流动注射分析

本文是《分析试验室》定期评述专号中“流动注射分析”课题的第二篇评述文章。它评述了1988年10月至1990年10月流动注射分析在我国的进展及国际上发展的新动向。内容包括:基础研究、实验装置与仪器、分光光度分析、原子光谱、电化学检测和化学发光分析、梯度技术与计算机方法等。     

电化学检测在流动注射分析中的应用

评述了近几年来电化学检测在流动注射分析中的应用，展望了流动注射电化学分析法的发展动向。     

岩石矿物分析

本文是《分析试验室》定期评述中“岩石矿物分析”的第五篇评述文章。它评述了１９９３年７月至１９９５年６月期间国内岩石矿物分析的发展概况。内容分概述、试样的前处理、重量法和滴定法、光度法、原子光谱分析法、电化学分析法、Ｘ射线荧光及电子探针法、色谱法及其它、流动注射分析法、物相分析、质量监控及标准物质和标准方法等１１个方面。引用文献４４５篇。     

岩石矿物分析

本文是《分析试验室》定期评述中“岩石矿物分析”第六篇评述文章评述了１９９５年７月至１９９７年６月期间国内岩石矿物分析的发展概况，内容分概述，试样的前处理，重量法和滴定法，光度法，原子发射光谱法，原子吸收光谱及原子荧光光谱法，电化学分析法，Ｘ射线荧光及微区分析法，色谱质谱与活化分析法，流动注射分析法，物相分析，标准物质和标准方法等１２个方面，引用文献４８１篇。     

流动注射化学发光分析研究与应用进展

评述近年来流动注射化学发光分析法的最新进展。总结了流动注射化学发光中重要的化学发光试剂及其相应的新发光体系,概述了流动注射化学发光分析与特定的检测技术、分离技术结合形成的分析体系及其应用。     

电化学分析

本文是《分析试验室》定期评述中“电化学分析”第二篇和“离子选择电极”第三篇评述文章,它第一次将上述两课题合并为“电化学分析”课题。它对1987～1990年间(其中离子选择电极为1989～1990年)国内电化学分析的进展作了全面评述。内容包括:基础理论研究、极谱与伏安分析、溶出分析、化学修饰电极、液-液界面电化学、色谱电化学与流动注射分析检测、光谱电化学、离子选择电极、库伦分析及其他分析方法     

流动注射分析法与多种仪器分析联用的进展

对流动注射分析法(FIA)与多种仪器分析方法,包括分光光度法、电感耦合等离子体原子发射光谱法(ICP-AES)、原子吸收光谱法(AAS)、化学发光法(CL)、荧光光度法、电化学分析法、生物传感器、毛细管电泳、免疫分析法等联用在最近两年中的新进展作了评述,引述文献42篇.     

无相分隔与/或无相分离的流动注射-液液萃取技术的进展

本文对无相分隔与 /或无相分离的流动注射 -液液萃取技术的进展作了回顾与评述。引用文献 32篇     

流动注射在线沉淀共沉淀预分离富集与原子光谱联用的进展

综述流动注射在线沉淀共沉淀预分离富集与原子光谱联用技术的进展.重点评述了流动注射在线沉淀预分离-火焰原子吸收间接法测定无机阴离子和有机化合物的方法和流动注射在线无滤共沉淀预富集-火焰或电热原子吸收法测定痕量金属离子的方法.共引用文献35篇.     

岩石矿物分析

本文是《分析试验室》定期评述中“岩石矿物分析”的第七篇评述文章。评述了 1 997年 7月至 1 999年 6月间国内岩石矿物分析的发展概况。内容分综述与会议、试样的前处理、重量法和滴定法、光度法、原子光谱分析法、电化学分析法、X射线荧光分析法、色谱、质谱及活化分析法、流动注射分析法、物相分析、标准物质和标准分析方法等几方面。引用文献 3 86篇。     

毛细管电泳的原理和应用(第六讲)CE在DNA、糖和离子分析中的应用

简要介绍了ＣＥ在ＤＮＡ、糖和离子分析中的应用。ＤＮＡ分析包括分离原理、方法及检测手段，碱基、核苷和核苷酸分析，纯度检测和微量制备，ｓｓＤＮＡ和ｄｓＤＮＡ分析，基因突变检测及ＤＮＡ序列分析等。糖分析包括衍生化技术、检测方法、所用模式及糖复合物的分析等。离子分析包括阴离子分析原理、检测方法、影响因素、应用及阳离子分析等。     

面向新世纪的冶金材料分析

21世纪冶金材料分析面临复杂体系中痕量元素分析、冶金材料原位分析以及在线实时分析等三大问题。本文对这三方面的发展趋势进行了评述。     

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。     

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.     

