Synthesis and characterization of soluble aromatic azopolyamides containing sulfone and ether units

A series of new polyamides 3a–d containing aryl-azo, ether and sulfone groups in the main chain were synthesized from bis[4-(4-aminophenoxy)phenyl sulfone] 1 and several azo aromatic diacyl chlorides 2a–d by the low temperature solution polycondensation technique. FTIR spectroscopy, nuclear magnetic resonance (NMR) and elemental analyses confirmed the structure of these polymers. Owing to the aryl and amide groups in the main chain, these polymers exhibit photochromic properties as well as excellent thermal stabilities. The transition temperatures (T _g) are between 242 and 265 °C, and the char yields at 800 °C in nitrogen atmosphere were above 39%. Based on incorporation of flexible ether linkages and polar sulfone groups, the polyamides show desirable solubility in organic solvents such as DMAc, N,N-dimethylformamide (DMF), N-methyl-2-pyrroidinone (NMP) and dimethylsulfoxide (DMSO). And it is exemplified that polyamide containing 2 and 2′ substitutes performed better solubility. Funded by the National Natural Science Foundation of China (No. 50572081)     

Antibacterial and corrosive properties of copper implanted austenitic stainless steel

Copper ions were implanted into austenitic stainless steel (SS) by metal vapor vacuum arc with a energy of 100 keV and an ions dose range of (0.5-8.0)×1017 cm-2. The Cu-implanted SS was annealed in an Ar atmosphere furnace. Glancing X-ray diffrac-tion (GXRD), transmission electron microscopy (TEM) and Auger electron spectroscopy (AES) were used to reveal the phase compositions, microstructures, and concentration profiles of copper ions in the implanted layer. The results show that the antibacterial property...     

Microstructural characterization of as-cast and homogenized 2D70 aluminum alloy

The microstructure of the as-cast 2D70 aluminum alloy and its evolution during homogenization were investigated by means of optical microscopy (OM), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), and differential scanning calorimetry (DSC) analysis. The results indicate that the microstructure of the as-cast 2D70 aluminum alloy mainly consists of the dendritic network of aluminum solid solution and intermetallic compounds (Al2CuMg, Al2Cu, Al9FeNi, Cu2FeAl7...     

混合溶剂法脱除软沥青的喹啉不溶物

煤沥青中含有较多的喹啉不溶物会影响炭材料的性能。以软沥青为原料,采用混合溶剂离心法对其进行脱除喹啉不溶物试验研究。考察了芳烷比、溶剂比、离心时间、离心温度对精制沥青的喹啉不溶物含量和收率的影响。结果表明：当芳烷比一定时,精制沥青喹啉不溶物含量和收率随溶剂比的增大而减小;当溶剂比一定时,精制沥青喹啉不溶物含量和收率均随芳烷比的增大而增加;离心时间越长,所得精制沥青喹啉不溶物含量越低,收率也越低;离心温度升高,有利于喹啉不溶物脱除,离心温度的较优选择为80℃。通过调整混合溶剂的比例,可以方便地控制净化过程的收率和喹啉不溶物含量。     

热定型工艺对斜纹涤纶机织滤布透气性能的影响

通过改变热定型温度、时间等工艺条件测试了织物热定型前后的透气性的变化,探讨了热定型工艺参数对涤纶机织滤布透气性的影响规律;采用二次回归正交设计得出斜纹涤纶机织滤布透气性与定型工艺的非线性关系,建立了热定型工艺与织物透气性影响规律的二次回归非线性经验方程.在定型温度为212℃、定型时间为143 s时涤纶机织滤布的透气量达...     

单周控制光伏并网系统的最大功率控制研究

单周控制的单级全桥光伏并网系统具有容量大、效率高、成本低等优点.但现有基于单周控制的光伏电池最大功率跟踪存在着难以搜索最大功率点、难以稳定工作在最大功率点以及搜索精度差等缺点.针对以上不足,提出了基于增量电导的光伏电池最大功率跟踪算法,该算法将光伏电池输出功率引入到单周控制的输入量中,同时优化了光伏电池输出电压的给定量.该算法在硬件上实现简单,仿真和实验结果表明该算法能够准确跟踪光伏电池最大功率点,并具有较高的精度和稳定性.     

Optimization of material structure of ploy-Si thin film based on Al induced crystallization

Based on Al induced crystallization (AIC) method, influences of different material structures on formation and characteristics of ploy-silicon thin films were studied and optimized. Al-Si films on glass with different structures (Si/Al/Glass, Al/Si/Glass, Si/Al/…/Si/Al/Glass) were deposited on glass substrates by sputtering method. All samples were annealed for MIC with varied time processes under 500℃ N2 environment. X-ray diffraction test and scanning electron microscope were adopted to characterize cryst...     

涵洞工程软弱地基处理中松木桩的应用

介绍赤天化纸业公司涵洞工程软弱地基的处理,针对软弱地基的不同构成需采取不同的处理方法,结合工程实践,对特殊环境下采用松木桩处理软弱地基的问题作了一些探讨。     

图像压缩编码在陶瓷中的应用

随着多媒体和网络技术的发展,图像压缩编码技术显得越来越重要。本文着重介绍了哈夫曼编码、预测编码、小波分析、分形压缩四种图像压缩编码在陶瓷中的应用。     

Correlations between characteristics of maximum influence and degree distributions in software networks

Software systems can be represented as complex networks and their artificial nature can be investigated with approaches developed in network analysis.Influence maximization has been successfully applied on software networks to identify the important nodes that have the maximum influence on the other parts.However,research is open to study the effects of network fabric on the influence behavior of the highly influential nodes.In this paper,we construct class dependence graph(CDG)networks based on eight practical Java software systems,and apply the procedure of influence maximization to study empirically the correlations between the characteristics of maximum influence and the degree distributions in the software networks.We demonstrate that the artificial nature of CDG networks is reflected partly from the scale free behavior:the in-degree distribution follows power law,and the out-degree distribution is lognormal.For the influence behavior,the expected influence spread of the maximum influence set identified by the greedy method correlates significantly with the degree distributions.In addition,the identified influence set contains influential classes that are complex in both the number of methods and the lines of code(LOC).For the applications in software engineering,the results provide possibilities of new approaches in designing optimization procedures of software systems.