电感耦合等离子体原子发射光谱分析中光谱干扰校正卡尔曼滤波法研究

本文利用电感耦合等离子体原子发射光谱多色仪的扫描功能,用卡尔曼滤波法对各种光谱干扰进行校正。结果表明,该法能处理各种类型光谱干扰,不需要样品基体匹配,其测定回收率明显优于在峰法和离峰法,具有简便、准确等优点。     

偏最小二乘法在原子吸收光谱分析中的应用——钴和铟的同时测定

本文用偏最小二乘法（ＰＬＳ）校正了火焰原子吸收分析Ｉｎ２５２．１３７ｎｍ对Ｃｏ２５２．１３６ｎｍ的吸收线重叠干扰,对混合样中Ｃｏ和Ｉｎ的含量进行了测定,结果令人满意。     

Analyzing electrochemical noise with Chebyshev’s discrete polynomials

The principles underlying a novel method intended for analyzing experimental data obtained when studying fluctuation processes are considered. The method in question is Chebyshev’s spectroscopy. The application of this method allows one to determine statistic characteristics of steady-state electrochemical noise against the background of severe deterministic interference without invoking the procedure of the fitting of the initial data. The potentialities of this novel method, which is intended for treating noise experiment, are demonstrated by examining model examples and analyzing the electrochemical noise generated by a lithium electrode placed in an aprotic organic electrolyte.     

海底沉积物的ICP-AES分析

海底沉积物用硝酸-高氯酸-氢氟酸消解,然后用ICP-AES法同时测定常量和微量元素。研究了样品中基体元素对微量元素测定的光谱干扰,并采用干扰曲线斜率法进行干扰校正,分析批量海底沉积物样品获得满意结果。     

磁场对含稀土铝锂合金断裂特征的影响

以含铈铝锂合金为研究对象，研究了磁场对含稀土铝锂合金时效过程的影响，从断裂特征及微观组织两方面分析了磁场作用规律。实验结果表明：未加磁场时，合金的断裂特征以理断裂为主；扁平晶粒厚度不匀，在磁场作用下，此合金的断裂特征与微观组织发生明显改观，随磁感应强度增强，合金主断裂面上准解理断裂特征减弱，同时二次裂纹增多，分层比较升高；扁平晶粒厚度变薄，尺寸趋于均匀。用少体物理理论，探讨了磁场对含稀土合金原子扩散过程的影响，为进一步研究稀土元素在磁场中的行为及其局域效应提供了一定的实验依据。     

高纯氧化镝电感耦合等离子体原子发射光谱法摄谱分析时光谱干扰校正方法的研究

本文建立了高纯氧化镝样品ICP摄谱分析时干扰系数法校正光谱干扰的方法。测定了镝基体对14种稀土杂质元素20条灵敏分析线的干扰系数(KCT)。并有效地校正了镝基体造成的光谱干扰,获得满意的结果。     

Approximation of titration curves and other sigmoidal functions by proportionally spaced cubic B-splines

Proportionally spaced cubicB-splines are an appropriate function system for the approximation of titration curves and other sigmoidal functions. They give a smooth weighted leastsquares fit without instability problems. The degree of smoothing depends only on the number of spline function which can be chosen by the user. The equivalence points of titration curves can be estimated with high accuracy from the zeros of the second derivative.The method gives good approximation curves even in the case of empty data regions, i. e. there are no artefacts in subranges where no data points exist. The routine has been tested successfully with large series of simulated and experimental data.     

Error estimation in peak‐shape analysis of XPS core‐level spectra using UNIFIT 2003: how significant are the results of peak fits?

An error analysis for numerically evaluating random uncertainties in x‐ray photoelectron spectroscopy has been implemented in version 2003 of the spectra treatment and analysis software UNIFIT in order to improve the understanding of the statistical basis and the reliability of the model parameters for photoelectron spectra. The theoretical basis as well as two approaches to obtain error limits of the fit parameters have been considered. Several test spectra have been analysed and discussed. A representative example has been chosen to demonstrate the relevance of the error estimation for practical surface analysis. Suggestions for the minimization of errors in the peak‐fitting procedures are presented. Copyright © 2004 John Wiley & Sons, Ltd.     

Component reconstruction in the primary space of spectra and concentrations. Alternating regression and related direct methods

A set of methods that extract the spectral components in a chromatographic run is considered. The methods do not need libraries of previously known spectra or retention times. The methods have been developed for two-dimensional spectra but they can also be used for chromatographic analyses with a single-channel detector. The methods are direct; they do not use principal components as the starting point. Alternating regression (AR) remains in the primary space of spectra and concentrations during the calculations. Random numbers are used as the starting spectra. Regression is used to solve first for the concentrations, then for the spectra. The method uses two kinds of constraints: all spectra and concentrations are forced to be positive; and all concentration profiles are forced to a unimodal shape with a single local maximum. It is assumed that all observations are a linear sum of components. Compact alternating regression (CAR) is a new variant of the basic AR. The idea is to replace multiplication of a large matrix by two multiplications of smaller matrices. This typically speeds up the iterations by a factor of ten. AR and CAR have been successfully used with combined techniques such as gas chromatography—mass spectrometry and liquid chromatography with UV—visible detection. The reliability of the solution is checked by repeatedly injecting noise and performing the analysis several times. This produces estimates of confidence intervals. AR and CAR have recently been extended to handle single-dimensional signals. Examples are single-channel detectors such as the flame ionization detector in gas or liquid chromatography with a fixed-wavelength UV detector. A batch of samples is used as the observation matrix. As a result, one obtains both the concentrations and the elution shapes of individual chromatographic peaks.