发光晶体NaTm（WO4）4的光谱性质及光谱参数

在已获得Ｔｍ＾３＋在Ｎａ５Ｔｍ（ＷＯ４）４晶体中强度参数Ωλ（λ＝２，４，６）的基础上，根据Ｊｕｄｄ－Ｏｆｅｌｔ理论，计算了Ｔｍ＾３＋多重量激发态之间的辐射跃迁几率、辐射寿命，荧光分支比及积分发射截面等光谱参数，并对晶体实现激光输出的可能性进行了讨论。     

Na5Dy（WO4）4晶体的结构与光谱

以分析纯Ｎａ２ＷＯ４为助熔剂，采用缓冷法培养出淡黄色单晶体Ｎａ５Ｄｙ（ＷＯ４）４。研究了该晶体的吸收光谱、荧光光谱及激发光谱。计算了它的晶胞参数：ａ＝１１．４２４Ａ，ｃ＝１１．３３５Ａ。并确定了Ｄｔ＾３＋的能级，为进一步研究其激光性能提供必要的数据基础。     

MgO对C_4A_3S水化性能的影响

用ＸＲＤ，ＩＲ和化学分析法研究了ＭｇＯ对Ｃ＿４Ａ＿３Ｓ晶体水化性能的影响。结果大明，ＭｇＯ的引不影响Ｃ＿４＿３的晶体形态和晶格尺寸，Ｍｇ￣（２＋）以间隙方式固溶入Ｃ＿４Ａ＿３晶体的晶格空隙中。用微量热仪和浆体的线性膨胀率探讨了ＭｇＯ对Ｃ＿４Ａ＿３水化性能的影响。结果表明，ＭｇＯ能延缓Ｃ＿４Ａ＿３的早期水化，降低其线性膨胀率，冈而体积稳定性得到提高。     

溶液掺杂法制备掺了Tm~(3+)单模石英光纤

本文主要论述了溶液掺杂法制备掺Ｔｍ~（３＋）单模石英光纤的技术和工艺、Ｔｍ~（３＋）掺杂浓度、脱水过程与Ｔｍ~（３＋）沿光纤芯部剖面掺杂分布的控制,以及光纤诸参数的优化设计。     

新的稀土锂钒酸盐的合成,结构和发光

本文首次报道了在６００℃灼烧数小时合成出新的稀土锂钒醛盐Ｙ０．５－ｘＬｉ１．５ＶＯ４；ＲＥｘ（ＲＥ＝Ｓｍ＾３＋，Ｄｙ＾３＋，Ｈｏ＾３＋，Ｅｒ＾３＋，Ｔｍ＾３＋）（０．０１＜ｘ＜０．０１）多晶粉末。比通常钒酸盐的合成温度降低近４００℃。用Ｘ射线粉末法分析此多晶粉末的结构。     

Ca8M（SiO4）4Cl2（M=Mg,Zn）中Ce^3＋的发光性质

报道了氯硅酸镁钙Ｃａ８Ｍｇ（ＳｉＯ４）４Ｃｌ２及氯硅酸锌钙Ｃａ８Ｚｎ（ＳｉＯ４）４Ｃｌ２中Ｃｅ＾３＋的发光特性，研究并分析了Ｃｅ＾３＋在这两种材料中的激发光谱，发射光谱及荧光衰减特性，在ＵＶ辐射激发下，Ｃｅ＾３＋发射出强的蓝紫光。室温下Ｃｅ＾３＋在两种材料中的荧光寿命分别为６１ｎｓ和４４ｎｓ。     

MgO对C4A3S↑—水化性能的影响

用ＸＲＤ，ＩＲ和化学分析法研究了ＭｇＯ对Ｃ４Ａ３Ｓ↑－晶体水化性能的影响。结果表明，ＭｇＯ的引入不影响Ｃ４Ａ３Ｓ↑－的晶体形态和晶格尺寸，Ｍｇ＾２＋以间隙方式固溶入Ｃ４Ａ３Ｓ↑－晶体的晶格空隙中。用微量热仪和浆体的线性膨胀率探讨了ＭｇＯ对Ｃ４Ａ３Ｓ↑水化性能的影响。结果表明，ＭｇＯ能延缓Ｃ４Ａ３Ｓ↑－的早期水化，降低其线性膨胀率，因而体积稳定性得到提高。     

