Polyaniline encapsulated Ti-MOF/CoS for efficient photocatalytic hydrogen evolution

We report the study of conductive polyaniline (PANI) chain embedded Ti-MOF functionalized with CoS as a cocatalyst for hydrogen evolution reaction (HER) application. The post synthetically modified hybrid photocatalyst PANI/Ti-MOF/CoS greatly influences the redox and e^? ? h⁺ separation process and exhibits an impressive rate of HER (～1322 μmol h^?1g^?1), suppressing the pristine Ti-MOF (～62 μmol h^?1g^?1) with apparent quantum yield (AQY) of ～3.2 and transient current response of ～46.4 μA cm^?2. In this system, Ti-MOF provides the circulation of Ti³⁺ and Ti⁴⁺ to the reaction of photocatalytic H₂ generation, where the additional PANI and CoS amended the performance of H₂ production through electron enrichment and thereby improving the stability and integrity of Ti-MOF. The Electrochemical studies demonstrated increased photocurrent by interweaving Ti-MOF crystal with PANI through cation-π interaction thereby enhancing interface connection and then promoting electron transfers. The charge dynamics revealed the initial charge transfer from photoexcited PANI to encapsulated MOF framework to boost the photocatalytic performance of the system. Further, the electron movement at the Ti-MOF/CoS interface is investigated through work function and electrochemical potential of electrons (Fermi level). DFT results demonstrate the importance of CoS in improving the photocatalytic performance of hybrid Ti-MOF catalyst, which leads to superior catalytic behaviour. These results establish that the encapsulation of catalytic active sites inside MOFs with desirable energy band gaps would be an ideal choice for the production of solar fuels.     

某矿快速掘进最优炮孔间距的选择

山西某矿5308底抽巷在掘进过程中速度慢、效率低，直接影响工作面的瓦斯抽采，为了改善上述情形，对炮孔间距进行研究。通过使用ANSYS软件对不同炮孔间距下快速掘进效果的模拟分析，并经现场验证，得出了适应该矿的最佳炮孔间距。结果表明：炮孔间距为500 mm时，爆破产生裂隙发育范围和岩石损伤区域都最大，快速掘进的效果最好。     

Effect of temperature on fast forging process of Mg-Ni samples for fast formation of Mg2Ni for hydrogen storage

Fast-Forging was used as a Severe Plastic Deformation technique to process Mg/Ni fine powder mixtures at a ratio corresponding to the eutectic composition. The samples were processed at different temperature, increased successively from room temperature up to above 500 °C. The one shock forging operation led to a reduction rate comprised between 80 to more than 90% depending of the applied temperature. Interestingly, a threshold temperature was pointed out for which amounts of the binary Mg₂Ni alloy were directly synthesized in increasing proportions when increasing temperature. A maximum amount of Mg₂Ni was synthesized according the nominal proportions at the highest applied temperature. Besides, numerical simulations were developed to consider and integrate to the forging process, the heat arising from the mechanical energy at deformation. Interestingly the total temperature at shock – heat applied to and heat developed in – indicates that the threshold temperature correspond well with the eutectic temperature as reported in the phase diagram. Early hydrogenation cycles suggest that both mechanical defects in brittle Mg and presence of amounts of Mg₂Ni as catalyst should be combined to optimize the hydrogenation characteristics.     

Development of a fast atom beam gun for surface-activated bonding

Surface-activated bonding (SAB), also called room-temperature bonding, is used in three-dimensional integration technology for semiconductor devices. An Ar fast atom beam (FAB) is used for SAB. However, conventional FAB guns must be replaced after hundreds of minutes of irradiation because carbon abrasion powders are generated by Ar ions sputtering in the gun. Therefore, this study develops a novel FAB gun with improved lifetime. The proposed FAB gun applies magnetic fields to guide Ar ions to reduce sputtering in the gun and improve irradiation efficiency. The proposed FAB gun indicates the possibility of improving gun lifetime.     

基于深度概率图模型的鲁棒人脸画像合成

针对基于数据驱动的人脸画像合成算法像素特征缺乏对光照变化和复杂背景的鲁棒性,常合成低质量的画像的问题,文中提出基于深度概率图模型的鲁棒人脸画像合成算法.采用预处理方法调整测试照片的光照亮度和人脸姿态,使之与训练照片一致.采用深度特征代替像素特征进行近邻匹配,采用深度概率图模型对画像重建权重和深度特征权重联合建模,得到合成画像的最佳重构表示.为了提高画像合成速度,提出快速近邻搜索方法.实验验证文中算法的鲁棒性和快速性.     

