纳米结构导电聚合物材料研究进展

具有纳米结构的导电聚合物因其诱人的应用前景越来越引起人们的重视。本文综述了聚苯胺、聚吡咯以及聚噻吩等导电聚合物的零维、一维、二维以及三维纳米结构的合成方法,并介绍了聚合物纳米结构的表征以及研究现状和应用前景。参考文献60篇。     

Cu离子A位掺杂对LaSrCoO4复合氧化物氧化性能的影响

采用聚丙烯酰胺法制备了La1-xCuxSrCoO4(x=0.2-0.8)复合氧化物,考察了Cu离子掺杂量(x)对CO及C3H8氧化反应活性的影响,并运用XRD、IR、TPR和TPD等多种手段对复合氧化物催化剂进行了表征。结果表明,催化剂活性随x的变化而变化,Cu部分取代A位La能提高LaSrCoO4催化剂的CO及C3H8氧化反应活性,当x=0.4时La1-xCuxSrCoO4催化剂的晶格氧和Co3 含量较多,晶格氧的活动性较高,催化活性最佳。     

低温水热法制备硅胶负载型二氧化钛催化剂

TiO2作为一种优良的光催化材料,能够降解有机物,起到抗菌防污的作用,其在工业上的潜在应用已吸引众多研究者的普遍关注和深入研究[1-3]。为了进一步提高它的光催化活性,研究者试图运用各种方法和技术对纯TiO2进行改进。负载[3]是其中常用方法之一。对于无负载的二氧化钛,由于本     

4,5-二苯基噁唑的荧光性能研究

荧光是物质从激发态失活到多重性相同的低能状态时所释放的辐射.自二十世纪初以来,有机荧光材料广泛用于纺织、塑料着色及印刷颜料,此外它在药物学、生物学、环境科学、信息科学方面都有广阔的应用前景.     

二维材料改性水性聚氨酯防腐涂料的研究进展

水性聚氨酯涂料作为一种新兴的环保涂料,在防腐领域得到了广泛应用。然而,水性聚氨酯涂料交联密度低,耐水性稍差,不利于其长效防腐性能。利用具有独特物理化学特性的二维材料作为水性聚氨酯的填料,可以有效改善其性能。本文主要介绍了三种二维材料(石墨烯、MXene和六方氮化硼)作为填料与水性聚氨酯进行复合,并重点介绍了石墨烯、MXene和六方氮化硼的改性方法,并对水性聚氨酯复合涂层的性能进行了阐述和比较,最后对未来二维材料/水性聚氨酯的复合材料的发展和应用进行了展望。     

螺旋线型脉冲形成线匝间击穿与输出波形的研究

 针对螺旋线型脉冲形成线放电过程的匝间击穿问题,采用数值模拟的方法研究了影响螺旋线上轴向电场的因素,模拟结果表明：螺旋线的螺旋角越大、开关的上升沿越小、负载的阻值越小则越容易造成匝间击穿;针对输出波形的前沿上冲和下凹问题,通过数值模拟和实验方法研究了加速器内阻抗不匹配段对输出波形的影响,结果表明: 改变螺旋线与开关之间连接段的阻抗以及开关和二极管之间过渡段的阻抗,使之接近于螺旋线阻抗,并使电长度减小,可以消除波形的前沿上冲和下凹,得到近似方波的高电压脉冲输出。     

1.2 MV大功率直流高压电源研制

 采用等边三角形结构的铁芯,次级线圈分成40级,分别进行三相全波整流,每级输出直流30 kV,串联后获得1.2 MV/A的直流高电压大功率输出。电源的能量转换效率大于95%,漏抗高达21.7%。采用无滤波电容结构,次级线圈星型/三角型接法交替使用,纹波系数小于±4%。整个电源密封在压力钢筒中,充0.8 MPa高纯度SF6气体作为绝缘介质,最大工作场强小于130 kV/cm。设计了专门的SF6气体冷却系统,气体温度控制在60 ℃以内,高电压由充气同轴传输线输出。在小负载条件下,电源各项指标满足技术要求,已经安装在1.2 MW,1.2 MeV大功率直流电子加速器上进行整机联调。     

Prisoner’s Dilemma Game with Cooperation-Defection Dominance Strategies on Correlational Multilayer Networks

As multilayer networks are widely applied in modern society, numerous studies have shown the impact of a multilayer network structure and the network nature on the proportion of cooperators in the network. In this paper, we use Barabási–Albert scale-free networks (BA) and Watts and Strogatz networks (WS) to build a multilayer network structure, and we propose a new strategy-updating rule called “cooperation-defection dominance”, which can be likened to dominant and recessive traits in biogenetics. With the newly constructed multilayer network structure and the strategy-updating rules, based on the simulation results, we find that in the BA-BA network, the cooperation dominance strategy can make the networks with different rs show a cooperative trend, while the defection dominance strategy only has an obvious effect on the network cooperation with a larger r. When the BA network is connected to the WS network, we find that the effect of strategy on the proportion of cooperators in the network decreases, and the main influencing factor is the structure of the network. In the three-layer network, the cooperation dominance strategy has a greater impact on the BA network, and the proportion of the cooperators is enhanced more than under the natural evolution strategy, but the promotion effect is still smaller than that of the two-layer BA network because of the WS network. Under the defection dominance strategy, the WS layer appears different from the first two strategies, and we conclude through simulation that when the payoff parameter is at the middle level, its cooperator proportion will be suppressed, and we deduce that the proportion of cooperators and defectors, as well as the payoff, play an important role.     

A List-Ranking Framework Based on Linear and Non-Linear Fusion for Recommendation from Implicit Feedback

Although most list-ranking frameworks are based on multilayer perceptrons (MLP), they still face limitations within the method itself in the field of recommender systems in two respects: (1) MLP suffer from overfitting when dealing with sparse vectors. At the same time, the model itself tends to learn in-depth features of user–item interaction behavior but ignores some low-rank and shallow information present in the matrix. (2) Existing ranking methods cannot effectively deal with the problem of ranking between items with the same rating value and the problem of inconsistent independence in reality. We propose a list ranking framework based on linear and non-linear fusion for recommendation from implicit feedback, named RBLF. First, the model uses dense vectors to represent users and items through one-hot encoding and embedding. Second, to jointly learn shallow and deep user–item interaction, we use the interaction grabbing layer to capture the user–item interaction behavior through dense vectors of users and items. Finally, RBLF uses the Bayesian collaborative ranking to better fit the characteristics of implicit feedback. Eventually, the experiments show that the performance of RBLF obtains a significant improvement.     

强流同步双阴极二极管电子束模拟与诊断

 高同步性的多电子束能够驱动产生有利于实现相位控制的多束微波,是高功率微波功率合成的关键技术。对单台加速器驱动强流同步双阴极二极管进行了模拟,在二极管阻抗约10 W,输入电压442.6 kV条件下,获得了总功率大于20 GW、总束流为47.6 kA、同步时间差小于6 ns的双电子束。开展了轰击不锈钢目击靶实验和同步双电子束诊断实验,双阴极材料为不锈钢,单个阴极长30 mm,两阴极中心间距为100 mm,阴极发射面采用天鹅绒,单阴极半径为20 mm,在阴阳极最大电压为442.8 kV时,束流峰值总和为48.78 kA,双束流同步时间差保持在4~6 ns范围内,实验结果与模拟符合较好。