中子单粒子效应研究现状及进展

回顾了中子单粒子研究的国内外发展情况,介绍了近几年西北核技术研究所在西安脉冲堆开展的低能中子单粒子效应研究进展。比较了稳态与脉冲工况下中子单粒子效应的异同性;分析了含有SRAM结构器件随着特征尺寸的减小,中子单粒子效应敏感性加剧的物理机制。分析认为目前中子单粒子效应已成为小尺寸大规模互补金属氧化物半导体器件的主要中子效应表现;中子辐射效应研究中,除了位移损伤效应以外还必需重视由中子电离造成的中子单粒子效应。     

混响室频率搅拌方式及其场环境特性分析

从本征模的角度阐明了频率搅拌技术的混响原理,并根据激励信号的频域特征,系统研究了频率搅拌方式下获取实时均匀场与统计均匀场的三种有效实现途径。选取线性扫频这一搅拌方式为主要研究对象,检验了混响室频率搅拌下的最低可用频率、场均匀性与统计特性三项主要技术指标。试验结果表明：线性扫频搅拌方式下,混响室的最低可用频域与机械搅拌方式基本一致;场均匀性满足IEC 61000-4-21标准规定的容差要求;场值波动规律符合理论分布模型。     

基于信号幅相特性的副瓣跟踪自动识别方法

传统雷达测角系统副瓣跟踪识别方法主要根据副瓣信号幅度较主瓣明显偏低这一特性提出,该文通过对副瓣跟踪原理的理论分析、仿真分析与实测验证,得出了关于副瓣跟踪特性的新结论：副瓣跟踪时和差相位正交、差和幅度比相对主瓣跟踪明显增大。在此基础上提出一种基于信号幅相特性的副瓣跟踪识别方法：构造以差和幅度比、和差相位差为描述子的幅相特征向量,采用支持向量机(SVM)对特征向量进行分类完成识别过程。实验结果表明,该文方法识别准确率高,鲁棒性、实时性、通用性强。     

基于样本紧密度的雷达高分辨距离像识别方法研究

模板库是基于高分辨距离像(HRRP)进行雷达自动目标识别的关键。由于真实目标复杂的电磁散射特性及背景杂波的存在,基于传统平均HRRP模板库的目标识别方法的实用性能有限。该文分析了雷达目标HRRP样本集在单位超球面上的空间分布特征,构建了类心+紧密度球特征模板库,定义了基于紧密度球的距离度量方法,最后提出基于样本紧密度的HRRP识别方法。基于公共MSTAR数据的实验结果表明该方法具有良好的工程实用性能。     

The Classification of Rice Blast Resistant Seed Based on Ranman Spectroscopy and SVM

Rice blast is a serious threat to rice yield. Breeding disease-resistant varieties is one of the most economical and effective ways to prevent damage from rice blast. The traditional identification of resistant rice seeds has some shortcoming, such as long possession time, high cost and complex operation. The purpose of this study was to develop an optimal prediction model for determining resistant rice seeds using Ranman spectroscopy. First, the support vector machine (SVM), BP neural network (BP) and probabilistic neural network (PNN) models were initially established on the original spectral data. Second, due to the recognition accuracy of the Raw-SVM model, the running time was fast. The support vector machine model was selected for optimization, and four improved support vector machine models (ABC-SVM (artificial bee colony algorithm, ABC), IABC-SVM (improving the artificial bee colony algorithm, IABC), GSA-SVM (gravity search algorithm, GSA) and GWO-SVM (gray wolf algorithm, GWO)) were used to identify resistant rice seeds. The difference in modeling accuracy and running time between the improved support vector machine model established in feature wavelengths and full wavelengths (200–3202 cm⁻¹) was compared. Finally, five spectral preproccessing algorithms, Savitzky–Golay 1-Der (SGD), Savitzky–Golay Smoothing (SGS), baseline (Base), multivariate scatter correction (MSC) and standard normal variable (SNV), were used to preprocess the original spectra. The random forest algorithm (RF) was used to extract the characteristic wavelengths. After different spectral preproccessing algorithms and the RF feature extraction, the improved support vector machine models were established. The results show that the recognition accuracy of the optimal IABC-SVM model based on the original data was 71%. Among the five spectral preproccessing algorithms, the SNV algorithm’s accuracy was the best. The accuracy of the test set in the IABC-SVM model was 100%, and the running time was 13 s. After SNV algorithms and the RF feature extraction, the classification accuracy of the IABC-SVM model did not decrease, and the running time was shortened to 9 s. This demonstrates the feasibility and effectiveness of IABC in SVM parameter optimization, with higher prediction accuracy and better stability. Therefore, the improved support vector machine model based on Ranman spectroscopy can be applied to the fast and non-destructive identification of resistant rice seeds.     

