Formation mechanism of subtrenches on cone-shaped patterned sapphire substrate

In this paper, the cone-shaped patterned sapphire substrates (PSS) were etched by an inductively couple plasma with BCl 3 as the reacting gas. The influence of the operating pressure and the RF bias power on subtrenches of the cone-shaped PSS and the formation mechanism of subtrenches were investigated. The profiles of patterns were characterized by FESEM (field emission scanning electron microscope). It showed that the subtrench size varied with the operating pressure and the RF bias power. As the operatin...     

Study on early warning index of spatial deformation for high concrete dam

Owing to the deficiency in early warning for high concrete dam,a formula was established to characterize the deformation behavior of high concrete dam as a whole.The early warning index of spatial deformation was calculated by low probability principle on the basis of the deformation entropy formula proposed.The steps were as follows.Firstly,the probability method was utilized to define the degree of order and degree of chaos for each survey point.Secondly,the weight distribution among the survey points was...     

Synthesis and photoconductivity study of phthalocyanine polymers. I. PAA–CuPc(NO2)2

Cu–dinitro–diamino phthalocyanine was synthesized and converted to the diazonium salt. Polyacrylamide bonded CuPc(NO₂)₂ [PAA–CuPc(NO₂)₂] (I) was synthesized by hot polymerization of acrylamide and this diazonium salt. Polymer(I) is water soluble and contains about 7 mol % CuPc(NO₂)₂ rings, which are covalently bonded to PAA. Polymer(I) shows good photoconductivity, which is much better than that of the corresponding phthalocyanine monomers. By doping with iodine (I₂), the photosensitivity of polymer(I) is increased, which through fluorescence analysis is explained by the fact that a charge–transfer complex (CTC) of polymer(I) with I₂ is formed. The influence of interface layer (IFL) and charge–transportation material (CTM) on the photoconductivity of polymer(I) were also studied.     

Tungsten Oxide Nanorods Array and Nanobundle Prepared by Using Chemical Vapor Deposition Technique

Tungsten oxide (WO₃) nanorods array prepared using chemical vapor deposition techniques was studied. The influence of oxygen gas concentration on the nanoscale tungsten oxide structure was observed; it was responsible for the stoichiometric and morphology variation from nanoscale particle to nanorods array. Experimental results also indicated that the deposition temperature was highly related to the morphology; the chemical structure, however, was stable. The evolution of the crystalline structure and surface morphology was analyzed by scanning electron microscopy, Raman spectra and X-ray diffraction approaches. The stoichiometric variation was indicated by energy dispersive X-ray spectroscopy and X-ray photoelectron spectroscopy.     

Microstructural studies of aluminium-silicon alloy reinforced with alumina fibres

The microstructure of an alumina fibre reinforced Al-7wt% Si alloy has been investigated. It was shown that the Al-Si eutectic structure which characterized this alloy was markedly changed by the presence of the fibres, with coarsening of silicon particles and a reduction in primary aluminium grain size. The coarse silicon particles exhibited twinning but no orientation relationship with the aluminium. Fine silicon precipitates were also present and these had a cube-cube orientation relationship with the aluminium lattice. Lath-like intermetallics, FeSiAl₅ and FeSi₂Al₄ with monoclinic and tetragonal structures, were identified which existed in equilibrium and had the epitaxial relationship (001)_mono//(001)_tet and [100]_mono//[100]_tet. The iron was a contaminant introduced in the course of composite fabrication.Dislocations were a common feature of the aluminium matrix, with a typical density of 4×10⁷mm^–2. Nevertheless, dislocation hardening of the metal matrix was not detected. No evidence of Mg₂Si precipitates in the metal matrix was found, but the small addition (0.2wt%) of magnesium to the alloy was discovered to segregate at the fibre-aluminium interface. This segregation was believed to result in improved wettability of the two constituents, encouraging the formation of a strong fibre-matrix bond, and producing desirable properties of the composite in the transverse direction.     

The optical properties of hot-pressed magnesium fluoride and single-crystal magnesium fluoride in the 0.1 to 9.0 μm range

A polycrystalline high-density magnesium fluoride, fabricated into plates or shapes by hot-pressing, exhibits high in-line transmittance from 2.5 to 6.0 m, and single-crystal magnesium fluoride extends from 0.1 to 6.0 m. The ultimate and practical transmittance of hot-pressed magnesium fluoride using intrinsic and extrinsic reflectance, absorptance and scattering mechanisms, are investigated. The intrinsic scattering mechanism due to the polycrystalline structure is basically responsible for the tremendous difference in transmittance in the short wavelength region of the spectrum. The in-line transmittance of polycrystalline and singlecrystal MgF₂ is discussed in terms of sample thickness.     

A Performance Evaluation of Classic Convolutional Neural Networks for 2D and 3D Palmprint and Palm Vein Recognition

Palmprint recognition and palm vein recognition are two emerging biometrics technologies. In the past two decades, many traditional methods have been proposed for palmprint recognition and palm vein recognition, and have achieved impressive results. However, the research on deep learning-based palmprint recognition and palm vein recognition is still very preliminary. In this paper, in order to investigate the problem of deep learning based 2D and 3D palmprint recognition and palm vein recognition in-depth, we conduct performance evaluation of seventeen representative and classic convolutional neural networks (CNNs) on one 3D palmprint database, five 2D palmprint databases and two palm vein databases. A lot of experiments have been carried out in the conditions of different network structures, different learning rates, and different numbers of network layers. We have also conducted experiments on both separate data mode and mixed data mode. Experimental results show that these classic CNNs can achieve promising recognition results, and the recognition performance of recently proposed CNNs is better. Particularly, among classic CNNs, one of the recently proposed classic CNNs, i.e., EfficientNet achieves the best recognition accuracy. However, the recognition performance of classic CNNs is still slightly worse than that of some traditional recognition methods.