微纳米加工技术在纳米物理与器件研究中的应用

物质在纳米尺度下可能呈现出与体材料不同的物理特件，这正是纳米科技发展的基础之一。要想探索在纳米尺度下材料物埋性质的变化规律及可能的应用领域，离不开相应的技术手段，微纳米加工技术作为当今高技术发展的重要技术领域之一，是实现功能人工纳米结构与器件微纳米化的基础。本文根据几个不同的应用领域，介绍了微纳米加工技术在纳米物理与器件研究领域的应用。     

用一类特定的双耦合Duffing振子系统检测强色噪声背景中的周期信号

通过分析耦合参数作用、系统所呈现大尺度周期相态的复杂性以及与系统在无噪声条件下状态的比较，得出耦合振子系统的动力学行为比同类单振子系统的复杂，周期相态更稳定、抗噪能力更强.用构造的一类含特定恢复力项双中强度耦合Duffing振子系统检测色噪声背景中的谐波、方波信号，信噪比分别达到-111.0和-108.45dB. 关键词： 特定双耦合 Duffing振子系统 色噪声 周期信号 信噪比     

Solvothermal synthesis of TiO2: anatase nanocrystals and rutile nanofibres from TiCl4 in acetone

This work reports a new synthetic approach for single‐phase TiO₂ nanomaterials by solvothermal treatment of titanium tetrachloride in acetone at 80–110 °C. Small, uniform, and yet size‐tunable (5–10 nm) anatase titania nanocrystallites were obtained using a low concentration of TiCl₄ in acetone (i.e., at molar ratios of TiCl₄/acetone ≤ 1:15) in the temperature range of 80–110 °C, while rutile nanofibers were synthesized using a high concentration of TiCl₄ (e.g., TiCl₄/acetone = 1:10) at 110 °C. Copyright © 2007 John Wiley & Sons, Ltd.     

Generalization of Einstein relation for doped organic semiconductors

Under the assumption of Gaussian energy distributions of the lowest unoccupied molecular orbital (LUMO) and the highest occupied molecular orbital (HOMO), analytical expressions of generalized Einstein relation for electron and hole transport in doped organic semiconductor thin films are developed. Numerical calculations show that, although traditional Einstein relation still holds for low carrier concentrations, that is, the diffusion-coefficient-to-mobility ratio in units of k_BT/q, with k_B the Boltzmann’s constant, T the temperature and q the elementary charge, equals 1. But when the electron (hole) concentration is high, the diffusion-coefficient-to-mobility ratio for electrons (holes) changes strongly with the electron (hole) concentration, the doping level, the mean energy of LUMOs (HOMOs) of the dopant E_Ld (E_Hd) and the host E_L (E_H), as well as their variances. Dopants with E_Ld<E_L (E_Hd>E_H) affect the diffusion-coefficient-to-mobility ratio mainly in the range of low and middle carrier concentrations, while those with E_Ld>E_L (E_Hd<E_H) have significant effect only in the range of high carrier concentrations. It was found that there can be a maximum in the dependence of the diffusion-coefficient-to-mobility ratio on the quasi-Fermi energy or carrier concentration exist, for appropriate values of the doping level, the mean energy and variance of LUMO or HOMO states of the dopant. PACS 71.20.Rv; 72.90.+y; 73.50.-h     

On the uniqueness of the foliation of spheres of constant mean curvature in asymptotically flat 3-manifolds

In this note we study constant mean curvature surfaces in asymptotically flat 3-manifolds. We prove that, outside a given compact subset in an asymptotically flat 3-manifold with positive mass, stable spheres of given constant mean curvature are unique. Therefore we are able to conclude that the foliation of stable spheres of constant mean curvature in an asymptotically flat 3-manifold with positive mass outside a given compact subset is unique.

     

3004铝合金“反常”锯齿屈服现象的研究

在应变速率为5.56×10^-5s^-1—5.56×10^-3s^-1的范围内，在不同温度下(从223K至773K)，对3004铝合金进行系列拉伸试验，探索其锯齿屈服规律；通过激活能的计算、内耗研究、微观组织观察和能谱分析，探讨锯齿屈服的机理与物理本质.结果表明，3004铝合金在形变过程中会出现动态应变时效现象；发现了一种“反常”的锯齿屈服现象：在出现锯齿屈服的温区内，存在锯齿屈服临界应变量转变温度T_t， 关键词： 动态应变时效 锯齿屈服 铝合金 内耗     

交流源作用下介观RLC电路系统量子态随时间的演化

根据量子不变量理论，同时考虑介观电容器极板间电子波函数的耦合作用和电路的耗散,研究介观RLC电路系统在交流电流源作用下动力学的演化过程，并且得到描述系统量子态随时间的演化算符.进一步的分析结果表明，介观RLC电路系统的波函数将由任意的初态演化到一般的压缩态. 关键词： 介观RLC电路 交变电源 不变量理论 时间演化算符     

含有五边形—七边形缺陷的单壁纳米碳管的输运性质研究

运用第一性原理的密度泛函理论结合非平衡格林函数研究了含有五边形—七边形拓扑缺陷的纳米碳管异质结的输运性质.结果发现：拓扑缺陷对碳管的输运性质有很大影响；另外，不同类型的碳管形成的异质结的输运性质也有明显的差异. 关键词： 纳米碳管 输运性质 异质结 透射系数     

透镜初级球差的横向剪切干涉条纹研究

利用玻璃平行平板构成简单的横向剪切干涉仪可以观察到单薄透镜形成的准直光束的剪切干涉条纹,由干涉条纹分布求出对应的几何像差和离焦量.用焦距为190 mm的单薄透镜做实验,实验结果与计算机模拟结果符合,说明可以从剪切干涉条纹的分布求出透镜的轴向调整误差和初级球差.     

Feature Selection using Fuzzy Support Vector Machines

The feature selection consists of obtaining a subset of these features to optimally realize the task without the irrelevant ones. Since it can provide faster and cost-effective learning machines and also improve the prediction performance of the predictors, it is a crucial step in machine learning. The feature selection methods using support machines have obtained satisfactory results, but the noises and outliers often reduce the performance. In this paper, we propose a feature selection approach using fuzzy support vector machines and compare it with the previous work, the results of experiments on the UCI data sets show that feature selection using fuzzy SVM obtains better results than using SVM.