Controllable fabrication of SnO2-coated multiwalled carbon nanotubes by chemical vapor deposition

A simple and efficient approach for coating multiwalled carbon nanotubes (MWCNTs) with size-controllable SnO₂ nanoparticles by chemical vapor deposition has been developed using tin hydride (SnH₄) gas as the source of SnO₂ at 550 °C. The size and coverage of SnO₂ nanoparticles can be adjusted by simply controlling the deposition time and the flow rate of the SnH₄/N₂ mixture gas during the CVD procedure. In addition, by using the MWCNTs as a sacrificial template, a kind of one-dimensional chain-like SnO₂ nanostructure has been synthesized by increasing the deposition temperature to 730 °C. This technique may provide a good way to produce tunable SnO₂-MWCNT composites.     

基于彩色立体视觉的障碍物快速检测方法

Real-time obstacle detection method is a key technique for machine vision based mobile robot and au-tonomous land vehicle navigation in unstructured environments. In this paper o considering the real-time requirement for stereo matching algorithm, an adaptive color segmentation method for possible obstacle region detection is first developed based on the color feature, and a simple region based stereo matching algorithm of binocular vision for realobstacle recognition is also introduced. Obstacle detection is implemented by combining the road color adaptive seg-mentation method and region based stereovision method. Lots of experiment results show that the proposed approachcan detect obstacle quickly and effectively, and this algorithm is particularly suited for road environments in which the road is relatively flat and of roughly the same color.     

Strengthening Mechanism and Microstructure of Deformable Ti Particles Reinforced AZ91 Composite

In this study, the deformable titanium (Ti) particles reinforced AZ91 composite was successfully prepared by powder metallurgy and subsequent extrusion. The mechanical properties and microstructural evolution of pure AZ91 and 5Ti/AZ91 composite were studied. The yield strength, ultimate tensile strength, and elongation of 5Ti/AZ91 composite are measured to be 212 MPa, 323 MPa, and 10.1%, respectively. Microstructure analysis revealed that Ti particles are elongated along the extrusion direction, forming a discontinuous strip Ti particles, fine precipitated Mg₁₇Al₁₂ phase inhibits dynamic recrystallization (DRX) behavior through Zener pinning effect and hinders the growth of matrix grains, resulting in refiner grains of 5Ti/AZ91 composite. Heterogeneous deformed Ti particles and magnesium (Mg) matrix to generate additional heterogeneous deformation-induced (HDI) strengthening. Heterogeneous deformation-induced strengthening mainly contributed to the increment of yield strength for 5Ti/AZ91 composite.     

A robust method based on ICA and mixture sparsity for edge detection in medical images

In this paper, a robust edge detection method based on independent component analysis (ICA) was proposed. It is known that most of the ICA basis functions extracted from images are sparse and similar to localized and oriented receptive fields. In this paper, the L ^p norm is used to estimate sparseness of the ICA basis functions, and then, the sparser basis functions were selected for representing the edge information of an image. In the proposed method, a test image is first transformed by ICA basis functions, and then, the high-frequency information can be extracted with the components of the selected sparse basis functions. Furthermore, by applying a shrinkage algorithm to filter out the components of noise in the ICA domain, we can readily obtain the sparse components of the noise-free image, resulting in a kind of robust edge detection even for a noisy image with a very low SN ratio. The efficiency of the proposed method for edge detection is demonstrated by experiments with some medical images.     

Microstructure and Mechanical Properties of Mg–RE–TM Cast Alloys Containing Long Period Stacking Ordered Phases: A Review

Casting magnesium alloys hold the greatest share of magnesium application products due to their short processing period, low cost and near net shape forming. Compared with conventional commercial magnesium alloys or other Mg–RE-based alloys, the novel Mg–RE–TM cast alloys with long period stacking ordered(LPSO) phases usually possess a higher strength and are promising candidates for aluminum alloy applications. Up to now, two ways: alloying design and casting process control(including subsequent heat treatments), have been predominantly employed to further improve the mechanical properties of these alloys. Alloying with other elements or ceramic particles could alter the solidifi cation pattern of alloys, change the morphology of LPSO phases and refi ne the microstructures. Diff erent casting techniques(conventional casting, rapidly solidifi cation, directional solidifi cation, etc.) introduce various microstructure characteristics, such as dendritic structure, nanocrystalline, metastable phase, anisotropy. Further heat treatments could activate the transformation of various LPSO structures and precipitation of diverse precipitates. All these evolutions exert great impacts on the mechanical properties of the LPSO-containing alloys. However, the underlying mechanisms still remain a subject of debate. Therefore, this review mainly provides the state of the art of the casting magnesium alloys research and the accompanying challenges and summarizes some topics that merit future investigation for developing high-performance Mg–RE–TM cast alloys.     

