三维电子散斑干涉技术及其应用研究

通过大错位剪切镜和一作为参考物的压电陶瓷相移器将三个电子散斑干涉系统组成一新的三维电子散斑干涉系统。利用该系统，结合相移技术和图像处理技术，可得到独立的位移场(u,v和w场)。该技术的特点是用三个激光器作为光源，一个压电陶瓷相移器产生参考光并实现相移，CCD摄像机前放置大错位剪切镜以使物光和参考光产生干涉。将该技术应用到柴油发动机零部件测量上，得到了主轴承孔周的三维位移场。     

82-channel multi-wavelength comb generation in a SOA fiber ring laser

We demonstrate a multi-wavelength semiconductor optical amplifier (SOA) fiber ring laser with a dual-pass Mach-Zehnder interferometer (MZI) filter. Two SOAs with different gain spectra provide sufficient gain and a wider gain spectrum to facilitate multi-wavelength lasing. The dual-pass MZI, configured by adding an optical isolator to the two outputs of the conventional MZI, serves as comb filter for multi-wavelength operation, and its extinction ratio can be enhanced to twofold as that of the conventional MZI in the same parameters. To investigate the influences of a dual-pass MZI filter and a conventional MZI filter on multi-wavelength operation, two different cavity configurations are presented and compared, including a single-SOA ring cavity and a double-SOA ring cavity. Stable simultaneous operation at 82 wavelengths, with a wavelength spacing of 40 GHz and a power deviation of 5 dB, and with a minimum optical signal-to-noise ratio (OSNR) of 28 dB, is observed from the double-SOA ring cavity using a dual-pass MZI filter.     

布里渊区内能带E(k)=E(-k)的对称性

说明了布里渊区内能带Ｅ（ｋ）＝Ｅ（－ｋ）的对称性是时间反演对称性的结果，而与晶体的空间对称性无关．并且证明了当晶体具有中心反演对称性时，布里渊区内能带是二重简并的．     

火焰原子吸收光谱法测定6种动物鲜肉中的微量元素的含量

采用HNO3-HClO4(体积比为4∶1)消化体系,在常压微沸消解条件下,用火焰原子吸收光谱法(FAAS)测定了天水市市售6种鲜肉(猪、鸡、牛、羊、鲤鱼、牛蛙)中Zn、Cu、Fe、Mn的含量.结果表明,Zn、Cu、Fe、Mn在6种鲜肉中的含量均差异极显著(P＜o.01);将6种鲜肉按动物类别分为3类:即单胃动物(猪、鸡)鲜肉、反刍动物(牛、羊)鲜肉和水产动物(鲤鱼、牛蛙)鲜肉,结果显示:不同动物类别鲜肉中Zn含量差异极显著(P＜0.01),Cu、Fe含量差异显著(P＜0.05);相关性分析表明,6种鲜肉中Zn和Cu含量呈极显著负相关(P＜0.01); Zn与Mn含量呈显著正相关(P＜0.05);Cu与Mn含量呈显著负相关(P＜0.05);Fe和Mn含量呈极著正相关(P＜0.01).     

Machine Learning Kinetic Energy Functional for a One-Dimensional Periodic System

Kinetic energy(KE) functional is crucial to speed up density functional theory calculation. However, deriving it accurately through traditional physics reasoning is challenging. We develop a generally applicable KE functional estimator for a one-dimensional (1D) extended system using a machine learning method. Our end-to-end solution combines the dimensionality reduction method with the Gaussian process regression, and simple scaling method to adapt to various 1D lattices. In addition to reaching chemical accuracy in KE calculation, our estimator also performs well on KE functional derivative prediction. Integrating this machine learning KE functional into the current orbital free density functional theory scheme is able to provide us with expected ground state electron density.     

黄素体系电子转移过程光谱研究

黄素类物质在生物体内广泛存在,是许多电子转移反应的活性中心,也是电子传递链的重要组成部分。其受到光照激发后引起的电子转移,是许多生命过程的基础与起始步骤。特别地,一种名为隐花色素的黄素蛋白在光激发后经一系列电子转移形成自旋相关自由基对,被认为是最有可能的生物磁敏物质,更使黄素体系电子转移过程的动力学,特别是自旋动力学过程倍受关注。对黄素电子转移过程及相关机理进行研究,有助于厘清多种生命过程的化学机理与影响因素。为此,科学界综合运用了多种仪器与测试手段,其中主要包括紫外-可见光谱,荧光光谱,瞬态吸收光谱,光化学诱导动态核极化（Photo-CIDNP）技术等。通过多年的研究,对黄素在生物体内的作用机理与电子转移过程的认识经历了由浅入深,不断深入的过程。紫外-可见光谱（UV-Vis）主要用于研究黄素系统中的电子激发,自旋动力学和电子转移。结合理论计算,UV-Vis还可以识别电子转移中涉及的基团并进行定量分析。荧光光谱可以识别电子受激发的物质,在反应过程中观察黄素和半醌中间体的产生和消耗,并确定其氧化还原和质子化状态。瞬态吸收光谱适于观测反应过程中出现的短寿命物种,其中飞秒泵浦探测技术的引入大大提高了观测的时间分辨率,并且可以通过光谱特征区分单重态和三重态的自由基对。光化学诱导动态核极化核磁共振（NMR）可以直接观察电子-核自旋动力学过程。磁场依赖性photo-CIDNP NMR揭示了控制单重态与三重态互变的因素,并提出了生物地磁导航可能依赖的化学机制。腔吸收与单分子光谱的运用,从技术上提高了实验装置的灵敏度并降低检测限。主要介绍黄素体系电子转移过程研究所运用的各种光谱手段与取得的成果,并展望其未来。     

