用改进的矩阵法作多组份分光光度分析

近年来对于多组分混合物的同时测定已有一些报导。我们在此基础上,提出在紫外光谱的多组份体系分析中采用改进的矩阵解法,并用微型计算机进行计算,并通过对结果及适用特点等方面与其它方法作了初步比较和评述。     

主成份分析法测定多组份体系

主成份分析法同多元线性回归法、因子分析法^[1],偏最小二乘法^[2]等都是对多组份体系进行仪器分析信号解析的分析方法,该法的特点是能将维数较大的数据矩阵降维,而保留其全部有效信息,Geladi等给出了确定主成份的方法^[3],但利用主成份对未知混合物试样进行浓度测定的报道尚不多见,本文以主成份分析法对光度法多组份体系进行了研究,采用迭代法求出各个主成份向量,利用所建立的数学模型对未知样品进行浓度测定,方法较简便。     

吸光度减技术在混合物分析中的应用

混合物的光谱是其组份光谱的叠加,直接对它进行解析是十分困难的,所以光谱工作者要在化学分离上耗费大量精力。富里埃变换红外光谱仪及其它计算机化的红外光谱仪器具有被称为吸光度减的功能,可用以进行光谱之间的带权相减。它在一定程度上代替了化学分离,把各组份的光谱从混合物光谱中一一“剥离”开来。此技术可广泛用于混合物分析和涉及混合物的研究工作。Koenig曾对此技术的应用作过     

轻稀土元素La、Pr、Nd、Sm的同时光度法测定

本文提出以各因素同时改进的因素轮换法来处理多组份混合物溶液的吸收光谱,方法能对任一组份加以任意的约束,因而适用于“病态体系”。用两种显色体系的数据联合解矛盾方程,进行La、Pr、Nd、Sm四组份的同时测定,计算得到满意的结果。     

偏最小二乘法及主组分回归法用于药物组分的测定

本文研究了多元校准方法——偏最小二乘法(PLS)和主组份回归法(PCR)在药物多组份光度分析中的应用,获得了较满意的结果。而且在系列校准样品的实验设计、交叉证实法确定最佳因子数以及空缺组份体系的分析等方面进行了探讨。     

用因子分析-光度法测定混合物的组份

在进行多组份的光度分析时,各组份间的干扰经常发生。至今除研制高选择性的显色剂外,利用计算数学的方法,也是解决该课题的一个有发展前途的方向。国内外已报导过的方法有:解联立方程、最小二乘、线性回归、线性规划等,近年来这方面的工作逐年增多,计算数学的方法是应用合宜的模型来解析混合物的测定数值,进而确定各组份的种类及含量。当组份数目及样品量越大,该法的优点亦越突出。     

因子分析—伏安法同时测定波峰重叠的混合物组份

本文将目标因子分析用于伏安分析法同时测定波峰重叠的混合物组份。用此法对Ｐｂ（Ⅱ）、Ｔｌ（Ｉ）混合体系的导数脉冲伏安重叠峰数据进行解析，获得了较理想的结果。     

多元分辨校正模型与方法研究—无机多组份分析

系统研究了各种多元分辨校正模型、方法及其应用，以模拟体系、病态体系有态体系为对象，考察了它们的多元校正能力与多元分辨效果，给我机多组份分析态体系实例。     

四组份混合物分离提纯方案的设计与实践

四组份混合物分离提纯方案的设计与实践张本才（陕西师范大学化学系，西安７１００６２）混合物的分离提纯是有机化学各个研究领域都不可缺少的内容，并且往往是能否获得研究成果的关键步骤。因此，在大学学习有机化学实验期间，如何精选合适的混合物分离提纯实验，培养学...     

