol. Within colloids Ag (core-shell CdSe/CdS) NPs presented average diameter and polydispersity index of 49.5 nm (4.2 nm) and 0.41 (0.21), respectively. On the other hand, the Ag (core-shell CdSe/CdS) NPs’ average diameter and polydispersity index assessed from the GHNCs were respectively 51.5 nm (4.1 nm) and 0.43 (0.25), revealing negligible aggregation of the nanophases within the glass template. The new GHNCs herein introduced presented two independent excitonic transitions associated to homogenously dispersed semiconductor NPs, peaking around 420 nm (core-shell CdSe/CdS) and 650 nm (CdS_xSe_1?x) and matching the plasmonic resonance (Ag NPs) in the 400–500 nm range. We envisage that the new GHNCs represent very promising candidates for superior light manipulation while illuminated with multiple laser beams in quantum interference-based devices.     

Image and Feature Space Based Domain Adaptation for Vehicle Detection

The application of deep learning in the field of object detection has experienced much progress. However, due to the domain shift problem, applying an off-the-shelf detector to another domain leads to a significant performance drop. A large number of ground truth labels are required when using another domain to train models, demanding a large amount of human and financial resources. In order to avoid excessive resource requirements and performance drop caused by domain shift, this paper proposes a new domain adaptive approach to cross-domain vehicle detection. Our approach improves the cross-domain vehicle detection model from image space and feature space. We employ objectives of the generative adversarial network and cycle consistency loss for image style transfer in image space. For feature space, we align feature distributions between the source domain and the target domain to improve the detection accuracy. Experiments are carried out using the method with two different datasets, proving that this technique effectively improves the accuracy of vehicle detection in the target domain.