Ultra-thin Body Buried In0.35Ga0.65As Channel MOSFETs with Extremely Low Off-current on Si Substrates

In this paper, we investigated the electrical properties of the Metal-oxide-semiconductor gate stack of Ti/Al2O3/InP under different annealing conditions. A min...     

Recent Progress in Iron-Based Microwave Absorbing Composites: A Review and Prospective

With the rapid development of communication technology in civil and military fields, the problem of electromagnetic radiation pollution caused by the electromagnetic wave becomes particularly prominent and brings great harm. It is urgent to explore efficient electromagnetic wave absorption materials to solve the problem of electromagnetic radiation pollution. Therefore, various absorbing materials have developed rapidly. Among them, iron (Fe) magnetic absorbent particle material with superior magnetic properties, high Snoek’s cut-off frequency, saturation magnetization and Curie temperature, which shows excellent electromagnetic wave loss ability, are kinds of promising absorbing material. However, ferromagnetic particles have the disadvantages of poor impedance matching, easy oxidation, high density, and strong skin effect. In general, the two strategies of morphological structure design and multi-component material composite are utilized to improve the microwave absorption performance of Fe-based magnetic absorbent. Therefore, Fe-based microwave absorbing materials have been widely studied in microwave absorption. In this review, through the summary of the reports on Fe-based electromagnetic absorbing materials in recent years, the research progress of Fe-based absorbing materials is reviewed, and the preparation methods, absorbing properties and absorbing mechanisms of iron-based absorbing materials are discussed in detail from the aspects of different morphologies of Fe and Fe-based composite absorbers. Meanwhile, the future development direction of Fe-based absorbing materials is also prospected, providing a reference for the research and development of efficient electromagnetic wave absorbing materials with strong absorption performance, frequency bandwidth, light weight and thin thickness.     

无线Ad hoc网络中的随机功率控制

 由于能量的限制,无线Ad hoc网络面临网络生存时间、无线资源利用效率以及时延要求等方面的挑战.无线Ad hoc网络中的功率控制已经成为研究领域中的一个热点,其主要目的是降低网络在分发数据包中的能量消耗,降低网络中的通信干扰.为了节省网络能量消耗,提出了一种随机功率控制的方法,其核心是让节点的发射功率随机分布在一个功率区间.通过对随机功率控制和固定功率控制在成功传输概率和网络节能上的理论分析和数值计算比较发现,合理选择随机功率控制中的最小发射功率,可获得与固定功率控制相当的成功传输概率,并能节省网络能量消耗,延长网络生存周期.     

一种通用的并联反馈式微波介质振荡器设计方法

介绍了并联反馈式介质振荡器的设计方法和相关理论,分析了影响介质振荡器性能的一些参数。采用高频路仿真和场仿真软件对13.20 GHz的介质振荡器进行设计,仿真结果表明,在偏离载频10 kHz处输出信号相噪为-113.6 dBc/Hz,功率为 10.026 dBm。     

Unusual Normal and Superconducting State Properties Observed in Hydrothermal Fe_(1-δ)Se Flakes

The electronic and superconducting properties of Fe_(1-δ)Se single-crystal flakes grown hydrothermally are studied by the transport measurements under zero and high magnetic fields up to 38.5 T. The results contrast sharply with those previously reported for nematically ordered Fe Se by chemical-vapor-transport(CVT) growth. No signature of the electronic nematicity, but an evident metal-to-nonmetal crossover with increasing temperature,is detected in the normal state of the present hydrothermal samples. Interestingly, a higher superconducting critical temperature T_c of 13.2 K is observed compared to a suppressed T_c of 9 K in the presence of the nematicity in the CVT Fe Se. Moreover, the upper critical field in the zero-temperature limit is found to be isotropic with respect to the field direction and to reach a higher value of ~42 T, which breaks the Pauli limit by a factor of 1.8.