甲硫醇的低能电子弹性碰撞截面

使用R-matrix方法在静态交换和静态交换加极化两种模型下研究电子-甲硫醇的弹性散射．计算的弹性散射截面与已有的实验结果符合的很好．静态交换极化模型探测到了两个具有2A'对称性的形 状共振态,能量位置分别在4.06和8.32 eV．通过波恩修正,用更高的分波l>4获得了收敛的截面．还使用计算的动量转移截面数据计算了200～30000 K的高效电子碰撞频率.     

Electric field gradients at 181Ta probe in ZrNi: Results from perturbed angular correlation and first-principles calculations

Results of temperature dependent perturbed angular correlation (PAC) measurements in the equiatomic ZrNi alloy have been reported for the first time using ¹⁸¹Hf probe. At room temperature, values of quadrupole frequency and asymmetry parameter for the major component (~80%) are found to be ω_Q=26.8(4) Mrad/s, and η=0.413(7). The resulting electric field gradient comes out to be V_zz=2.99 ×10¹⁷ V/cm² and this corresponds to the probe nuclei occupying the regular substitutional Zr sites. In ZrNi system, no magnetic interaction is observed down to 77 K indicating absence of any magnetism in this material. X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) studies on an inactive but similarly prepared sample confirm the dominant presence of the orthorhombic ZrNi phase in the sample. A complementary density functional theory (DFT) calculation results in V_zz=−2.35×10¹⁷ V/cm², η=0.46 at the ¹⁸¹Ta probe impurity site and zero magnetic moment on each atomic site, in close agreement with the experimental results. Furthermore, it is found that electric field gradient for the regular component follows a T^3/2 temperature dependence between 77 and 353 K, beyond which it varies linearly with temperature.     

石墨炉原子吸收光谱法直接测定铝合金中的痕量铍

本文叙述了痕量铍在铝合金中的重要作用以及石墨炉原子吸收光谱法测定铝合金中痕量铍的方法研究。该方法用硝酸（１＋１）溶解样品。０．１０ｍｇ／ｍＬ以上的铝具有增感效应，铍在０－０．２５μｇ／１００ｍＬ的范围内具有良好线性关系。该方法操作简便、灵敏度高，特征浓度为１．０５×１０￣（－５）μｇ／ｍＬ／１％。相对标准偏差为１．６６％，回收率在９６％－１０２．５％。     

Internal stress dependent structural transition in ferromagnetic Ni-Mn-Ga nanoparticles prepared by ball milling

Ni-Mn-Ga nanoparticles were prepared by ball milling technique. X-ray diffraction pattern of the milled powders has a broad peak near the location of the prominent peak for the Heusler phase of Ni₂MnGa, indicating very disordered structures with small particle sizes. Structural properties of milled Ni-Mn-Ga particles recover to those of the bulk state after appropriate annealing temperature. It is worth noting that particles with size above 50 nm exhibit martensitic transformation. The average internal stress was calculated to be 2.83-1.13 MPa stored in the distorted lattice. Saturation magnetization of the milled sample increases with annealing temperature due to re-crystallization and grain growth.     

A memory device sustained by noise

We propose a memory device consisting of a ring of two bistable coupled oscillators. We show that this system is capable of storing a single bit and its performance improves with noise, in agreement with previous experimental results obtained with discrete bistable electronic circuits. The stored bit can be retrieved asynchronously and, after a certain synchronization time, the probability of error does not depend on the interrogated oscillator. Memory persistence is shown to be maximized for the same noise range that both minimizes the probability of error and ensures synchronization.     

The shape of data and probability measures

We introduce the notion of multiscale covariance tensor fields (CTF) associated with Euclidean random variables as a gateway to the shape of their distributions. Multiscale CTFs quantify variation of the data about every point in the data landscape at all spatial scales, unlike the usual covariance tensor that only quantifies global variation about the mean. Empirical forms of localized covariance previously have been used in data analysis and visualization, for example, in local principal component analysis, but we develop a framework for the systematic treatment of theoretical questions and mathematical analysis of computational models. We prove strong stability theorems with respect to the Wasserstein distance between probability measures, obtain consistency results for estimators, as well as bounds on the rate of convergence of empirical CTFs. These results show that CTFs are robust to sampling, noise and outliers. We provide numerous illustrations of how CTFs let us extract shape from data and also apply CTFs to manifold clustering, the problem of categorizing data points according to their noisy membership in a collection of possibly intersecting smooth submanifolds of Euclidean space. We prove that the proposed manifold clustering method is stable and carry out several experiments to illustrate the method.