直流电压下绝缘油中杂质集聚特性及其影响因素

近年来特高压直流输电在我国迅速发展,换流变压器是特高压直流输电系统的核心设备之一,长期运行时其出线处电极表面易发生纤维固体杂质物的集聚沉积,影响绝缘油的耐受能力。改变电极间距以及杂质微粒的初始浓度和材料等参数进行仿真计算和实验,探究杂质的集聚特性及其机理。研究结果表明:改变电极间距会影响电场的分布和杂质的受力,长间隙下杂质会在电极表面进行聚集,短间隙时改变间距还会影响“纤维小桥”是否形成;杂质的浓度越高,其集聚程度越高;纤维杂质比金属杂质更易集聚。该研究有助于明确绝缘油中杂质在电极表面的集聚沉积机理,为合理设计换流变压器出线装置提供一定的理论基础,有利于防止电力设备出现绝缘事故、提高电力设备长期运行可靠性。

利用局部集聚特性的聚类算法的研究

基于SNN相似性和密度的聚类算法是当前主要的无监督聚类方法之一,该类算法在发现不同大小形状簇的聚类过程中都取得了较好的结果。但是该类算法也存在局限性,如Jarvis-Pat-rick算法通过单连结的方式发现簇,可能分割真正的簇或者合并应该保持分离的簇,而SNN密度类算法的Eps,MinPts参数的确定对用户来说是比较困难的。针对该类问题,本文对聚类过程中的局部集聚特征进行了分析和定义,提出了利用数据的局部集聚特征来控制聚类过程的的聚类算法。通过验证,该算法对发现不同密度以及任意形状的数据集合的聚类分析问题是有效的,突出了数据分析的局部集聚特征,改进了数据聚类的质量。

控温条件下甲醇分子集聚特性的研究

控温条件下采用分子动力学模拟研究甲醇水溶液中甲醇分子的集聚特性,研究发现,甲醇的集聚特性随温度增加而增强。

通风状态下综合管廊燃气管道小孔泄漏扩散模拟研究

为揭示多因素影响下的综合管廊复杂受限空间燃气随时间的扩散集聚特性,利用Fluent软件模拟常态机械通风下不同泄漏口朝向、泄漏口位置、管道压力、泄漏口孔径及形状的燃气浓度分布特性。结果表明:泄漏口朝向对泄漏甲烷初期分布具有重要影响,泄漏口竖直向上、泄漏口竖直向下朝向泄漏甲烷主要分布于管廊中上部区域;泄漏朝向壁面水平距离较远一侧、泄漏朝向壁面水平距离较近一侧泄漏甲烷主要分布于管廊中下部区域;泄漏报警触发时间随泄漏口朝向呈非对称分布,报警触发时间从短到长依次为泄漏口竖直向上、泄漏口竖直向下、泄漏朝向壁面水平距离较近一侧、泄漏朝向壁面水平距离较远一侧,泄漏朝向壁面水平距离较远一侧为廊内最不利泄漏口朝向。综合管廊顶部进风口存在通风滞速区,当泄漏口处于滞速区时泄漏甲烷聚积并达到爆炸极限;泄漏口坐标与廊内泄漏甲烷分布广度呈负相关,泄漏点在滞速区附近为最不利泄漏口位置。泄漏口孔径和管道压力与燃气泄漏量、扩散范围均呈正相关,与报警时间均呈负相关。条缝型泄漏口的泄漏甲烷扩散能力弱于圆形泄漏口,在泄漏口上风处甲烷质量分数高于圆形泄漏口。

现代商业展览凸显六大特性

进入新世纪，越来越多的企业把参与大型商业展览，作为商品促销或采购的重要手段。实践证明，组织良好的大型商业展会常给与会者带来意外惊喜。而随着科学技术的不断进步，大型商业展览的时代特征也日益明显。我们从对全球部分成功展会的综合分析和比较中可以发现，现代商业展览一般具有以下六大特性。