High-resolution ISAR imaging of fast rotating targets based on pattern-coupled Bayesian strategy for multiple measurement vectors

Very high resolution inverse synthetic aperture radar (ISAR) imaging of fast rotating targets is a complicated task. There may be insufficient pulses or may introduce migration through range cells (MTRC) during the coherent processing interval (CPI) when we use the conventional range Doppler (RD) ISAR technique. With compressed sensing (CS) technique, we can achieve the high-resolution ISAR imaging of a target with limited number of pulses. Sparse representation based method can achieve the super resolution ISAR imaging of a target with a short CPI, during which the target rotates only a small angle and the range migration of the scatterers is small. However, traditional CS-based ISAR imaging method generally faced with the problem of basis mismatch, which may degrade the ISAR image. To achieve the high resolution ISAR imaging of fast rotating targets, this paper proposed a pattern-coupled sparse Bayesian learning method for multiple measurement vectors, i.e. the PC-MSBL algorithm. A multi-channel pattern-coupled hierarchical Gaussian prior is proposed to model the pattern dependencies among neighboring range cells and correct the MTRC problem. The expectation-maximization (EM) algorithm is used to infer the maximum a posterior (MAP) estimate of the hyperparameters. Simulation results validate the effectiveness and superiority of the proposed algorithm.     

Ternary Blends of Renewable Fast Pyrolysis Bio-Oil,Advanced Bioethanol,and Marine Gasoil as Potential Marine Biofuel

An alternative for reducing emissions from marine fuel is to blend bio-oil from lignocellulose non-edible feedstocks to diesel fossil fuels. Phase diagrams of the ternary systems were built to represent the transition from heterogeneous regions to homogeneous regions. Four homogeneous blends of bio-oil of eucalyptus-bioethanol-marine gasoil were experimentally characterized with respect to the most important fuel parameters for marine engines: water content, flash point, low heating value, viscosity, and acidity. Blends with closer properties to marine gasoil replacement, lower costs, and environmental impacts should be tested for large engines.     

Self-learning residual model for fast intra CU size decision in 3D-HEVC

As an extension of the High Efficiency Video Coding (HEVC) standard, 3D-HEVC requires to encode multiple texture views and depth maps, which inherits the same quad-tree coding structure as HEVC. Due to the distinct properties of texture views and depth maps, existing fast intra prediction approaches were presented for the coding of texture views and depth maps, respectively. To further reduce the coding complexity of 3D-HEVC, a self-learning residual model-based fast coding unit (CU) size decision approach is proposed for the intra coding of both texture views and depth maps. Residual signal, which is defined as the difference between the original luminance pixel and the optimal prediction luminance pixel, is firstly extracted from each CU. Since residue signal is strongly correlated with the optimal CU partition, it is used as the feature of each CU. Then, a self-learning residual model is established by intra feature learning, which iteratively learns the features of the previously encoded coding tree unit (CTU) generated by itself. Finally, a binary classifier is developed with the self-learning residual model to early terminate CU size decision of both texture views and depth maps. Experimental results show the proposed fast intra CU size decision approach achieves 33.3% and 49.3% encoding time reduction on average for texture views and depth maps with negligible loss of overall video quality, respectively.     

Analysis and improvement of the influence of sample shape on Pu measurement results

ABSTRACT

The analysis method of Fast Neutron Multiplicity Counting (FNMC) plays an increasingly important role in the measurement of nuclear material properties. Based on the assumption of point model, fast neutron multiplicity measurement equation is derived which can be used to measure the mass of Pu sample. However, the deviation of the simulated measurement of 1 kg Pu sample reaches 16.6% and increases with mass. Because nonpoint source samples of different shapes do not fully satify the hypothesis. To correct this deviation, a set of fast neutron multiplicity counters was built by Geant4 to simulate and study the mass attribute of Pu samples.The cylindrical sources of different shapes and different masses were simulated, the self-multiplication factor and α coefficient were corrected.And the corresponding third-order polynomial fitting equation was obtained, the goodness of fit was greater than 0.970. In the same way, the spherical and spherical shell source samples in the mass range of 0–5 kg were analyzed, the corrected mass deviation of samples was less than 10% in this interval. The results show that the combination of the fast neutron multiplicity counter and parameter correction can accurately measure the sample mass attribute.     

面向电网实时运行风险的快速定级方法研究及应用

为满足电网运行实时风险评估时效性要求,解决电网运行实时风险评估与定级中效率与精度两者间协调的问题,在当前国家和主要电网企业规定的电网运行事故定级标准基础上提出了一种快速定级方法。快速定级方法充分考虑了电网运行实际特性,采取数据治理和算法重构两方面主要措施,对原判定方法进行优化处理。通过数据治理,大幅降低了对外部数据的依赖性,并取消了部分不必要的输入数据。采用算法重构,进一步将运行风险定级与实际业务流程紧密联系。以该快速定级方法为核心,构建了支撑电网运行风险分析与事故处置的实时运行风险管理系统,介绍了该系统的功能框架与系统架构。最后结合该系统在贵阳的实际应用情况,分析了快速定级方法的实际使用效益。