The phosphorescence emission in undoped lead-halide Cs4PbBr6 single crystals at low temperature

Recently, all-inorganic cesium lead-halide perovskites have shown their promise for light emission applications, due to the excellent optical performance. Herein, we report that the initially nonphosphorescent undoped lead-halide Cs₄PbBr₆ single crystals (SCs) exhibit an ultralong phosphorescence emission under X-ray excitation at low temperatures. It is shown that the dramatic change has been taken place in radioluminescence spectra and the broad-band emission gradually appeared with the decrease of temperature. Below 210 K, the radioluminescence spectra can be deconvoluted into one narrow peak located at 530 nm and two broad peaks centered at 595 nm and 672 nm respectively. Subsequently, the time-dependent radioluminescence spectra in undoped lead-halide Cs₄PbBr₆ SCs were investigated. The ultralong phosphorescence emission can persist over 120 min at 70 K. We consider that ultralong phosphorescence originates from defect-related emission. To the best of our knowledge, our finding is the first time that undoped Cs₄PbBr₆ SCs exhibit the phosphorescence emission, which will offer a paradigm to motivate revolutionary applications on perovskite.     

The influence of FeNi nanoparticles on the microstructures and soft magnetic properties of FeSi soft magnetic composites

In this work, a new type of FeSi/FeNi soft magnetic powder core (SMPC) was successfully fabricated by coating FeNi nanoparticles on the surface of FeSi micrometer powder. The effects of different contents of FeNi nanoparticles on the micromorphology, internal structures, and soft magnetic properties of SMPCs were studied. The results show that FeNi nanoparticles adhere to the surface of FeSi powder, which can effectively fill the air gap between FeSi powder and is beneficial to the compaction of the powder cores during the pressing process. Thus, the density of the SMPCs is increased. Compared to FeSi SMPCs, the comprehensive soft magnetic properties of FeSi/FeNi SMPCs have been greatly improved. When adding 15 wt% FeNi nanoparticles, the SMPCs exhibit excellent magnetic properties with high effective permeability (increased by 43.8 %) and low core loss (decreased by 22.1 %). The high performance FeSi/FeNi SMPCs prepared in this work are expected to be widely used in power choke coils, uninterruptible power supplies, and boosts and inverter inductors.     

Identifying catalyst layer compositions of proton exchange membrane fuel cells through machine-learning-based approach

Membrane electrode assembly (MEA) is considered a key component of a proton exchange membrane fuel cell (PEMFC). However, developing a new MEA to meet desired properties, such as operation under low-humidity conditions without a humidifier, is a time- and cost-consuming process. This study employs a machine-learning-based approach using K-nearest neighbor (KNN) and neural networks (NN) in the MEA development process by identifying a suitable catalyst layer (CL) recipe in MEA. Minimum redundancy maximum relevance and principal component analysis were implemented to specify the most important predictor and reduce the data dimension. The number of predictors was found to play an essential role in the accuracy of the KNN and NN models although the predictors have self-correlations. The KNN model with a K of 7 was found to minimize the model loss with a loss of 11.9%. The NN model constructed by three corresponding hidden layers with nine, eight, and nine nodes can achieve the lowest error of 0.1293 for the Pt catalyst and 0.031 for PVA as a good additive blending in the CL of the MEA. However, even if the error is low, the prediction of PVA seems to be inaccurate, regardless of the model structure. Therefore, the KNN model is more appropriate for CL recipe prediction.     

Thermal behaviour and phases evolution during the sintering of porous inorganic membranes

Anorthite-based highly porous membranes were successfully produced using calcined oyster shell to enhance the pore network. The calcined oyster shells produce CaO responsible for the crystallisation of gehlenite and anorthite at relatively low temperature. While the crystallisation produced nano and meso size of intergranular pores, vitrification of feldspar is responsible for development of the capillary porosities. The increasing sintering temperature from 1200 °C to 1300 °C implies the increase in average pores radius from 1.2 μm to 14.3 μm due to the formation of spherical pores from vitrification. The combination of different class of porosities in the matrices results in the interconnection with improvement of the permeability of the porous network. Porosity, permeability and chemical stability were improved with 20 wt.% of calcined oyster shell addition allowing the possible development of high strength porous network which is promising for the membranes support and other applications including liquid separation as well as liquid filtration where high pressure is used.     

Slow strain rate technique for studying hydrogen induced cracking in 34CrMo4 high strength steel

Alloy hardened steels offer excellent combination of mechanical properties, hardenability and corrosion resistance. 34CrMo4 is a medium carbon, low alloy steel widely used due to a good combination of high-strength, toughness and wear resistance. However, this steel experiences hydrogen embrittlement (HE), a complex phenomenon depending on the composition and microstructure. This work estimates de loss of the mechanical properties caused by hydrogen in electrochemically H-charged specimens in absence of mechanical stress but also, at low strain rate and constant load. H-charging for 2 and 6 h induce YS losses of about 40% and 71% and UTS losses of 39% and 59%, respectively. The synergistic effect of the stress and the H-charging process leads to a higher loss, 91%, and a faster brittle fracture even though hydrogen content is similar to those firstly H-charged and then tested in air.     