共掺ZnO提高LiNbO3晶体中Ho3+分凝系数的研究

在Ｈｏ：ＬｉＮｂＯ３中掺入摩尔分数为６％和ＺｎＯ，生长（Ｈｏ，ＺｎＯ）：ＬｉＮｂＯ３晶体。用电感硝等离子体发射光谱（ＩＣＰ－ＡＥＳ）法，测定了晶体不同部位Ｈｏ＾３＋的浓度，并计算其分凝系数，共掺ＺｎＯ后，晶体中Ｈｏ＾３＋的分凝系数为０．３提高到０．６，表明Ｈｏ＾３＋在晶体中分布更为均匀。对双掺Ｈｏ和Ｚｎ的ＬｉＮｂＯ３晶体组分均匀性提高的机理进行了探讨。     

二高氯酸四（2－羟基吡啶）二水合钴的单晶制备及结构分析

２－羟基吡啶（ＨＬ）、Ｔｂ（ＣｌＯ_４）_３·６Ｈ_２Ｏ和Ｃｏ（ＣＨ_３ＣＯＯ）_２·４Ｈ_２Ｏ在乙腈中反应，制备了［Ｃｏ（ＨＬ）_４（Ｈ２Ｏ）_２］（ＣｌＯ_４）_２，并且测定了它的晶体结构。［Ｃｏ（ＨＬ）_４（Ｈ_２Ｏ）_２］（ＣｌＯ_４）_２的晶体为单斜晶系，ｐ２１／ｎ空间群，晶胞参数为α＝０．９３１３（３）ｎｍｂ＝１．１５８６（１）ｎｍ，ｃ＝１．２９８４（２）ｎｍ，β＝９７．２４（２）°。［Ｃｏ（ＨＬ）_４（Ｈ_２Ｏ）_２］￣（２＋）为六配位畸变八面体构型，２－羟基吡啶的氧原子同钴配位。     

4氨基吡啶的合成

４－氨基吡啶（Ⅰ）是有机合成和医药合成的中间体，也是合成新型降压药吡那地尔（Ｐｉｎａｃｉｄｉｌ）的重要原料。Ⅰ作为分析试剂，其合成路线［１］如下：ＮＣＯＣＯＯ，Ｈ２Ｏ２→ＮＯＨ＋·ＣＯＯ－ＣＯＯＨＨＣｌ→ＮＯＨ＋·Ｃｌ－ＫＮＯ３，Ｈ２ＳＯ４→Ｎ（Ⅱ）...     

Er:LiGdF_4晶体生长及光谱性能

采用提拉法生长出掺铒氟化钆锂(Er3+:LiGdF4,Er:LGF)激光晶体。晶体生长工艺参数为:提拉速率为0.16mm/h,晶体转速为3r/min,冷却速率为10℃/h。X射线粉末衍射分析表明:晶体属于四方晶系,白钨矿结构,空间群为I41/a,计算的晶胞参数:a=0.5196nm,c=1.10286nm。晶体的吸收光谱和荧光光谱表明:晶体在659,980nm和1540nm附近的吸收峰较强,其中在1540nm处的吸收截面为1.09×10-20cm2。在激光二极管的532nm波长泵浦下,发射峰分别位于995nm和1530nm附近,其中1530nm处的半高宽为52nm。     

SPECTRAL ANALYSIS WITH TAPERED DATA

Abstract. A new method based on an upper bound for spectral windows is presented for investigating the cumulants of time series statistics. Using this method two classical results are proved for tapered data. In particular, the asymptotic normality for a class of spectral estimates including estimates for the spectral function and the covariance function is proved under integrability conditions on the spectra using the method of cumulants.     

