光泽精与钨（Ⅲ）的流动注射－胶束增敏化学发光反应

采用了Jones柱在线还原钨（Ⅵ）为钨（Ⅲ），详细研究了钨（Ⅲ）与光泽精的化学发光反应，加入乳化剂OP能明显提高发光的信噪比，基于此建立了痕量钨的流动注射化学发光分析法。该法线性范围为1×10－6～1×10－2 g·L－1, 检出限为5×10－7 g·L－1 , 相对标准偏差为2.0％（5×10－5 g·L－1, n=11）。文中还探讨了反应机理。     

吐温—80固相化学发光测定痕量金的研究及其应用

研究了吐味－８０与Ａｎ（Ⅲ）的因相化学发光反应。比较了其在不同固相上的反应情况，用自制的固相化学发光仪，以巯基泡沫塑料（ＳＰＦ）吸附溶液中Ａｕ（Ⅲ），采用圆表制片直接在ＳＰＦ表面进行化学发光测定，建立了痕量金的固相化学发光分析法。方法的线性范围为０．０１－１０μｇＡｕ（Ⅲ），对１．０μｇ（Ⅲ）测定１１次的相对标准偏差为４．２％，用于实际矿样痕量金的测定，结果满意。     

鲁米诺化学发光熄灭法测定铕

研究了Ｅｕ（Ⅲ）对Ｌｕｍｉｎｏｌ－Ｈ２Ｏ２－Ｃｒ（Ⅲ）体系化学发光的熄灭效应,在此基础上建立了铕的流动注射化学发光分析法。分析灵敏度高,线性范围宽,仪器设备简单,操作方便。     

稀土Yb(Ⅲ)对Luminol-H2O2-Cr(Ⅲ)体系的化学发光熄灭效应

研究了稀土Ｙｂ（Ⅲ）对Ｌｕｍｉｎｏｌ－Ｈ２Ｏ２－Ｃｒ（Ⅲ）体系化学发光的熄灭效应，在此基础上建立了稀土Ｙｂ的流动注射化学发光分析法。该法灵敏度高，线性范围宽，仪器设备简单，操作方便     

流动注射无机偶合化学发光测定水样中痕量锑

在碱性条件下,锑（Ⅲ）还原重铬酸钾产生铬（Ⅲ）,该反应与鲁米诺-过氧化氢-铬（Ⅲ）化学发光体系相偶合,并应用流动注射和巯基棉分离干扰技术,建立了测锑的新方法。线性范围为0.1-100μg/L,检出限为0.03μg/L,对1.0μg/L的锑（Ⅲ）标准溶液连续11次测定的相对标准偏差为2.0%。方法可用于环境水样分析。     

还原剂与鲁米诺化学发光反应的研究（Ⅳ）──痕量铀的流动注射－化学发光测定

本文利用流动注射系统研究了由Ｊｏｎｅｓ柱产生的铀（Ⅲ）与鲁米诺之间的化学发光反应，建立了痕量铀的化学发光测定法。方法的检出限是３×１０￣（－１０）ｇ／ｍＬ铀。校准曲线的线性范围是１×１０￣（－９）～４×１０￣（－６）ｇ／ｍＬ铀，相对标准偏差为２％（测定２×１０￣（－９）ｇ／ｍＬ铀，ｎ＝１１）。对于反应机理进行了初步研究。     

测定核黄素的化学发光新方法

研究了核黄素的化学发光性质，建立了一种测定核黄素的化学发光新方法，并应用于实际样品中核黄素的测定，与文献相比，本方法无需避光，而且分析体系和样品处理简单；干扰小，牛血清白蛋白、抗坏血酸、天冬氨酸等８种生物有机物质和 Ｃｕ（Ⅱ）、Ｚｎ（Ⅱ）、Ｆｅ（Ⅲ）等１５种常见金属离子的允许量较大；核黄素溶液浓度在０． １０～５０ ｍｇ／Ｌ范围内，与化学发光强度成正比，方法线性范围宽；测定１．０ｍｇ／Ｌ核黄素溶液１２次，求得相对标准偏差为２．９％，方法精密度高；方法的检测限为０．０７５ ｍｇ／Ｌ，灵敏度高。     

流动注射-胶束增敏-光泽精与铁(Ⅱ)化学发光反应的研究

采用Ｊｏｎｅｓ柱在线还原铁（Ⅲ）为铁（Ⅱ），研究了铁（Ⅱ）与光泽精的化学发光反应，加 入ＣＴＭＡＢ和乳化剂ＯＰ能明显提高发光的信噪比，基于此建立了痕量铁的流动注射化学发光 分析法。此法线性范围为 １×１０－１１～ １×１０－５ｇ／ｍＬ，检出限为 ２×１０－１２ｇ／ｍＬ，相对标准偏差为 ２．０％（１×１０－８ｇ／ｍＬ，ｎ＝１１），已用于人发中铁的测定。深入探讨了反应机理。     

流动注射胶束增敏光泽精化学发光法测定谷物中Fe(Ⅲ)

用流动注射胶束增敏光泽精化学发光法测定谷物中Ｆｅ（Ⅲ）,其结果与原子吸收法相当吻合,该法仪器设备简单,操作方便。     

利用巯基棉集分离和鲁米诺—过氧化氢—铬（Ⅲ）：化学发光体系测定水…

本文提出了用鲁米诺－过氧化氢－铬（Ⅲ）化学发光体系结合巯基棉对Ａｓ（Ⅲ）的分离，建立了快速简单的测定水样中痕量砷的新方法。     

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.     

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.     

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。     

Automatic window factor analysis—A more efficient method for determining concentration profiles from evolutionary spectra

An algorithm called automatic window factor analysis (AUTOWFA) is developed for the purpose of determining, efficiently and automatically, the concentration profiles of the spectroscopically active components present in evolutionary processes, such as chemical titration, chromatography and kinetics. The method not only yields windows and profiles in agreement with those reported in the literature, but also reveals components not detected by precursor techniques. The method, however, has not been optimized and may require user interaction to fine-tune the windows.     

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).