Improving the prediction of petroleum reservoir characterization with a stacked generalization ensemble model of support vector machines

The ensemble learning paradigm has proved to be relevant to solving most challenging industrial problems. Despite its successful application especially in the Bioinformatics, the petroleum industry has not benefited enough from the promises of this machine learning technology. The petroleum industry, with its persistent quest for high-performance predictive models, is in great need of this new learning methodology. A marginal improvement in the prediction indices of petroleum reservoir properties could have huge positive impact on the success of exploration, drilling and the overall reservoir management portfolio. Support vector machines (SVM) is one of the promising machine learning tools that have performed excellently well in most prediction problems. However, its performance is a function of the prudent choice of its tuning parameters most especially the regularization parameter, C. Reports have shown that this parameter has significant impact on the performance of SVM. Understandably, no specific value has been recommended for it. This paper proposes a stacked generalization ensemble model of SVM that incorporates different expert opinions on the optimal values of this parameter in the prediction of porosity and permeability of petroleum reservoirs using datasets from diverse geological formations. The performance of the proposed SVM ensemble was compared to that of conventional SVM technique, another SVM implemented with the bagging method, and Random Forest technique. The results showed that the proposed ensemble model, in most cases, outperformed the others with the highest correlation coefficient, and the lowest mean and absolute errors. The study indicated that there is a great potential for ensemble learning in petroleum reservoir characterization to improve the accuracy of reservoir properties predictions for more successful explorations and increased production of petroleum resources. The results also confirmed that ensemble models perform better than the conventional SVM implementation.     

Experimental study on the permeability and self-healing capacity of geosynthetic clay liners in heavy metal solutions

Geosynthetic clay liners (GCLs), which have a very low permeability to water and a considerably high self-healing capacity, are widely used in liner systems of landfills. In this study, a series of experimental tests were carried out under complex conditions on typical commercial GCLs from China. In particular, the effects of pH values and lead ions (Pb²⁺) were tested in addition to other factors. The swelling properties of natural bentonite encapsulated between geotextile components in the GCLs were tested first. The swelling capacity was reduced rapidly at pH values < 3 and concentrations of Pb²⁺ >40 mM. Permeability tests on GCLs with different concentrations of lead ions were then performed by using the self-developed multi-link flexible wall permeameter, and data showed that increases in lead ion concentrations greatly improved the permeability. Finally, self-healing capacity tests were conducted on needle-punched GCLs under different levels of damage. Results showed that the GCLs have a good self-healing capacity with small diameter damage holes (2 mm, close to three times the original aperture), but with a damage aperture larger than 15% of the sample area, the self-healing capacity could not prevent leakage; hence, in certain situations it will be necessary to repair the damage to meet the anti-seepage requirement.     

Design and optimization of ceramic membrane structure: From the perspective of flux matching between support and membrane

The support flux was first investigated as a separate influencing factor for its effect on performances of ceramic filtration membranes. Three pre-membranes were prepared by tape-casting and then transfer-coated to supports to form dual-layer ceramic membranes after sintering. Experiments demonstrated that membrane layers with almost the same properties were obtained despite the huge difference in support flux. When the support flux increases from 3.120 to 97.53 m³m^?2h^?1, the flux of these three membrane series have increased by 75%, 186% and 228%, respectively. Experimental rules can provide structural design and evaluation from the perspective of permeability. The limit membrane flux of a certain system was derived according to the resistance distribution law of internal membrane structure and the Darcy's theorem. On this basis, a method for designing support flux was proposed. Furthermore, we present a criterion to quickly and easily evaluate the match between the support and the top layer, which is the ratio of membrane resistance to total resistance. Finally, the filtration resistance of penetration caused by suction of membrane particles into the support was measured for the first time, taking the advantage of the transfer-coating method that inherently free of penetration. Our works are expected to deepen the understanding of the ceramic membrane structure and provided guidance for its rational design and optimization.     

Low cycle fatigue behavior of a eutectic 80Au/20Sn solder alloy

The eutectic 80Au/20Sn solder alloy is widely used in high power electronics and optoelectronics packaging. In this study, low cycle fatigue behavior of a eutectic 80Au/20Sn solder alloy is reported. The 80Au/20Sn solder shows a quasi-static fracture characteristic at high strain rates, and then gradually transforms from a transgranular fracture (dominated by fatigue damage) to intergranular fracture (dominated by creep damage) at low strain rates with increasing temperature. Coffin-Manson and Morrow models are proposed to evaluate the low cycle fatigue behavior of the 80Au/20Sn solder. Besides, the 80Au/20Sn solder has enhanced fatigue resistance compared to the 63Sn/37Pb solder.     

Voltage reference architectures for low-supply-voltage low-power applications

This paper presents a voltage reference generator architecture and two different realizations of it that have been fabricated within a standard 0.18 μm CMOS technology. The architecture takes the advantage of utilizing a sampled-data amplifier (SDA) to optimize the power consumption. The circuits achieve output voltages on the order of 190 mV with temperature coefficients of 43 ppm/°C and 52.5 ppm/°C over the temperature range of 0 to 120°C without any trimming with a 0.8 V single supply. The power consumptions of the circuits are less then 500 nW while occupying an area of 0.2 mm² and 0.08 mm², respectively.