All-printed and highly stable organic resistive switching device based on graphene quantum dots and polyvinylpyrrolidone composite

We propose all printed and highly stable organic resistive switching device (ORSD) based on graphene quantum dots (G-QDs) and polyvinylpyrrolidone (PVP) composite for non-volatile memory applications. It is fabricated by sandwiching G-QDs/PVP composite between top and bottom silver (Ag) electrodes on a flexible substrate polyethylene terephthalate (PET) at ambient conditions through a cost effective and eco-friendly electro-hydrodynamic (EHD) technique. Thickness of the active layer is measured around 97 nm. The proposed ORSD is fabricated in a 3 × 3 crossbar array. It operates switching between high resistance state (HRS) and low resistance state (LRS) with OFF/ON ratio ∼14 for more than 500 endurance cycles, and retention time for more than 30 days. The switching voltage for set/reset of the devices is ±1.8 V and the bendability down to 8 mm diameter for 1000 cycles are tested. The elemental composition and surface morphology are characterized by XPS, FE-SEM, and microscope.     

Weak Delocalization in Graphene on a Ferromagnetic Insulating Film

Graphene has been predicted to develop a magnetic moment by proximity effect when placed on a ferromagnetic film, a promise that could open exciting possibilities in the fields of spintronics and magnetic data recording. In this work, the interplay between the magnetoresistance of graphene and the magnetization of an underlying ferromagnetic insulating film is studied in detail. A clear correlation between both magnitudes is observed but through a careful modeling of the magnetization and the weak localization measurements, that such correspondence can be explained by the effects of the magnetic stray fields arising from the ferromagnetic insulator is found. The results emphasize the complexity arising at the interface between magnetic and 2D materials.     

复合绝缘子老化评估方法浅析

复合绝缘子老化是用户十分关心的问题。笔者介绍了两种判别复合绝缘子老化程度的方法,并通过实例,分析了这两种方法的优点以及存在的问题。     

Flashover voltage characteristics of contaminated station insulators under temporary ac overvoltages in the ac system connected with a frequency converter station

According to the recent analysis results of temporary ac overvoltage in the ac system connected with a frequency converter station, large-magnitude over-voltages were confirmed to occur under some special system conditions. Most of the station insulators currently used cannot withstand such overvoltages according to an evaluation based on the data obtained earlier. The necessity of tests to be done to evaluate such performance more accurately was recognized. Both power frequency and switching impulse overvoltage flashover tests were made on contaminated insulators by the method well simulating the natural wetting condition. Switching impulse flashover voltage with the waveshape having a long wavefront time of 2 ms can be well correlated with the flashover voltage characteristics of temporary ac overvoltage. Higher flashover voltage characteristics were obtained by a clean fog test method compared with those obtained by equivalent fog test method.     

复合绝缘子耐电腐蚀特点及其电蚀老化区域性的差异

为了了解复合绝缘子外绝缘材质电蚀老化状态和区域性的差异,对Al(OH)3耐电腐蚀机理、外绝缘材质中Al(OH)3颗粒分布状态和环境污湿因素的实际情况进行了研究。Al(OH)3颗粒分解成水蒸气、析出白色粉末状氧化铝,并催化生成二氧化碳,将使外绝缘材质逐渐微观减薄和加大表面的粗糙度,而引起电蚀老化的污湿环境因素,近期不可能得到改善,因此必然引起其电蚀老化出现区域性差异。此外,外绝缘憎水表面污珠场强变化引起的电晕也是促使电蚀老化的重要因素。     

Plasma immersion ion implantation for SOI synthesis: SIMOX and ion-cut

We have demonstrated feasibility to form silicon-on-insulator (SOI) substrates using plasma immersion ion implantation (PIII) for both separation by implantation of oxygen and ion-cut. This high throughput technique can substantially lower the high cost of SOI substrates due to the simpler implanter design as well as ease of maintenance. For separation by plasma implantation of oxygen wafers, secondary ion mass spectrometry analysis and cross-sectional transmission electron micrographs show continuous buried oxide formation under a single-crystal silicon overlayer with sharp Si/SiO₂ interfaces after oxygen plasma implantation and high-temperature (1300°C) annealing. Ion-cut SOI wafer fabrication technique is implemented for the first time using PIII. The hydrogen plasma can be optimized so that only one ion species is dominant in concentration and there are minimal effects by other residual ions on the ion-cut process. The physical mechanism of hydrogen induced silicon surface layer cleavage has been investigated. An ideal gas law model of the microcavity internal pressure combined with a two-dimensional finite element fracture mechanics model is used to approximate the fracture driving force which is sufficient to overcome the silicon fracture resistance.     

钙铁硅铁磁体微晶玻璃热处理制度的研究

使用XRD、DTA、VSM等分析测试手段对在还原气氛下含少量B2O3、P2O5钙铁硅微晶玻璃的热处理制度进行了较深入的研究。研究发展，预核化处理对于钙铁硅微晶玻璃的晶化无明显作用。900℃作为钙铁硅微晶玻璃的晶化温度较适宜，晶化时间宜8h以上。     

MLS结构的电容-电压特性

本文报导在 Si 衬底上拉制聚酰胺 LB 膜的电容-电压特性,结果表明:它具有与其它绝缘膜相似的特性,为聚酰胺 LB 膜应用于场效应器件奠定了基础。     

一种基于相关函数法铁磁谐振波形研究

对铁磁谐振波形进行了系统的分类分级,提出了一种基于Matlab的相关函数方法,并且利用大量数据进行对比,已经得到了效果验证,经过桂林市电力电容器责任有限公司认证,具有良好的实际效果。     

Characterization of acoustic signals due to surface discharges on H.V. glass insulators using wavelet radial basis function neural networks

A hybrid model incorporating wavelet and radial basis function neural network is presented which is used to detect, identify and characterize the acoustic signals due to surface discharge activity and hence differentiate abnormal operating conditions from the normal ones. The tests were carried out on cleaned and polluted high voltage glass insulators by using surface tracking and erosion test procedure of international electrotechnical commission 60587. A laboratory experiment was conducted by preparing the prototypes of the discharges. This study suggests a feature extraction and classification algorithm for surface discharge classification, which when combined together reduced the dimensionality of the feature space to a manageable dimension, by “marrying” the wavelet to radial basis function neural network very high levels of classification are achieved. Wavelet signal treatment toolbox is used to recover the surface discharge acoustic signals by eliminating the noisy portion and to reduce the dimension of the feature input vector. A radial basis function neural network classifier was used to classify the surface discharge and assess the suitability of this feature vector in classification. This learning method is proved to be effective by applying the wavelet radial basis function neural network in the classification of surface discharge fault data set. The test results show that the proposed approach is efficient and reliable.