Approaches to bioresponse-linked instrumental analysis in water analysis

A new concept based on hyphenation of biotests, for biological selection, and chemical analysis is introduced for water analysis. Biomolecular recognition components such as receptors, enzymes, and nucleic acids integrated in biological reaction chains are used for binding and selective enrichment of known and unknown biologically active substances in water samples; this is followed by identification and quantitation. The coupling of biomolecular recognition and binding to chemical analysis can be achieved either in discrete analytical steps, e.g. binding and elution of bioactive ligands from affinity columns followed by chemical analysis, or by methods capable of monitoring the binding of the ligand and simultaneous verification of its identity. This analytical strategy, denoted bioresponse-linked instrumental analysis (BLIA), enables detection of potential biological effects and identification of the analyte causing these effects. Several examples are presented.     

顶空-气相色谱法进展

回顾了顶空采样气相色谱分析法在复杂基质中挥发性成分中的应用．总结并详述了顶空分析的三种重要模式-介绍了顶空分析的相关原理和整个顶空分析系统的参数优化过程．综述了顶空．气相色谱分析在生物样本中挥发性有机物的测定、药品中有机残留溶剂的检测、聚合材料中挥发性有机物的分析、环境中有害的有机挥发性物质分析、挥发油分析和烟草分析等方面的进展．     

Correlating detergent fiber analysis and dietary fiber analysis data for corn stover collected by NIRS

There exist large amounts of detergent fiber analysis data [neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL)] for many different potential cellulosic ethanol feedstocks, since these techniques are widely used for the analysis of forages. Researchers working in the area of cellulosic ethanol are interested in the structural carbohydrates in a feedstock (principally glucan and xylan), which are typically determined by acid hydrolysis of the structural fraction after multiple extractions of the biomass. These so-called dietary fiber analysis methods are significantly more involved than detergent fiber analysis methods. The purpose of this study was to determine whether it is feasible to correlate detergent fiber analysis values to glucan and xylan content determined by dietary fiber analysis methods for corn stover. In the detergent fiber analysis literature cellulose is often estimated as the difference between ADF and ADL, while hemicellulose is often estimated as the difference between NDF and ADF. Examination of a corn stover dataset containing both detergent fiber analysis data and dietary fiber analysis data predicted using near infrared spectroscopy shows that correlations between structural glucan measured using dietary fiber techniques and cellulose estimated using detergent techniques, and between structural xylan measured using dietary fiber techniques and hemicellulose estimated using detergent techniques are high, but are driven largely by the underlying correlation between total extractives measured by fiber analysis and NDF/ADF. That is, detergent analysis data is correlated to dietary fiber analysis data for structural carbohydrates, but only indirectly; the main correlation is between detergent analysis data and solvent extraction data produced during the dietary fiber analysis procedure.     

X射线荧光光谱法在稀土元素分析中的应用

本文研究了Ｘ射线荧光光谱在混合稀土氧化物和高纯稀土氧化物分析中的应用，并探讨了在常量分析中影响分析准确度和精密度的主要因素；样品及标样制备，基体效应校正方法在痕量分析中降低检测限的方法，选择最佳测量条件，降低背景，与分离富集手段相结合，取得满意的结果。     

Application of multivariate data-analysis techniques to biomedical diagnostics based on mid-infrared spectroscopy

The objective of this contribution is to review the application of advanced multivariate data-analysis techniques in the field of mid-infrared (MIR) spectroscopic biomedical diagnosis. MIR spectroscopy is a powerful chemical analysis tool for detecting biomedically relevant constituents such as DNA/RNA, proteins, carbohydrates, lipids, etc., and even diseases or disease progression that may induce changes in the chemical composition or structure of biological systems including cells, tissues, and bio-fluids. However, MIR spectra of multiple constituents are usually characterized by strongly overlapping spectral features reflecting the complexity of biological samples. Consequently, MIR spectra of biological samples are frequently difficult to interpret by simple data-analysis techniques. Hence, with increasing complexity of the sample matrix more sophisticated mathematical and statistical data analysis routines are required for deconvoluting spectroscopic data and for providing useful results from information-rich spectroscopic signals. A large body of work relates to the combination of multivariate data-analysis techniques with MIR spectroscopy, and has been applied by a variety of research groups to biomedically relevant areas such as cancer detection and analysis, artery diseases, biomarkers, and other pathologies. The reported results indeed reveal a promising perspective for more widespread application of multivariate data analysis in assisting MIR spectroscopy as a screening or diagnostic tool in biomedical research and clinical studies. While the authors do not mean to ignore any relevant contributions to biomedical analysis across the entire electromagnetic spectrum, they confine the discussion in this contribution to the mid-infrared spectral range as a potentially very useful, yet underutilized frequency region. Selected representative examples without claiming completeness will demonstrate a range of biomedical diagnostic applications with particular emphasis on the advantageous interaction between multivariate data analysis and MIR spectroscopy.     

我国化学物相分析的进展

对我国化学物相分析的最新成就和进展作了简要评述,内容包括概述、物质相态分析、元素赋存状态分析以及非金属矿物相分析等。引用近十年来的主要文献１００篇。