Dynamic maintenance decision-making for series–parallel manufacturing system based on MAM–MTW methodology

Proper maintenance schedule is required to improve manufacturing systems’ profitability and productivity. A novel dynamic maintenance strategy is thus developed to incorporate both the single-machine optimization and the whole-system schedule for series–parallel system. Firstly, multiple attribute value theory and maintenance effects are considered in the single-machine optimization. A developed multi-attribute model (MAM) is used to determine the optimal maintenance intervals. Then, a series–parallel structure of the system is investigated in terms of the whole-system schedule. Maintenance time window (MTW) programming is presented to make a cost-effective system schedule by dynamically utilizing maintenance opportunities. The maintenance scheme achieved by using the proposed MAM–MTW methodology is demonstrated through a case study in a hydraulic steering factory. It is concluded that proper consideration of maintenance effects and time window leads to a significant cost reduction.     

50,52,53,54Cr光核反应数据评价

通过分析光子诱发52,50Cr核反应的各类实验数据,澄清52Cr光子吸收截面评价数据与中子、质子出射截面测量值间的分歧,给出了52Cr中子出射截面实验数据的修正;选取EGLO模型光子强度函数,结合准氘模型,给出光子吸收截面。在此基础上,采用最新研制的光子与中重核反应计算程序MEND-G,通过优化理论模型参数,包括剩余核的能级密度和对能修正参数,给出光子能量在200 MeV范围内的n、p、${{\rm{\alpha }}}$等粒子出射核反应的截面,52,50Cr的计算结果在30 MeV以下能区很好地符合了现有实验数据,并按国际标准ENDF/B-6库格式给出了50,52,53,54Cr的全套数据文档,便于核工程用户使用。     

A giant enhancement of magnetic moment in a ternary three-shell icosahedral cluster: Fe@Mn12@Au20

ABSTRACT

The average magnetic moment per atom of Mn₁₃ cluster is expected to be enhanced by doping or coating with a shell. Several ternary core–shell icosahedral clusters TM@Mn₁₂@Au₂₀ were constructed by combining substituting the central Mn with VIII elements (Fe, Co, Ni, Ru, Rh, Pd and Pt) and coating with a icosahedral Au₂₀ shell, and systematically studied by using the first-principles density functional method. Compared to Mn₁₃, Fe@Mn₁₂@Au₂₀ cluster shows a giant enhancement on total magnetic moment (52?µ_B) which can be greatly attributed to the ferromagnetic coupling between spin moments of atoms. Coating with Au₂₀ shell enlarged the average distances of TM-Mn and Mn-Mn and is a useful way to change the magnetic coupling style. By analysis of density of states and electron localisation functional, we can conclude that the weak hybridisation between Fe and Mn in Fe@Mn₁₂@Au₂₀ is propitious to maintain their original direction of spin moments of atoms and then form ferromagnetic coupling.     

Fault Diagnosis of Rolling Bearings Based on WPE by Wavelet Decomposition and ELM

The fault diagnosis classification method based on wavelet decomposition and weighted permutation entropy (WPE) by the extreme learning machine (ELM) is proposed to address the complexity and non-smoothness of rolling bearing vibration signals. The wavelet decomposition based on ‘db3’ is used to decompose the signal into four layers and extract the approximate and detailed components, respectively. Then, the WPE values of the approximate (CA) and detailed (CD) components of each layer are calculated and composed to be the feature vectors, which are finally fed into the extreme learning machine with optimal parameters for classification. The comparative study of the simulations based on WPE and permutation entropy (PE) shows that the classification method of seven kinds of signals of normal bearing signals and six types of fault states (7 mils and 14 mils) based on WPE (CA, CD) with the number of nodes in the hidden layers of ELM determined by the five-fold cross-validation has the best performances, the training accuracy can reach 100%, and the testing accuracy can reach 98.57% with 37 nodes of the hidden layer by ELM. The proposed method using WPE (CA, CD) by ELM provides guidance for the multi-classification of normal bearing signals.