大豆异黄酮的LC-MS分析

大豆异黄酮是从大豆中提取的1种天然异黄酮类混合物,具有抗氧化及抗癌作用,长期服用不仅能降低胆固醇,减少心脏病的发生,而且可以降低癌症的发病率[1,2].此外,大豆异黄酮还具有内分泌调节功能,用于缓解妇女更年期症状.随着人们保健意识的加强,大豆异黄酮将成为医药、保健、食物等方面多功能产品.由于其组份多,缺少标准对照物质,定性定量分析该类化合物比较困难.文献报导[3]的方法只分析了其中的几个组份,我们采用LC-MS方法,首次同时分析了大豆异黄酮中的12个成分,并用归一化法测定了各组份的相对含量,为控制该产品的质量提供了可靠的分析手段.     

On-line fermentation gas analysis: Error analysis and application of mass spectrometry

On-line fermentation gas analysis is of general interest because it permits the determination of metabolic rates in almost any biological process using living organisms. The consumption and production of gases (O₂, CO₂, CH₄, etc.) and volatile compounds may be determined without causing any risk of infection. Elemental balancing permits the determination of other metabolic rates if the stoichiometry is known. This was studied with the production of poly-β-hydroxybutyrate (PHB) by Alcaligenes latus. Estimations were based on the measurement of gas partial pressure and flow-rates, pH and alkali consumption rate. Experiments with a small quadrupole mass spectrometer showed unacceptable error propagation. Therefore, dynamic error propagation for all rates was studied using simulation. It was found that, for example, a 1% relative offset-calibration error for oxygen can result in an error in PHB estimation of > 50%. It is suggested that this culture is used in combination with elemental balancing for thorough tests of the accuracy of on-line gas analysis equipment. An on-line process gas analyser based on a quadrupole mass spectrometer (Balzers PGM 407) gave the following precision values (abs. vol.?%) during cultivation of Bacillus subtilis: nitrogen (m/z 14), 0.024; oxygen (m/z 32), 0.020; argon (m/z 40), 0.0011; and carbon dioxide (m/z 44), 0.0034. These values, combined with automatic recalibration, would be sufficient for reasonable estimation of PHB, biomass and substrates.     

Impact of alkali treatment on physico-chemical,thermal, structural and tensile properties of Carica papaya bark fibers

This study aims to examine the effect of sodium hydroxide (NaOH) treatment on the physico-chemical properties, structure, thermal, tensile and surface topography of Carica papaya fibers (CPFs). The surface of raw CPFs was modified by soaking with 5% NaOH solution for 15, 30, 45, 60, 75 and 90?min. The results of thermo-gravimetric analysis revealed that the optimum treatment time for alkali treatment was 60?min. It was found that the alkali treatment improved the properties of the CPFs. The results of TGA, FT-IR, XRD and AFM suggest that the treated CPF is a suitable alternative as reinforcement in polymer composites.     

Chemometric and trend analysis of water quality of the South Chennai lakes: an integrated environmental study

In order to bring out the nature of the factors influencing lake water composition, multivariate statistical analysis and trend analysis were performed based on the hydrochemical data of the study area, namely, South Chennai. Change in land use pattern and settlements along the banks of the lakes alters the quality and quantity of the surface water. In the present study, the R‐mode factor analysis and cluster analysis were applied to the geochemical parameters of the water to identify the factors affecting the chemical composition of the lake water. Dendograms of both the seasons give three major clusters, reflecting the groups of unpolluted to moderately polluted, polluted, and heavily polluted stations. The movement of stations from one cluster to another clearly brings out the seasonal variation in the chemical composition of the lake water. The complex hydrochemical data of the surface water were interpreted by condensing them into three major factors. Factor score analysis was used successfully to delineate the stations under study and the role of the contributing factors, and the nature of factors responsible for the variation in chemical composition of the water has been clearly brought out. Results of trend analysis using ArcGIS clearly indicate that the trend in water quality is deteriorating at a faster rate in the eastern part of the study area. It is understood that although natural shifts probably can account for some of the variation, it is most likely that human activities play a major role in affecting the water quality on a regional scale. Copyright © 2014 John Wiley & Sons, Ltd.     

