能量回收型直线加速器

 能量回收型直线加速器(EnergyRecoveringLinacs,简称ERL),是一种新型的、发展中的加速器,它具有直线加速器的优质束流性能,具有接近环型加速器的高效率。已在自由电子激光等方面投入应用,并具有多方面的发展和应用前景。一、由来和优势我们知道,高频电子直线加速器是用高频电场加速沿直线轨道运动的电子束的装置。通常,电子束只通过直线加速结构一次,在达到要求的能量后,即离开直线加速器,或直接用于科学实验、医学放疗、材料辐照、自由电子激光驱动等;或注入到环型加速器中继续加速和积累,用于同步辐射光源或高能物理实验等。     

耦合非线性Schrdinger系统的多辛差分格式

近年来,Bridges等人在Hamiltonian力学意义下,直接把有限维Hamiltonian系统推广到无穷维,通过引入新的函数坐标,使得偏微分方程在时间和空间的各个方向上都有各自不同的有限维辛结构,这样原偏微分方程就由各个有限维辛结构以及右端的梯度函数决定,称这样的方程为多辛Hamiltonian系统.多辛Hamiltonian系统满足多辛守恒定律,满足多辛Hamiltonian系统的多辛守恒律的离散算法称为多辛算法.以耦合非线性Schr dinger方程为例,研究无穷维Hamiltonian系统的多辛算法,验证了两孤立子碰撞后会发生相互通过、反射及融合现象.     

Novel Chiral Ferrocenyl Aziridino Alcohol Catalysts Promoting Asymmetric Addition of Diethylzinc to Aldehydes

Optically active aziridino alcohols containing ferrocenyl groups were prepared from commercially available L-threonine in excellent yields and used as catalysts to promote the asymmetric addition of diethylzinc to aryaldehydes to afford 1-arylpropanol in up to 84% enantiomeric excesses with moderate to good yields.     

Studies on the Adsorption of Asymmetrical Triblock Copolymers by Scheutjens-Fleer Theory and Monte Carlo Simulation

The adsorption of asymmetrical triblock copolymers from a non-selective solvent on solid surface has been studied by using Scheutjens-Fleer mean-field theory and Monte Carlo simulation method on lattice model. The main aim of this paper is to provide detailed computer simulation data, taking A8-kB20Ak as a key example, to study the influence of the structure of copolymer on adsorption behavior and make a comparison between MC and SF results. The simulated results show that the size distribution of various configurations and density-profile are dependent on molecular structure and adsorption energy. The molecular structure will lead to diversity of adsorption behavior. This discrepancy between different structures would be enlarged for the surface coverage and adsorption amount with increasing of the adsorption energy. The surface coverage and the adsorption amount as well as the bound fraction will become larger as symmetry of the molecular structure becomes gradually worse. The adsorption layer becomes thicker with increasing of symmetry of the molecule when adsorption energy is smaller but it becomes thinner when adsorption energy is higher. It is shown that SF theory can reproduce the adsorption behavior of asymmetrical triblock copolymers. However, systematic discrepancy between the theory and simulation still exists.The approximations inherited in the mean-filed theory such as random mixing and the allowance of direct back folding may be responsible for those deviations.     

微全分析系统检测方法的研究进展

综述了不同类型的检测方法在微全分析系统的应用，并简述了各类型的检测方法的优缺点。引用文献92篇。     

r－不可分矩阵的本原指数（Ⅱ）

本文给出了 n阶 r-不可分矩阵的本原指数的上界 ,即任 n阶 r—不可分矩阵 A的本原指数 (A)≤n+(r- ) 2r (1≤ r相似文献   

晶体微观结构的数值计算

晶体微观结构是晶体材料在特定物理条件下其多个能量极小平衔态在空间形成的某种微尺度的规则分布．几何非线性的连续介质力学理论可以用能量极小化原理来解释晶体微观结构的形成，并用Young测度来刻画平衡态各变体在空间的概率分布．定性的理解与定量地分析和计算晶体材料的微观结构对于发展和改进高级晶体功能材料，如形状记忆合金、铁电体、磁至伸缩材料等，有重要的意义．本文回顾了近年来晶体微观结构数值计算方面的最新进展．介绍了计算晶体微观结构的几种数值方法及有关的数值分析结果。     

Birkhoff系统的Hojman定理的几何基础

研究了Birkhoff系统的Hojman定理的几何基础.建立了系统的运动微分方程和Hojman守恒 定理，利用现代微分几何给出了Birkhoff系统的Hojman定理的一个证明. 关键词： Birkhoff系统 Hojman定理 对称性 微分几何     

Gain Spectrum in an Asymmetric Double Quantum Well

We propose a scheme for light amplification in an asymmetric double quantum well, where two excited states are coupled by resonant tunnelling through a thin barrier in a three-level system of electronic subbands. By applying a single driving laser, the steady state gain can be obtained. The calculated gain spectrum for an asymmetric GaAs/AlGaAs double quantum well structure was presented.     

Local Prediction of Chaotic Time Series Based on Support Vector Machine

Based on phase space delay-coordinate reconstruction of a chaotic dynamics system, we propose a local prediction of chaotic time series using a support vector machine （SVM） to overcome the shortcomings of traditional local prediction methods. The simulation results show that the performance of this proposed predictor for making onestep and multi-step prediction is superior to that of the traditional local linear prediction method and global SVM method. In addition, it is significant that its prediction performance is insensitive to the selection of embedding dimension and the number of nearest neighbours, so the satisfying results can be achieved even if we do not know the optimal embedding dimension and how to select the number of nearest neighbours.