BIAS-CORRECTED NONPARAMETRIC SPECTRAL ESTIMATION

Abstract. The theory of nonparametric spectral density estimation based on an observed stretch X₁,…, X_N from a stationary time series has been studied extensively in recent years. However, the most popular spectral estimators, such as the ones proposed by Bartlett, Daniell, Parzen, Priestley and Tukey, are plagued by the problem of bias, which effectively prohibits ?N-convergence of the estimator. This is true even in the case where the data are known to be m-dependent, in which case ?N-consistent estimation is possible by a simple plug-in method. In this report, an intuitive method for the reduction in the bias of a nonparametric spectral estimator is presented. In fact, applying the proposed methodology to Bartlett's estimator results in bias-corrected estimators that are related to kernel estimators with lag-windows of trapezoidal shape. The asymptotic performance (bias, variance, rate of convergence) of the proposed estimators is investigated; in particular, it is found that the trapezoidal lag-window spectral estimator is ?N-consistent in the case of moving-average processes, and ?(N/log/N)-consistent in the case of autoregressive moving-average processes. The finite-sample performance of the trapezoidal lag-window estimator is also assessed by means of a numerical simulation.     

DISCRIMINATING BETWEEN TWO SPECTRAL DENSITIES IN CASE OF REPLICATED OBSERVATIONS

Abstract. Coates and Diggle (1986) introduced a test procedure for the comparison of the spectral densities of two stationary processes. We extend this test to a situation in which replicated observations are available for each process.     

REGRESSION OF SPECTRAL ESTIMATORS WITH FRACTIONALLY INTEGRATED TIME SERIES

Abstract. Assuming a normal distribution we supplement the proof of periodogram regression suggested by Geweke and Porter-Hudak ( J. Time Ser. Anal. 4 (1983) 221–38) in order to estimate and test the difference parameter of fractionally integrated autoregressive moving-average models. The procedure proposed by Kashyap and Eom ( J. Time Ser. Anal. 9 (1988) 35–41) arises as a special case and is found to be correct if the true parameter value is negative. Regression of the smoothed periodogram yields estimators for the difference parameter with much faster vanishing variance; no asymptotic distribution can be derived, however. In computer experiments we find that the smoothed periodogram regression may be superior to pure periodogram regression when we have to discriminate between autoregression and fractional integration     

CONTRIBUTIONS TO EVOLUTIONARY SPECTRAL THEORY

Abstract. The purpose of this paper is to discuss several fundamental issues in the theory of time-dependent spectra for univariate and multivariate non-stationary processes. The general framework is provided by Priestley's evolutionary spectral theory which is based on a family of stochastic integral representations. A particular spectral density function can be obtained from the Wold—Cramér decomposition, as illustrated by several examples. It is shown why the coherence is time invariant in the evolutionary theory and how the theory can be generalized so that the coherence becomes time dependent. Statistical estimation of the spectrum is also considered. An improved upper bound for the bias due to non-stationarity is obtained which does not rely on the characteristic width of the process. The results obtained in the paper are illustrated using time series simulated from an evolving bivariate autoregressive moving-average process of order (1, 1) with a highly time-varying coherence.     

LOCALLY ADAPTIVE LAG-WINDOW SPECTRAL ESTIMATION

Abstract. We propose a procedure for the locally optimal window width in nonparametric spectral estimation, minimizing the asymptotic mean square error at a fixed frequency Λ of a lag-window estimator. Our approach is based on an iterative plug-in scheme. Besides the estimation of a spectral density at a fixed frequency, e.g. at frequency Λ = 0, our procedure allows to perform nonparametric spectral estimation with variable window width which adapts to the smoothness of the true underlying density.     

WAVELETS AND TIME-DEPENDENT SPECTRAL ANALYSIS

Abstract. One of the key features of wavelet analysis is its potential use for effecting time-frequency decompositions of non-stationary signals. The relationship between wavelet analysis and time-dependent spectral analysis has so far rested mainly on heuristic reasoning:in this paper we examine the relationship in a more precise mathematical form. A crucial feature of this analysis is the need to define carefully the notion of "frequency" when applied to non-stationary signals.     

SPECTRAL ANALYSIS FOR AMPLITUDE-MODULATED TIME SERIES

Abstract. Let { X ( n )} be a non-observed strictly stationary process, { a ( n )} a sequence independent of { X ( n )} and Y ( n ) = a ( n ) X ( n ) the observed process. This work deals with the estimation of the spectral density function fx ( Λ ) of the process of interest, { X ( n )}, using observations of the modulated process { Y ( n )}. We obtain estimators of fx ( Λ ) for three types of modulating functions:deterministic, random independent and random correlated.