新材料的发展与分析化学

文章介绍了新材料的重要性及发展方向,分析化学在新材料研制中起着耳目的作用,另一方面新材料也为分析化学的进展提供了课题与条件。微量分析、微区分析、表面分析是此领域中的重点。在未来的发展中,分析化学在材料的发展中的地位不会改变,并期待着分析灵敏度与空间分辩率的进一步提高。     

Time-series analysis in analytical process control

Analysis of time series tries to extract tendencies from measured values dependent on time. For this purpose the cusum technique has proved to be a very sensitive tool for the evaluation of both current and completed time series. Even very weak tendencies can be detected at a high level of noise. Time-series analysis further tries to predict values to come from hitherto performed measurements. As a very flexible model exponential smoothing could be successfully used. Even for processes with a high extent of non-stationarity this model allowed a good prediction owing to the dynamics of the process. Three types of time-series analysis, i.e., evaluation of current measurements, retrospective evaluation and prediction of data (also known as “in vivo”, “post mortem” and “in futurum” time-series analysis) are demonstrated for problems stemming from analytical process control.     

Determination of rank by augmentation (DRAUG)

Determining the rank of a chemical matrix is the first step in many multivariate, chemometric studies. Rank is defined as the minimum number of linearly independent factors after deletion of factors that contribute to random, nonlinear, uncorrelated errors. Adding a matrix of rank 1 to a data matrix not only increases the rank by one unit but also perturbs the primary factor axes, having little effect on the secondary axes associated with the random errors in the measurements. The primary rank of a data matrix can be determined by comparing the residual variances obtained from principal component analysis (PCA) of the original data matrix to those obtained from an augmented matrix. The ratio of the residual variances between adjacent factor levels represents a Fisher ratio that can be used to distinguish the primary factors (chemical as well as instrumental factors) from the secondary factors (experimental errors). The results gleaned from model studies as well as those from experimental studies are used to illustrate the efficacy of the proposed methodology. The method is independent of the nature of the error distribution. Limitations and precautions are discussed. An algorithm, written in MATLAB format, is included. Copyright © 2011 John Wiley & Sons, Ltd.     

Determination of Mercury in Geological Materials by Continuous-Flow,Cold-Vapor,Atomic Absorption Spectrophotometry

Abstract

To determine mercury in geological materials, samples are digested with nitric acid and sodium dichromate in a closed teflon vessel. After bringing to a constant weight, the digest is mixed with air and a sodium chloride-hydroxylamine hydrochloride-sulfuric acid solution and then Hg(II) is reduced to Hg with stannous chloride in a continuous flow manifold. The mercury vapor is then separated and measured using cold vapor atomic absorption spectrophotometry (CV-AAS). For a 100 mg sample the limit of detection is 20 parts per billion (ppb) Hg in sample. To obtain a 1% absorption signal, the described method requires 0.21 ppb Hg solution (equal to 16 ppb in sample). Precision is acceptable at less than 1.2% RSD for a 10 ppb Hg aqueous standard. Accuracy is demonstrated by the results of the analysis of standard reference materials. Several elements do interfere but the effect is minimal because either the digestion procedure does not dissolve them (e.g., Au or Pt) or the; are normally of low abundance (e.g., Se or Te).     

A Tin(II) Chloride Based Reduction Method for Multiple-Metal Trace Analysis of Natural Waters

Based on tin(II) chloride reduction in basic medium, a method of general use is proposed for the estimation of the whole gamut of multiple trace metals in natural waters by the atomic absorption method. The quantitative aspects of the method related to variables such as pH of the medium, amount of reductant and operational conditions are studied as a function of absorption sensitivity. The proposed method utilizes only a 50.0 ml portion of the water sample and yields above 90 per cent recoveries for various metals from a single aliquot of the sample. The reported data pertain to the estimation of silver, chromium, copper, iron, lead, mercury, manganese, magnesium, nickel and strontium, reported as averaged over replicate measurements at +-2S confidence level. The precision in individual cases is found to be better than +1.8%.