Noncovalent Functionalized Graphene-Filled Polyimides with Improved Thermal,Mechanical, and Wear Resistance Properties

A facile method is proposed to prepare poly-o-phenylenediamine (PoPD) noncovalent functionalized graphene (G)-reinforced polyimide (PI) nanocomposites. PoPD-G exhibited excellent dispersibility in various organic solvents. The structures of PoPD-G were characterized by Raman and UV spectrum, which verified the π–π interactions between PoPD and G. The effective exfoliation of graphene nanosheets was investigated by observation of the morphology of PoPD-G with SEM, SPM, and TEM. Compared to PI/G composites, the interfacial adhesion between graphene nanosheets and PI matrices promoted efficient stress transfer from PI chains to PoPD-G nanofillers. Polyimide nanocomposites with different incorporations of PoPD-G exhibited outstanding thermal properties. It is interesting to note that only 0.5 wt% PoPD-G-reinforced PI composites increased by 20.8% in hardness, enhanced by 84.0% in storage modulus, and reduced by 72.8% in wear rate compared with neat PI. The eminent enhancement was attributed to the facile dispersion of graphene nanosheets and strong interface adhesion between PI and PoPD-G.     

基于约化乘法表的绝热量子整数分解算法

绝热量子计算模型是一种极具潜力的量子计算模型。报告一种基于约化乘法表的绝热量子整数分解方案及其在6量子~16量子比特内的数值仿真实验结果。这种方案采用约化的乘法表将整数分解问题转化为优化问题,从而将分解问题所需要的量子比特降低到n(n为待分解整数的二进制位宽)。实验结果表明新的绝热量子整数分解算法只需要多项式时间来求解此优化问题。     

Kinetic theory for aquatic animal distribution simulation

Identifying the underlying mechanisms that influence the spatial patterns in populations improves the forecasts of the alternative management strategies on the spatial dynamics of the populations, which are critical for assessing and managing the fisheries and improving the water resource management. This paper described a new approach of the numerical model for the prediction of the aquatic animal distribution in the flows. The model was developed based on the kinetic theory of gases, the mechanism of the aquatic animal movement and the flow hydrodynamic patterns. The model was validated using the available experimental data and an acceptable agreement was obtained. A comprehensive parameter study was then conducted to help understand the impact and the sensitivity of each parameter to the aquatic animal distribution. The promising results of the model reveal the prospect of applying this model to the reliable prediction of the aquatic animal distribution within a relatively large water area.     

An efficient equivariant adaptive separation via independence algorithm for acoustical source separation and identification

To balance the convergence rate and steady-state error of blind source separation (BSS) algorithms, an efficient equivariant adaptive separation via independence (Efficient EASI) algorithm is proposed based on separating indicator, which was derived from the convergence condition of EASI, and can be used to evaluate the separation degree of separated signals. Furthermore, a nonlinear monotone increasing function between suitable step sizes and separating indicator is constructed to adaptively adjust step sizes, and forgetting factor is employed to weaken effects of data at the initial stage. Numerical case studies and experimental studies on a test bed with shell structures are provided to validate the efficiency improvement of the proposed method. This study can benefit for vibration & acoustic monitoring and control, and machinery condition monitoring and fault diagnosis.     

微小催化燃烧器中催化剂的研究进展

在简述催化剂构成的基础上,结合微小燃烧器催化燃烧的发展,综述了近年来国内外微小燃烧器中催化燃烧催化剂的研究进展,主要介绍了以多孔氧化铝、碳化硅陶瓷和泡沫金属为结构基体的Pt、Pd等贵金属整体催化剂在碳氢燃料催化燃烧反应中的应用.讨论了这些催化剂对CH4、H2、C3H6等碳氢燃料燃烧的活性、起燃温度、燃烧温度和反应稳定性的影响,展望了研发新型低温、高性能微小尺度催化燃烧催化剂的研究重点和未来发展方向.     

Dynamic observation of bainite transformation in a Fe-C-Mn-Si superbainite steel

The dynamic observations of bainitic transformation in a Fe-C-Mn-Si superbainite steel were conducted on a high temperature laser scanning confocal microscope. It is indicated that the mutual intersection of bainite sheaves often occurs during growth of bainite ferrite, resulting in an interlocked bainite microstructure. Moreover, bainite transformation is promoted by higher austenization temperature and the longer and finer bainite platelets are obtained. Further, The average growth rate of bainite after austenization at 1 100 ° is calculated as 5.8 µm·s^?1. In situ observation investigation makes it possible to identify bainite transformation in real time during isothermal holding.     

