Kinetics of light-induced degradation in compensated boron-doped silicon investigated using photoluminescence and numerical simulation

We use photoluminescence to observe light-induced degradation in silicon in real time. Numerical simulations are used to match our results and lifetime decay data from the literature with theoretical models for the generation of the light-induced boron–oxygen defects. It is found that the existing model of the slowly generated defect SRC, where its saturated concentration is a function of the majority carrier concentration, does not explain certain results in both p- and n-type samples. A new model is proposed in which the saturated SRC concentration is controlled by the total hole concentration under illumination.     

Microstructure and mechanical properties of laser beam welded Al–Li alloy 2060 with Al–Mg filler wire

Alloy 2060-T8 is a newly developed high-strength Al–Li alloy for applications in aircraft industry. Crack-free welds were obtained in laser beam welding with 5087 filler wire under optimized welding conditions. In this paper, fusion zone microstructure and joint mechanical properties were investigated. Microstructure typical for the weld metal consists of α-Al matrix with a few nanoscale precipitates inside and a coarse icosahedral quasicrystalline T₂ phase at the dendritic and grain boundaries. The quasicrystalline occurred normally in Al–Li–Cu alloys with higher Li contents. Our investigations show that the icosahedral quasicrystalline phase T₂ phase forms in the laser-welded Al–Li alloy 2060 with lower Li content as a result of segregation and replacement of Mg element. The joint tensile strength in as-welded condition is around 317 MPa, about 63% of that of the base metal, and fracture occurs within the fusion zone.     

改进HSR-FCN的服装图像识别分类算法研究

目前网络上的服装图像数量增长迅猛，对于大量服装图像实现智能分类的需求日益增加。将基于区域的全卷积网络（Region-Based Fully Convolutional Networks，R-FCN）引入到服装图像识别中，针对服装图像分类中网络训练时间长、形变服装图像识别率低的问题，提出一种新颖的改进框架HSR-FCN。新框架将R-FCN中的区域建议网络和HyperNet网络相融合，改变图片特征学习方式，使得HSR-FCN可以在更短的训练时间内达到更高的准确率。在模型中引入了空间转换网络，对输入服装图像和特征图进行了空间变换及对齐，加强了对多角度服装和形变服装的特征学习。实验结果表明，改进后的HSR-FCN模型有效地加强了对形变服装图像的学习，且在训练时间更短的情况下，比原来的网络模型R-FCN平均准确率提高了大约3个百分点，达到96.69%。     

Enhanced propene/ethene selectivity for methanol conversion over pure silica zeolite: Role of hydrogen-bonded silanol groups

Pure silica zeolite with MEL structure (Si-ZSM-11) was firstly reported as an efficient Methanol-to-Propene (MTP) catalyst in methanol conversion, with higher propene yield (14.0 wt.%) and propene/ethene ratio (5.9) than H-ZSM-11 zeolite with a Si/Al ratio of 26 (7.4 wt.% and 1.9, respectively). Hydrogen-bonded silanol groups in Si-ZSM-11 are weakly acidic and act as active sites in methanol conversion, predominantly promoting propene production and inhibiting side reactions.     

Theoretical investigation of solvent effects on the selective hydrogenation of furfural over Pt(111)

It was well known that solvent effect plays a very important role in the catalytic reaction. There are many theoretical studies on the solvent effect in homogeneous catalysis while there are few theoretical studies on the solvent effect in the heterogeneous catalytic reaction and there has been no work to investigate the solvent effect on furfural transformation in heterogeneous catalysis. In the present work, both the density functional calculations and the microkinetic analysis were performed to study the selective hydrogenation of furfural over Pt(111) in the presence of methanol as well as toluene and compared with that in the gas condition. The present results indicated that the methanol can enhance the adsorption strength of furfural and other oxygen-containing reaction species due to its relatively strong polarity properties and this can be a main reason for solvent-induced high activity and selectivity. Another reason is that reaction paths study showed that the presence of methanol solvent makes the dehydrogenation of furfural less thermochemical due to the fact that furfural is more stabilized than that of dehydrogenation species, and methanol also has an inhibition effect on the dehydrogenation of furfural in the kinetic aspect, and further energetic span theory proves highest activity and selectivity for hydrogenation in methanol solvent of vapor, methanol and toluene. Moreover, microkinetic model simulation demonstrated that the activity and selectivity of hydrogenation in methanol is both higher than that in vapor and toluene. The much higher activity in methanol is due to the stabilized adsorbed reactants in the surface, which leads to a higher surface coverage of furfural. It might be proposed based on the present work that a solvent with relatively strong polarity may be favorable for the high selective hydrogenation of furfural.     

