Synthesis and photoluminescence of ZnS : Cu nanoparticles

The room-temperature photoluminescence (PL) of copper doped zinc sulfide (ZnS:Cu) nanoparticles were investigated. These ZnS:Cu nanoparticles were synthesized by a facile wet chemical method, with the copper concentration varying from 0 to 2 mol%. By Gaussian fitting, the PL spectrum of the undoped ZnS nanoparticles was deconvoluted into two blue luminescence peaks (centered at 411 nm and 455 nm, respectively), which both can be attributed to the recombination of the defect sates of ZnS. But for the doped samples, a third peak at about 500 nm was also identified. This green luminescence originates from the recombination between the shallow donor level (sulfur vacancy) and the t(2) level of Cu2+. With the increase of the CU2+ concentration, the green emission peak is systematically shifted to longer wavelength. In addition, it was found that the overall photoluminescence intensity is decreased at the Cu2+ concentration of 2%. The concentration quenching of the luminescence may be caused by the formation of CuS compound. (c) 2005 Elsevier B.V. All rights reserved.

Two opposite gradients of hole density in as-grown and annealed (Ga,Mn)As layers

The depth distribution of the hole density p in 500 nm-thick (Ga,Mn)As layers is investigated. From Raman scattering spectra, it is found that the gradients of p are opposite in the as-grown and annealed layers. At the region around the free surface, with increasing etching depth, p significantly increases in the as-grown layer; however, p decreases distinctly in the annealed layer. Then, in the bulk, p becomes almost homogeneous for both cases. The etching-depth dependence of Curie temperature obtained from magnetic measurements is in agreement with the distribution characterization of p. These results suggest that annealing induces outdiffusion of Mn interstitials towards the free surface, and incomplete outdiffusion during the growth leads to an accumulation of Mn interstitials around the free surface of the as-grown (Ga,Mn)As. (c) 2006 Elsevier B.V. All rights reserved.

Effects of phase-breaking on long-range charge transfer in DNA: Partially-coherent-tunneling model study

The mechanism of hole charge transfer in DNA of various lengths and sequences is investigated based on a partially coherent tunneling theory (Zhang et al., J Chem Phys 117:4578, 2002), where the effects of phase-breaking in adenine-thymine and guanine-cytosine base pairs are treated on equal foot. This work aims at providing a self-consistent microscopic interpretation for rate experiments on various DNA systems. We will also clarify the condition under which the simple superexchange-mediated-hopping picture is valid, and make some comments on the further development of present theory.

Optical-phonon modes and Frohlich potential in quantum dots

By extending the microscopic dipole model on optical-phonon modes as applied in quantum wells and quantum wires, to rectangular quantum dots (QD), optical phonon modes and their accompanying Frohlich potentials in QD are calculated and classified. When the bulk phonon dispersion is ignored, the optical phonon modes in QD can be clearly divided into the confined LO- and TO-bulk-like modes and the extended interface-like modes. Among the interface-like modes, a special attention is given to the corner modes, whose anisotropic behavior is depicted in the long wavelength limit. Based on the numerical results, a set of analytical formula are proposed to approximately describe the bulk-like modes, for which both the optical displacements and Frohlich potentials vanish at the interfaces. (C) 2000 Elsevier Science Ltd. All rights reserved.

Structure approximate based on double weighted neural network

Double weighted neural network; is a kind of new general used neural network, which, compared with BP and RBF network, may approximate the training samples with a move complicated geometric figure and possesses a even greater approximation. capability. we study structure approximate based on double weighted neural network and prove its rationality.

Dynamic power management approaches based on neural network

Dynamic Power Management (DPM) is a technique to reduce power consumption of electronic system. by selectively shutting down idle components. In this article we try to introduce back propagation network and radial basis network into the research of the system-level policies. We proposed two PAY policies-Back propagation Power Management (BPPM) and Radial Basis Function Power management (RBFPM) which are based on Artificial Neural Networks (ANN). Our experiments show that the two power management policies greatly lowered the system-level power consumption and have higher performance than traditional Power Management(PM) techniques-BPPM is 1.09-competitive and RBFPM is 1.08-competitive vs. 1.79,145,1.18-competitive separately for traditional timeout PM, adaptive predictive PM and stochastic PM.

Cancer classification based on direction-basis-function neural networks

Automatic molecular classification of cancer based on DNA microarray has many advantages over conventional classification based on morphological appearance of the tumor. Using artificial neural networks is a general approach for automatic classification. In this paper, Direction-Basis-Function neuron and Priority-Ordered algorithm are applied to neural networks. And the leukemia gene expression dataset is used as an example to testify the classifier. The result of our method is compared to that of SVM. It shows that our method makes a better performance than SVM.

Research of Face Location System Based on Human Vision Simulations

In this paper we present a robust face location system based on human vision simulations to automatically locate faces in color static images. Our method is divided into four stages. In the first stage we use a gauss low-pass filter to remove the fine information of images, which is useless in the initial stage of human vision. During the second and the third stages, our technique approximately detects the image regions, which may contain faces. During the fourth stage, the existence of faces in the selected regions is verified. Having combined the advantages of Bottom-Up Feature Based Methods and Appearance-Based Methods, our algorithm performs well in various images, including those with highly complex backgrounds.

Interaction of linear waves with infinitely long horizontal cylinders studied by boundary element method

The two-dimensional problems concerning the interaction of linear water waves with cylinders of arbitrary shape in two-layer deep water are investigated by use of the Boundary Integral Equation method (BIEM). Simpler new expressions for the Green functions are derived, and verified by comparison of results obtained by BIEM with these by an analytical method. Examined are the radiation and scattering of linear waves by two typical configurations of cylinders in two-layer deep water. Hydrodynamic behaviors including hydrodynamic coefficients, wave forces, reflection and transmission coefficients and energies are analyzed in detail, and some interesting physical phenomena are observed.

马蹄形过水断面临界水深的直接计算法

马蹄形过水断面是无压隧洞较常采用的断面形式之一,水力计算中临界水深的求解无显函数公式,传统的试算法或查图法不仅计算过程繁琐复杂,而且计算精度不高。该文通过对马蹄形断面临界流方程的数学变换,并对本文引入的无量纲参数与相对临界水深的关系分析及数值计算,应用逐步优化拟合原理,得到标准Ⅰ、Ⅱ型马蹄形断面临界水深的直接计算式。实例计算及误差分析表明:在工程实用范围内该公式最大相对误差仅为0.8%,且该式物理概念清晰明确、公式形式简捷,为工程设计及水工设计手册的编制提供有益的参考。