Improved visible transparency of SIO<Subscript>2</Subscript>/ZNO:AL /CEO<Subscript>2</Subscript>-TIO<Subscript>2</Subscript>/SIO<Subscript>2</Subscript> multilayer films with high UV absorption and infrared reflection rate

New visible transparent, UV absorption, and high infrared reflection properties have been realized by depositing multilayer SiO₂/ZnO: Al/CeO₂-TiO₂/SiO₂ films onto glass substrates at low temperature by radio frequency magnetron sputtering. Optimum thickness of SiO₂, ZnO: Al (ZAO) and CeO₂-TiO₂ (CTO) films were designed with the aid of thin film design software. The degree of antireflection can be controlled by adjusting the thickness and refractive index. The outer SiO₂ film can diminish the interference coloring and increase the transparency; the inner SiO₂ film improves the adhesion of the coating on the glass substrate and prevents Ca²⁺, Na⁺ in the glass substrate from entering the ZAO film. The average transmittance in the visible light range increases by nearly 18%-20%, as compared to double layer ZAO/CTO films. And the films display high infrared reflection rate of above 75% in the wavelength range of 10-25 μm and good UV absorption (> 98%) properties. These systems are easy to produce on a large scale at low cost and exhibit high mechanical and chemical durability. The triple functional films with high UV absorption, antireflective and high infrared reflection rate will adapt to application in flat panel display and architectural coating glass, automotive glass, with diminishing light pollution as well as decreasing eye fatigue and increasing comfort.     

Microstructure and properties of cement foams prepared by magnesium oxychloride cement

Microstructural features including pore size distribution, cell walls and phase compositions of magnesium oxychloride cement foams (MOCF) with various MgO powders and water mixture ratios were studied. Their influences on compressive strength, water absorption and resistance of MOCF were also discussed in detail. The experimental results indicated that moderate and slight excess MgO powders (MgO/MgCl₂ molar ratios from 5.1 to 7) were beneficial to the formation of excellent microstructure of MOCF, but increasing water contents (H₂O/MgO mass ratios from 0.9 to 1.29) might result in opposite conclusions. The microstructure of MOCF produced with moderate and slight excess MgO powders could enhance the compressive strength, while serious excess MgO powders addition (MgO/MgCl₂ molar ratios = 9) would destroy the cell wall structures, and therefore decrease the strength of the system. Although MOCF produced with excess MgO powders could decrease the water absorption, its softening coefficient was lower than that of the material produced with moderate MgO powders. This might be due to the instability of phase 5, the volume expansion and cracking of cell walls as immersed the sample into water.     

Interactive Evolutionary Multi-Objective Optimization Algorithm Using Cone Dominance

As the number of objectives increases, the performance of the Pareto dominance-based Evolutionary Multi-objective Optimization (EMO) algorithms such as NSGA-II, SPEA2 severely deteriorates due to the drastic increase in the Pareto-incomparable solutions. We propose a sorting method which classifies these incomparable solutions into several ordered classes by using the decision maker's (DM) preference information. This is accomplished by designing an interactive evolutionary algorithm and constructing convex cones. This method allows the DMs to drive the search process toward a preferred region of the Pareto optimal front. The performance of the proposed algorithm is assessed for two, three, and four-objective knapsack problems. The results demonstrate the algorithm's ability to converge to the most preferred point. The evaluation and comparison of the results indicate that the proposed approach gives better solutions than that of NSGA-II. In addition, the approach is more efficient compared to NSGA-II in terms of the number of generations required to reach the preferred point.     

A Semi-Supervised WLAN Indoor Localization Method Based on 1-Graph Algorithm

For indoor location estimation based on received signal strength (RSS) in wireless local area networks (WLAN), in order to reduce the influence of noise on the positioning accuracy, a large number of RSS should be collected in offline phase. Therefore, collecting training data with positioning information is time consuming which becomes the bottleneck of WLAN indoor localization. In this paper, the traditional semi-supervised learning method based on k-NN and ε-NN graph for reducing collection workload of offline phase are analyzed, and the result shows that the k-NN or ε-NN graph are sensitive to data noise, which limit the performance of semi-supervised learning WLAN indoor localization system. Aiming at the above problem, it proposes a 1-graph-algorithm-based semi-supervised learning (LG-SSL) indoor localization method in which the graph is built by 1-norm algorithm. In our system, it firstly labels the unlabeled data using LG-SSL and labeled data to build the Radio Map in offline training phase, and then uses LG-SSL to estimate user’s location in online phase. Extensive experimental results show that, benefit from the robustness to noise and sparsity of 1-graph, LG-SSL exhibits superior performance by effectively reducing the collection workload in offline phase and improving localization accuracy in online phase.