Image super-resolution based on two-level residual learning CNN

In recent years, CNN has been used for single image super-resolution (SR) with its success of in the field of computer vision. However, in the recovery process, there are always some high-frequency components that cant be recovered from low-resolution images to high-resolution ones by using existing CNN-based methods. In this paper, we propose an image super-resolution method based on CNN, which uses a two-level residual learning network to learn residual components, i.e., high-frequency components. We use the Super-Resolution Convolutional Neural Network (SRCNN) as the network structure in each level so that our proposed method can achieve the high-resolution images with high-frequency components that cant be obtained by the existing methods. In addition, we analyze the proposed method with considering three kinds of residual learning networks, which are different in the structure and superimposed layers of the residual learning network. In the experiments, we investigate the performance of the proposed method with various residual learning networks and the effect of image super-resolution to image captioning task.

     

Improved Corrosion Resistance in AZ61 Magnesium Alloys Induced by Impurity Reduction

The effect of impurity element Fe on corrosion behavior of AZ61 magnesium alloys in various states has been investigated by immersion test and hydrogen evolution measurements in 3.5% sodium chloride solution.The corrosion rate is found to relay on the impurity Fe concentration in the alloys and decreases with decreasing Fe content.When Fe content drops from 150 ppm to 10 ppm,the corresponding corrosion rates under as-cast and solution treatment conditions are reduced from 8.54 mm/a and 8.61 mm/a to 2.54 mm/a and 0.21 mm/a,respectively.The corrosion pattern of the AZ61 alloys is the localized corrosion,and the galvanic couples are formed among the impurity particles,second-phase particles and the matrix.The Fe impurity particles tend to act as main cathodic to form micro-galvanic cell with the α-Mg matrix,which is harmful for corrosion resistance of AZ61 alloy.     

稀土改性玻璃纤维对PTFE复合材料摩擦磨损性能的影响

分别用硅烷偶联剂SG-Si900(SGS)、含SG-Si900的稀土溶液(SGS/RES)和稀土溶液(RES)对玻璃纤维进行表面改性,考察了稀土改性玻璃纤维填充的PTFE复合材料在油润滑条件下的摩擦磨损性能,并用扫描电子显微镜(SEM)分析了磨损表面形貌.结果表明:与未经表面改性玻璃纤维填充的PTFE复合材料相比,经表面改性玻璃纤维填充的PTFE复合材料的减摩耐磨性能得到提高,以RES的作用最明显,SGS/RES次之,SGS第三;在油润滑条件下,稀土改性玻璃纤维填充的PTFE复合材料只出现了轻微磨损,这是由于玻璃纤维经稀土表面改性后极大地改善了玻璃纤维与PTFE基体之间的界面结合力,使稀土改性玻璃纤维填充的PTFE复合材料具有优异的摩擦磨损性能.     

Hot Deformation Behavior and Hardness of a CoCrFeMnNi High-Entropy Alloy with High Content of Carbon

A CoCrFeMnNi high-entropy alloy with a high content of carbon was synthesized, and its hot deformation behavior was studied at the temperatures 800–1000 ℃ at the strain rates ranging from 0.001 to 0.1 s~(-1).As-prepared alloy is a face-centered cubic-structured solid solution, with a large amount of carbides residing at grain boundaries.True stress–strain curves were employed to develop the constitutive equation of apparent activation energy.The apparent activation energy( Q) was found to be 423 kJ mol~(-1), indicating a dynamic flow softening behavior.The size of dynamic recrystallized(DRXed) grains increases with increasing the temperature or decreasing the strain rate.A processing map was sketched on the basis of the flow stress.The temperature range of 900–1000 ℃ and 10~(-3)–10~(-2.6) s~(-1) strain rate were found to be the optimum hot-forging parameter.With increasing temperature or decreasing strain rate, the volume fraction of fine carbides(≤ 1 μm) increases.A lot of coarse carbides can be found in the matrix after deformation at 800 ℃, which leads to a high hardness value of 345 HV.The carbides after deformation at 1000 ℃ are mainly nano-sized M_7C_3 and M_(23)C_6, which can promote the nucleation of DRX.