换流变压器液体绝缘中纤维杂质颗粒研究

纤维杂质颗粒在变压器绝缘油杂质颗粒中的占比超过90%,悬浮在绝缘油中的纤维杂质颗粒在高压直流电场的作用下易发生集聚,导致电场畸变,使绝缘油耐受能力劣化。随着我国高压直流输电工程的快速发展,关于换流变压器液体绝缘系统中纤维杂质颗粒的研究逐渐成为新的研究热点。为此,综合国内外研究现状论述了绝缘油中纤维杂质颗粒的研究进展,分别从纤维杂质颗粒的来源和受力情况、运动集聚规律、放电特性、杂质小桥阻断技术以及油流对纤维杂质颗粒集聚特性的影响这5个方面进行论述和探讨,并展望了未来换流变压器中纤维杂质颗粒研究的发展趋势。通过对现有研究成果的分析和总结,获得的结果可为换流变压器的安全运行以及结构改善提供参考。

Application of Light Reflectance-Transmittance Measurement Method to Reconstruct Geometrical Morphology of Particle Fractal Aggregates

Particles,including soot,aerosol and ash,usually exist as fractal aggregates.The radiative properties of the particle fractal aggregates have a great influence on studying the light or heat radiative transfer in the particle medium.In the present work,the performance of the single-layer inversion model and the double-layer inversion model in reconstructing the geometric structure of particle fractal aggregates is studied based on the light reflectancetransmittance measurement method.An improved artificial fish-swarm algorithm(IAFSA)is proposed to solve the inverse problem.The result reveals that the accuracy of double-layer inversion model is more satisfactory as it can provide more uncorrelated information than the single-layer inversion model.Moreover,the developed IAFSA show higher accuracy and better robustness than the original artificial fish swarm algorithm(AFSA)for avoiding local optimization problems effectively.As a whole,the present work supplies a useful kind of measurement technology for predicting geometrical morphology of particle fractal aggregates.

Optimal extent of fluorination enabling strong temperature-dependent aggregation, favorable blend morphology and high-efficiency polymer solar cells

Temperature-dependent aggregation is a key property for some donor polymers to realize favorable bulk-heterojunction(BHJ)morphologies and high-efficiency(>10%) polymer solar cells.Previous studies find that an important structural feature that enables such temperature-dependent aggregation property is the 2nd position branched alkyl chains sitting between two thiophene units.In this report,we demonstrate that an optimal extent of fluorination on the polymer backbone is a second essential structural feature that enables the strong temperature-dependent aggregation property.We compare the properties of three structurally similar polymers with 0,2 or 4 fluorine substitutions in each repeating unit through an in-depth morphological study.We show that the non-fluorinated polymer does not aggregate in solution(0.02 mg mL^(-1) in chlorobenzene) at room temperature,which results in poor polymer crystallinity and extremely large polymer domains.On the other hand,the polymer with four fluorine atoms in each repeating unit exhibits an excessively strong tendency to aggregate,which makes it difficult to process and causes a large domain.Only the polymer with two fluorine atoms in each repeating unit exhibits a suitable extent of temperature-dependent aggregation property.As a result,its blend film achieves a favorable morphology and high power conversion efficiency.This provides another key design rationale for developing donor polymers with suitable temperature-dependent aggregation properties and thus high performance.

Preparation and self-assembly of amphiphilic polymer with aggregation-induced emission characteristics

An amphiphilic polymer bearing tetraphenylethene (TPE) moiety was synthesized by convenient reactions. The polymer exhibits unique aggregation-induced emission (AIE) characteristics and can self-assemble to size-tunable particles in DMF/water mixtures. The polymer nanoparticles can be used for cell imaging, which provides a potential stable fluorescent tool to monitor the distribution of drugs and bioconjugates in living cells.

New tetraphenylpyridinium-based luminogens with aggregation-induced emission characteristics

The research on aggregation-induced emission (AIE) has drawn increasing interests in the past decade. With the efforts scientists paid, a variety of AIE systems have been developed, among which the tetraphenylethelene and silole derivatives are the most studied. Development of new AIE systems could further enrich the AIE molecules and promote the development of AIE area. In this communication, we prepared a new AIE system based on 1,2,4,6-tetraphenylpyridinium ions according to the restriction of intramolecular rotation mechanism. These molecules could be facilely synthesized via one-step and one-pot reaction. The ionic AIE-active molecules could find wide application in sensing and optoelectronic areas.

