聚N-乙烯基甲酰胺碱性水解反应的XPS研究

用X-射线光电子能谱仪(XPS)和胶体滴定法研究了聚N-乙烯基甲酰胺(PNVF)的碱性水解反应.结果表明PNVF水解产物的胺化度随着体系中碱浓度的增大而增大.在PNVF中含有约10%的非甲酰胺基团,由XPS谱图推论这些基团存在C O C结构.PNVF水解产物的高解像度C 1s XPS谱图中,存在5种不同结合能的碳,各峰的变化与PNVF水解过程中的官能团变化规律一致.在285.5 eV处的峰为-CHNH2结构中的碳,归因于PNVF的-NHCHO水解为-NH2;胶体滴定和XPS谱图分析结果的比较表明:采用胶体滴定法测定氨基含量时,如果不考虑PNVF的纯度,将存在较大的误差.     

新型聚酰胺复合膜的制备及性能研究--Ⅰ.界面聚合工艺条件的影响

以改性后的聚丙烯腈(PAN)超滤膜为基膜、p,p′-二氨基二苯甲烷(DDM)和均苯三甲酰氯(TMC)为单体,采用界面聚合法制备一种新型聚丙烯腈/聚p,p′-二氨基二苯甲烷酰胺复合膜.探索了单体浓度、界面聚合时间以及后处理时间、温度等工艺条件对膜分离性能的影响.采用环境扫描电镜(ESEM)观察复合膜的表面形态及断面结构.     

*EI 拓扑分子格在聚类分析中的应用

本文在引入AFS代数和AFS结构的基础上,通过对AFS代数上拓扑分子格结构的讨论,给出了EM中,由一些模糊概念生成的拓扑分子格所诱导出的X上拓扑的几点性质,并利用这些性质,对一个实际例子构造了隶属函数进行聚类分析,说明了这些性质在聚类分析中的应用。     

高频超声空化场喷射枪

根据高频超声及其空化场的力、热效应,以及空化场聚束管和液-固界面的增强作用原理,提出、设计和制作了一种小型的高频超声空化场喷射枪.试验表明,它用于水下破解冰冻物品、高分子板材焊接和瓶装液体除气方面是可行的.     

聚(N-异丙基丙烯酰胺)水凝胶微控阀的制备与性能

以毛细管(0.5 mm内径)为反应器,通过自由基聚合的方法合成了聚(N-异丙基丙烯酰胺)(PNIPAAm)水凝胶.在自制的毛细管系统中分别测定了盐浓度、pH值、有机溶剂体积分数以及压力对PNIPAAm水凝胶的响应时间和相转变温度值的影响.结果表明:乙酸铵溶液浓度在0.05 mol/L以下、磷酸二氢钠溶液的pH值在3~11范围内、乙醇溶液的体积分数在5%以下和流体静压力低于1.96 kPa时,PNIPAAm水凝胶的响应时间及相转变温度值变化不大,该水凝胶可作为微流控系统中的微阀直接使用.     

北京工商大学科研成果“多硫代聚芳基乙炔的合成及电化学性能研究”荣获解放军科技进步三等奖

日前，2005年度解放军科技进步奖颁发，北京工商大学（下称我校）孙家跃教授、杜海燕副教授与军事医学研究所联合研究成果“多硫代聚芳基乙炔的合成及电化学性能研究”荣获解放军科技进步三等奖．近年来，我校科研团队勇攀高峰、不断创新，科研成果屡获解放军科技进步奖，本次是继2001年获得一等奖，2003年获得二等奖后第3次荣获该奖项．     

Effects of Some Additives on the Adhesion of Polyacrylamide Sizes to Fibers

IntroductionPolyacrylamide ( PAM) size is one of the sizeingredients that are commonly used in conventionalfor mulations for warp sizing and paper making .It has theproperties of adhering to fibers and can be capable ofholding fiber together by surface attachment . Comparedwith starches and polyvinyl alcohols , PAM possesses suchcapability as excellent adhesion to cellulose fibers . Thiscapability ,however ,is not due to chemical valence ;but isdeveloped only through hydrogen bonds and Van …     

Research on Flax Fiber Reinforced Polylactide Environmental Friendly Composite

Biodegradable polylactide acid （PLA） resin can be combined with flax fibers to produce biodegradable composite materials. In our study, commercial PLA fibers were mixed with flax fibers by a non-woven method so as to make non- woven pre-forms, which can be generated into flax fiber reinforced PLA environmental friendly composites by heat pressing technology. The tensile, flexural and impact properties are tested in order to evaluate the basic physical properties of the composites, and the influenced factors listed as making technology of the pre-forms, weight ratio of flax fibers and heat pressing technology are discussed and optimized, which can be described as weight ratio of flax fibers and PLA fibers is 50/50, heating temperature, time and pressure are respectively 195℃, 20 rain and 12.5 Mpa. Preliminary results show that mechanical properties of the flax/PLA composites are quite promising compared with flax/PP composites in coclrnon commercial automotive use. Scanning electron microscope （SEM） is used to analyze the tensile specimen fracture surfaces, which shows voids and gaps occurring between flax fibers and PLA matrix and sign of fiber pull.out, the strength of flax/PLA interface can be further improved.     

Combined Density-based and Constraint-based Algorithm for Clustering

We propose a new clustering algorithm that assists the researchers to quickly and accurately analyze data. We call this algorithm Combined Density-based and Constraint-based Algorithm （CDC）. CDC consists of two phases. In the first phase, CDC employs the idea of density-based clustering algorithm to split the original data into a number of fragmented clusters. At the same time, CDC cuts off the noises and outliers. In the second phase, CDC employs the concept of K-means clustering algorithm to select a greater cluster to be the center. Then, the greater cluster merges some smaller clusters which satisfy some constraint rules.Due to the merged clusters around the center cluster, the clustering results show high accu racy. Moreover, CDC reduces the calculations and speeds up the clustering process. In this paper, the accuracy of CDC is evaluated and compared with those of K-means, hierarchical clustering, and the genetic clustering algorithm （GCA）proposed in 2004. Experimental results show that CDC has better performance.     

一种基于改进径向基神经网络的人脸图像识别方法

常用于径向基神经网络中心参数学习的K-均值聚类算法,易受初始参数选取的影响而收敛于局部极小值.将自动终止聚类判据的减聚类算法用于径向基网络的学习,可根据样本集确定径向基函数数目,且其计算量与数据点的数目与考虑问题的维数无关,很适合于人脸这种维数较高的模式.实验证明,应用这种算法训练径向基神经网络识别人脸,从识别精度到识别速度上都优于传统算法.