Magnetic properties and magnetoresistance effect of SnFe2O4 spinel nanoparticles: Experimental,ab initio and Monte Carlo simulation

In this contribution, SnFe₂O₄ nanoparticles were prepared by the solvothermal method, the structural properties were performed using X-Ray Diffraction (DRX) to prove the success of tin ferrite formation and to determine de crystals parameters. The size and morphological study were build using Scanning Electron Microscopy (SEM) and Transmission Electron microscopy (TEM), the results showed that the size of particles is uniform with a range of particles (5–7 nm). The magnetic properties were carried out using the SQUID device, the SnFe2O4 nanoparticles have a magnetic transition at 750 K. In addition, the hysteresis loops at low temperature displayed Ms and Mr equals to 23 emu/g and 6 emu/g, respectively. The magnetoresistance properties were investigated, the SnFe₂O₄ nanoparticles present a large magnetoresistance effect (80%). The experimental results are supplemented by model calculations utilizing density functional theory and Monte-Carlo simulations.     

Influence of Al3+ doping for V5+ on the structural,optical, thermal and electrical properties of V2-xAlxO5-δ (x=0–0.20) ceramics

This paper reports an investigation on the structure-properties correlation of trivalent metal oxide (Al₂O₃)-doped V₂O₅ ceramics synthesized by the melt-quench technique. XRD patterns confirmed a single orthorhombic V₂O₅ phase formation with increasing strain on the doping of Al₂O₃ in place of V₂O₅ in the samples estimated by Williamson-Hall analysis. FTIR and Raman investigations revealed a structural change as [VO₅] polyhedra converts into [VO₄] polyhedra on the doping of Al₂O₃ into V₂O₅. The optical band gap was found in a wide semiconductor range as confirmed by UV–visible spectroscopy analysis. The thermal and conductivity behavior of the prepared samples were studied using thermal gravimetric analysis (TGA) and impedance analyzer, respectively. All the prepared ceramics exhibit good DC conductivity (0.22–0.36 Sm^-1) at 400 ?C. These materials can be considered for intermediate temperature solid oxide fuel cell (IT-SOFC)/battery applications due to their good conductivity and good thermal stability.     

无线传感器网络中移动sink节点的路径规划

在无线传感器网络中,大量感知数据汇集到sink节点的采集方法会导致sink节点附近的节点能量耗尽,造成能量空洞。针对该问题,利用移动的sink节点进行数据收集是一种解决方法,其中移动sink的路径规划成为一个重要的问题。提出了一个移动sink路径规划算法,将无线传感器中随机分布的节点划分为不同的子区域,寻找sink节点移动的最佳转向点,最终得到最优的移动路径,以实现无线传感器网络生命周期最大化。仿真实验表明,与现有方案相比,该算法能显著延长网络的生命周期。     

Investigations on grinding process of woven ceramic matrix composite based on reinforced fiber orientations

Fiber orientations play the decisive role in grinding process of woven ceramic matrix composites, but the influence of woven fibers in grinding process is not clear. This paper studies the surface quality and grinding force by comparing different woven surfaces. Through a series of experiments in optimized sampling conditions, we analyze characteristics of the material surface topography height, wave distribution and surface support properties in details. And we find some outstanding characteristics of the surface microstructure. We also study the influence of grinding processing parameters on surface microstructure. The results show that machining surface which contains more parallel fibers is rougher and more keenness than gauss surface. Grinding wheel speed and depth of cut have great influence on surface topography and surface support properties. And it is discovered that grinding forces are also highly dependent on fiber orientations. The mechanism of the grinding phenomena is also analyzed in this paper according to knowledge of fracture mechanics and mechanical damage phenomenology. The research obtained will be an important technical support on improving the processing quality of woven ceramic matrix composites.     

Classification and regression models of audio and vibration signals for machine state monitoring in precision machining systems

We present a data-driven method for monitoring machine status in manufacturing processes. Audio and vibration data from precision machining are used for inference in two operating scenarios: (a) variable machine health states (anomaly detection); and (b) settings of machine operation (state estimation). Audio and vibration signals are first processed through Fast Fourier Transform and Principal Component Analysis to extract transformed and informative features. These features are then used in the training of classification and regression models for machine state monitoring. Specifically, three classifiers (K-nearest neighbors, convolutional neural networks and support vector machines) and two regressors (support vector regression and neural network regression) were explored, in terms of their accuracy in machine state prediction. It is shown that the audio and vibration signals are sufficiently rich in information about the machine that 100% state classification accuracy could be accomplished. Data fusion was also explored, showing overall superior accuracy of data-driven regression models.     

The influence of plastic properties on chip formation

A two-dimensional finite-element model of the chip formation process is used to study the influence of the material law determining plastic flow on chip formation of titanium alloys at high cutting speeds. For simplicity, friction and thermo-mechanical properties of the tool are neglected in the simulations. Titanium chips are strongly segmented and therefore especially suitable to study the role of segmentation for the cutting force and other cutting parameters. Of special interest is the influence of the thermal softening parameter in the material law. Increasing thermal softening leads to a drastic decrease in the cutting force and a corresponding increase in chip segmentation. A variation of the hardening exponent is also performed. It is shown that the simulation results can be understood by using adiabatic flow stress curves. The variation of the hardening exponent leads to strongly differing chip shapes, although the cutting force stays nearly constant. This shows that mean cutting forces should not be used as simulation verification parameters.     

Investigation into polishing process of CVD diamond films

A new technique used for polishing chemical vapor deposition (CVD) diamond films has been investigated, by which rough polishing of the CVD diamond films can be achieved efficiently. A CVD diamond film is coated with a thin layer of electrically conductive material in advance, and then electro-discharge machining (EDM) is used to machine the coated surface. As a result, peaks on the surface of the diamond film are removed rapidly. During machining, graphitization of diamond enables the EDM process to continue. The single pulse discharge shows that the material of the coated layer evidently affects removal behavior of the CVD diamond films. Compared with the machining of ordinary metal materials, the process of EDM CVD diamond films possesses a quite different characteristic. The removal mechanism of the CVD diamond films is discussed.     

β21s高强度钛合金的铣削试验研究

针对一种新型的难加工钛合金材料β21s,进行了刀具磨损试验和铣削力的测量试验,对材料的切削加工性进行评价,并且给出优选结果,为实际生产提供参考。