Influence of polymer modulus on the percolation threshold of latex-based composites

Monodispersed copolymer emulsions with different glass transition temperatures were synthesized to investigate the effect of room temperature polymer matrix modulus on the electrical properties of carbon black (CB) filled segregated network composites. The emulsion with the highest modulus at room temperature produced composites with the lowest percolation threshold. The threshold for a composite made from a copolymer latex containing an equal ratio of butyl acrylate and methyl methacrylate (BA5) is 1.5 vol%, while the percolation threshold for the much lower modulus BA7 (7:3 BA/MMA ratio) is 4.93 vol%. The microstructure of each composite shows significant differences in the level of CB dispersion within the polymer matrix. Higher modulus polymer particles push the CB more efficiently into the interstitial space between them, resulting in a lower percolation threshold. This modulus effect was confirmed by increasing the drying temperature, where the moduli of latexes (BA5, BA5.5, and BA6) were more similar and the percolation thresholds for three composites also become closer to one another.     

Morphological aspects of rubber fracture and wear

Morphology of carbon black (CB)‐filled rubber was studied with AFM and SEM and the classification of filler agglomerates, based on their internal structure and filler–matrix interactions, has been proposed. It varies according to the activity of CB and the kind of rubber. It has been shown that fracture of rubber starts either inside filler agglomerates (de‐cohesion) or in a filler–matrix interphase (de‐adhesion) initiating wear of the material. Microscopic observations correlate well with TGA and EPR data of wear debris collected during friction of rubber. The increase of thermal stability of CB and the appearance of additional spin signals, respectively, for elongated samples or debris, are proposed to be associated with de‐cohesion or de‐adhesion of the agglomerates. New approach to the fracture of rubber called “fatal agglomerate concept” is presented. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Memory of Distributed Computer Systems: Distinctive Features of Their Architectural-Structural Organization and Use

Distinctive features of architectural-structural organization and use of memory networks are considered with the aim of choosing an optimal configuration in designing distributed computer systems.     

永州电力通信交换网集中操作和维护的实现

分析实现永州电力通信交换网集中操作和维护的必要性，介绍了实现程控交换机远程操作和维护的两种方式，总结在实践过程中所得到的经验和教训。     

Bruchanalyse an Hohlgläsern

Failure analysis of hollow glasses The failure analysis is very important to clarify damages of hollow glasses. Damages of glass bottle through over pressure are very often linked with damages to persons. This is the reason why the causal research is from particular importance. Different surface characteristics of glass fragments as well as the fracture pattern give hints to the direction of the crack, the stress just before breakage and the reason of stress. A reconstruction of the bottle is a further helpful instrument for cause studies. The difference of the various characteristics of the surface will be explained. Further on there will be discussed different reasons and mechanism of fracture.     

广播电视发射台技术指标集中自动测试系统

本文介绍了利用计算机技术、网络技术、三遥技术对广播电视发射技术指标进行实时自动测试的系统，以便进一步为安全优质播出提供技术保证。     

Artificial Neural Network Modeling of Osmotic Dehydration Mass Transfer Kinetics of Fruits

Artificial neural network (ANN) models were developed for the prediction of transient moisture loss (ML) and solid gain (SG) in osmotic dehydration of fruits using process kinetics data from the literature. ANN models for ML and SG were developed based on data over a broad range of operating conditions and ten common processing variables: temperature and concentration of osmotic solution, immersion time, initial water and solid content of the fruit, porosity, surface area, characteristic length, solution-to-fruit mass ratio, and agitation level. The trained models were able to accurately predict the outputs with associated regression coefficients (r) of 0.96 and 0.93, respectively, for ML and SG. These ANN models performed much better than those obtained from linear multivariate regression analysis. The large number of process variables and their wide ranges considered along with their easy implementation in a spreadsheet make them very useful and practical for process design and control.     

Study on phase behavior–impact strength relationship of unsaturated polyester/polyurethane hybrid polymer network

The phase behavior of a hybrid polymer network (HPN) composed of poly[(propylene glycol maleate)-co-(propylene glycol phthalate)] crosslinked with styrene and polyester–urethane crosslinked with methylene-bis-ortho-chloroaniline was examined. The correlation between phase separation and impact strength of the HPNs is discussed. The composition of HPNs has an effect on their properties.     

人工神经网络A／D变换器

本文对［５］的４位人工神经网络Ａ／Ｄ变换器进行了研究．指出按其方法推广实现多位Ａ／Ｄ时存在突触电阻大小以至无法实现且抗干扰能力也不好的问题并给出了解决办法．同时对如何改善神经元转移特性的硬限幅曲线作了简单讨论．     

Prediction of fatigue behaviour in stress-concentrators of arbitrary geometry

A new method is outlined which aims to predict high-cycle fatigue behavior of components which fail from stress-concentrators. This involves examination of the stress field in the vicinity of the stress-concentrator, and comparison with stress fields for cracks at known stress intensities. Methods which are currently used for simple notch geometries can thus be generalised, making the approach applicable to stress concentrators of any geometry. The method of prediction is shown to be stable, providing a solution of good accuracy when compared to analytical methods for standard specimen geometries. Favourable comparisons with experimental data have been achieved both for standard notches and for a corner geometry which represents a typical component case.