Large piezoelectricity and potentially activated polarization reorientation around relaxor MPB in complex perovskite

Improving piezoelectric performance is always favorable to further enhance the sensitivity and accuracy of piezoelectric devices. Here, a complex piezoelectric system of Pb(Ni_1/3Nb_2/3)O₃-Pb(Yb_1/2Nb_1/2)O₃-Pb(Hf_0.1Ti_0.9)O₃ is designed and investigated in detail. Optimized piezoelectric response of ～ 880 pC/N is achieved at the composition of 0.51PNN-0.09PYN-0.40PHT. The characterization of TEM and In-situ high-energy synchrotron diffraction indicate that nanodomain growth and microdomain switching occurs in succession at around coercive electric field. Most interestingly, the coexisted tetragonal and rhombohedral-like phase transforms into multiple monoclinic-like phases with polarization vectors aligned as close to the electric field direction as possible under the strong electric field. The enhanced polarization instability in this complex morphotropic phase boundary sample should be ascribed to the strong local heterogeneity. The novel polarization rotation behavior found in this work would be important guidance for designing high-performance piezoceramics.     

Effect of steel slag on 3D concrete printing of geopolymer with quaternary binders

A new type of 3D-printable ‘one-part’ geopolymer was synthesized with fly ash (FA), granulated blast furnace slag (GBFS), steel slag (SS) and flue gas desulfurization gypsum (FGD). The effects of SS content (0–40%) on the rheological properties, 3D-printability, mechanical anisotropy and reaction kinetics of geopolymer were investigated. The yield stress and plastic viscosity monotonically decreased with the increasing SS content. Contrarily, the geopolymer with 10% of SS presented better extrudability, buildability and mechanical strength than those with 0, 20%, 30% and 40% of SS. This was mainly attributed to the conflicting influence of SS on geopolymerization, of which the OH^? produced by hydration of SS raised the alkalinity of the reaction system and accelerated the dissolution of SiO₄^4? and AlO₄^5?, while the low reactivity prohibited the following polymerization process. Furthermore, the 3D-printed geopolymer presented more compact microstructure and less mechanical anisotropy thanks to the crosslinking of morphologically complementary products, including N(C)-A-S-H, C–S–H, AFt and CH, formed via synergistic reaction of FA-GBFS-SS-FGD system.     

A gradient boosting decision tree approach for insider trading identification: An empirical model evaluation of China stock market

Insider trading is a kind of criminal behavior in stock market by using nonpublic information. In recent years, it has become the major illegal activity in China’s stock market. In this study, a combination approach of GBDT (Gradient Boosting Decision Tree) and DE (Differential Evolution) is proposed to identify insider trading activities by using data of relevant indicators. First, insider trading samples occurred from year 2007 to 2017 and corresponding non-insider trading samples are collected. Next, the proposed method is trained by the GBDT, and initial parameters of the GBDT are optimized by the DE. Finally, out-of-samples are classified by the trained GBDT–DE model and its performances are evaluated. The experiment results show that our proposed method performed the best for insider trading identification under time window length of ninety days, indicating the relevant indicators under 90-days time window length are relatively more useful. Additionally, under all three time window lengths, relative importance result shows that several indicators are consistently crucial for insider trading identification. Furthermore, the proposed approach significantly outperforms other benchmark methods, demonstrating that it could be applied as an intelligent system to improve identification accuracy and efficiency for insider trading regulation in China stock market.     

Fabrication and properties of Si3N4 based ceramics using combustion synthesized powders

Silicon nitride (Si₃N₄) based ceramics were fabricated with β-SiAlON and Si₃N₄ powders synthesized by combustion synthesis method via power injection molding (PIM). In the PIM process, the solids loading for each material was first determined from the results of the torque rheometer experiment. The mixing process was repeated to produce the homogeneous feedstock, and homogeneity of feedstocks was evaluated by observing the shear viscosity with time at a constant shear rate. The rheological behavior of feedstocks was investigated using capillary rheometer. It found that both feedstocks have no problem in injection molding. The binder decomposition behavior was also investigated, and a wax-polymer binder system was nearly removed by the optimized solvent and thermal debinding processes. Thereafter, the debound samples were sintered at 1750 and 1800 °C for 4 h in nitrogen atmosphere. Regardless of sintering temperature, the relative density of higher than about 96% was achieved. When comparing mechanical properties including bending strength, Vickers hardness and fracture toughness, Si₃N₄ with 2 wt% Y₂O₃ and 5 wt% Al₂O₃ (Si₃N₄+2Y5A) had higher values than β-SiAlON with 4 wt% Y₂O₃ (β-SiAlON+4Y) regardless of sintering temperature. It was supported by observing the microstructures of the plasma-etched samples.     

Mitigating Hydrological Risk with Energy Derivatives

The variability of river inflows affects the energy production of hydropower generators and may result in reductions in revenues that can be financially disruptive for these producers. Recent climatic changes have highlighted the risks involved in hydroelectriciy production in Brazil. In this paper, we propose a different approach to formulating a collar derivative, namely an Inverted Collar, to mitigate hydrological risk considering the particularities of Brazil's energy regulatory environment. In addition, we propose a customized collar-by-difference as a variation of the collar model. The effect of these derivatives is analyzed considering electricity market price and power generation uncertainty for a typical hydro generator. The results suggest that these derivatives are effective tools to manage hydrological risk during period of great climatic volatility, such as the height of the drought period experienced by Brazil in 2016. The results also indicate that our models outperform traditional commercial hedging commonly practiced by hydropower producers in the country.