Kinetics of Specific and Non-Specific Copper Sorption on Aggregates of an Acidic Paddy Soil from the Taihu Lake Region in East China

The Taihu Lake region in East China has become prone to soil acidification, which changes heavy metals such as copper(Cu) in soil into water-soluble species and increases the mobility and contamination risks of heavy metals in the biological environment. In this study, the kinetics of Cu2+sorption by the bulk soil and the aggregate size fractions of an acidic paddy soil collected from the Taihu Lake region, the effects of temperature on Cu2+sorption, and the p H changes of the solution were investigated by static sorption and magnetic stirring. The aggregate size fractions were prepared by low-energy ultrasonic dispersing and freeze-drying. The total sorption amounts of the bulk soil and the aggregate size fractions for Cu2+followed a descending order of clay > coarse sand > bulk soil > silt> sand, corresponding to those of organic matter content, free iron oxide content, free aluminum oxide content, and cation exchange capacity. The kinetic sorption curves of Cu2+by the bulk soil and the aggregates, which were divided into two stages(rapid and slow sequentially), were well fitted by the first-order equation, the diffusion equation, and the Elovich equation, showing significant correlations(P < 0.05). Specific and non-specific sorption dominated in the fast and slow stages, respectively, and the former was predominant throughout the sorption process. The specific sorption accelerated and the non-specific sorption decelerated with rising temperature. The p H of the solution decreased significantly during the specific sorption and remained unchanged or increased slightly during the non-specific sorption. When the specific sorption terminated, the p H of the solution was minimized nearly simultaneously.The sorption progress of Cu2+by the bulk soil significantly preceded that by the aggregates. Therefore, heavy metal contamination may be another factor reducing soil p H and metal sorption forms should be taken into consideration in studies of mitigating soil heavy metal pollution or determining environmental capacity of heavy metal in soil.

Red fluorescent siloles with aggregation-enhanced emission characteristics

A series of new red fluorescent siloles consisting of a silole core and dimesitylboranyl substituent connected with a furan, thiophene, and selenophene bridges were synthesized and characterized. The optical properties, electronic structures, and electroluminescence （EL） performances were investigated. The emission wavelengths were red-shifted from the siloles with furan, to those with thiophene, and then selenophene. The thiophene, and selenophene-containing siloles, （MesB）2DTTPS, and （MesB）zDSTPS, showed the typical aggregation-enhanced emission （AEE） feature, while furan-containing one, （MesB）2DFTPS, showed slight emission decrease as the aggregate formation. Theoretical calculations were carried out to explain the difference in the optical properties. Undoped OLEDs using these red siloles as light-emitting layers were fabricated. The device of （MesB）2DTTPS exhibited the best performance. It radiated red EL emission at 589 nm, and afforded good maximum luminance, current, power, and external quantum efficiency of 13300 cd m^-2, 4.3 cd A^-1, 2.9 lm W^-1, and 1.8%, respectively.

Computational approaches to understanding protein aggregation in neurodegeneration

The generation of toxic non-native protein conformers has emerged as a unifying thread among disorders such as Alzheimer＇s disease, Parkinson＇s disease, and amyotrophic lateral sclerosis. Atomic-level detail regarding dynamical changes that facilitate protein aggre- gation, as well as the structural features of large-scale ordered aggregates and soluble non-native oligomers, would contribute signifi- cantly to current understanding of these complex phenomena and offer potential strategies for inhibiting formation of cytotoxic species. However, experimental limitations often preclude the acquisition of high-resolution structural and mechanistic information for aggregating systems. Computational methods, particularly those combine both aU-atom and coarse-grained simulations to cover a wide range of time and length scales, have thus emerged as crucial tools for investigating protein aggregation. Here we review the current state of computational methodology for the study of protein self-assembly, with a focus on the application of these methods toward understanding of protein aggregates in human neurodegenerative disorders.