修正的Arrhenius方程与过渡状态理论

用过渡状态理论导出了修正的Arrhenius方程.该方程与Eyring方程是等价的,但仅适用于参数n为负数的情况.     

组合取样的误差理论研究及其Monte Carlo模拟

基于多项分布理论,建立了组合取样方差与取样总体中各子区的大小及其组分含量之间的关系和计算公式,探讨了组合取样常数的物理意义.以颗粒物质为例,探讨了组合取样的逻辑质量单元的概念及其意义,为确定组合取样中的份样质量提供了理论依据.本文对于完善组合取样误差理论,保证组合取样的质量均具有重要意义.     

Arrhenius活化能理论的修正

针对Arrhenius活化能理论的不足,修正了这个理论,建立了一个修正的Arrhenius方程,它能适用于更宽的温度范围。     

进口铜冶炼渣的取样及其分析试样的制备

针对大吨位量进口铜冶炼渣的不均匀性且有不能破碎的金属颗粒的存在,根据统计学及概率论的基础原理和实际经验提出了新的取样及制样方法,对整批铜冶炼渣渣料,以500t为一个取样单元,每个单元中取份样50～60个。根据渣料的粒径大小,决定每一份样的质量,粒径在20-50mm之间者,取份样量为4kg,粒径在10-20mm之间者,取份样量为2kg。将每一个取样单元所取的份样充分混合均匀作为副样,将每一副样进行粉碎,研磨并按需要多次缩分。收集在规定粒径条件下不能破碎的金属颗粒,并分别装在样袋中,另将通过100μm粒径的渣样收集于另一样袋,分别对不同样袋中铜,银,金的含量进行测定。按统计方法计算3元素的加权平均值,并最终得到整批渣料中上述3元素的含量。按所提出的方法,对两船进口的两批铜冶炼渣进行取样、制样并分析了其中铜、银及金的含量,所得结果与国外实验室的结果相吻合。     

取样量对润滑油中微量水分检测结果的影响

研究取样量对润滑油中微量水分测定结果的影响。基于卡尔·费休滴定法,在选定的测量条件下,用发生电极为有隔膜的自动库仑水分仪对基础油、有机热载体油、压缩机油、膨胀机油等新油和发动机油、汽轮机油、涡轮机油、压缩机油、齿轮油、液压油、导热油、船用油、电器绝缘油、风动工具油、金属加工油等在用油在0.1~2.0 g内各取9组不同质量的样品进行测定,得到了润滑油中微量水分准确测定所需的取样量。实验结果表明,新油取样量大于1.0 g,在用油取样量在1.0~1.5 g范围内,可以准确测定润滑油中微量水分含量。测定结果的相对标准偏差为0.83%~3.51%(n=10),样品加标回收率为95.0%~103.0%。在选择的取样量下,该方法具有良好的精密度、准确度,可连续测定多个样品,满足测定需求。     

世界采样大会的由来与Pierre Gy采样理论的发展

简单介绍了世界采样大会的由来与Pierre Gy采样理论的产生与发展。重点阐述了Pierre Gy公式和采样理论的涵义与应用,以及化学计量学对采样理论发展的推动和促进作用。同时,采样理论的发展也推动了过程分析技术的应用以及各类先进采样、制样和混样设备的研制和应用。中国作为全球最大的大宗商品进口国和消费国,对采样理论和实践应用有着迫切的需求,将第九届世界采样与混样大会引入中国,必将促进和提升我国采样理论的研究和实践水平,使其更好地为我国大宗商品交易和检验检测市场服务。     

世界采样大会的由来与Pierre Gy采样理论的发展

简单介绍了世界采样大会的由来与Pierre Gy采样理论的产生与发展。重点阐述了Pierre Gy公式和采样理论的涵义与应用,以及化学计量学对采样理论发展的推动和促进作用。同时,采样理论的发展也推动了过程分析技术的应用以及各类先进采样、制样和混样设备的研制和应用。中国作为全球最大的大宗商品进口国和消费国,对采样理论和实践应用有着迫切的需求,将第九届世界采样与混样大会引入中国,必将促进和提升我国采样理论的研究和实践水平,使其更好地为我国大宗商品交易和检验检测市场服务。     

物化实验教材中误差理论的不足

一些国内主要实验教材所编写的误差理论部分存在图象、数值分析和数据处理方面的种种疑问,可予证明。本文提出误差方程和几率误差作为误差计算和误差分析方面的补充。     

二元颗粒混合物按质量取样的误差研究

二元颗粒混合物的随机取样方式有两种：一是按颗粒数目取样,二是按质量取样本文对二元颗粒混合物按质量取样的误差进行了深入研究,详细分析了混合物的各种参对被测组分含量取样误差的影响,应用Ｍｏｎｔｅ Ｃａｒｌｏ技术对取样进行了模拟。以颗粒药品的二元混合物为例对按颗粒数目取样和按质量取样的误差进行了比较。此项研究对于分析取样理论和应用具有重要的价值。     

On the mechanisms of the reactions between some perfluorinated compounds and CH(5) (+) --experimental and theoretical approaches

Five perfluorocompounds [perfluoropentane, 4-(perfluoroethoxy)-perfluorobutane, 5-(perfluoroethyl)-perfluorotetrahydrofuran, 2-(trifluoromethyl)-perfluorotetrahydropyran, and 4-(trifluoromethyl)-perfluorotetrahydropyran] were analyzed by electron ionization (EI) and chemical ionization (CI), using methane and isobutane as reagent gases. Under CI conditions, isobutane does not lead to significative results whereas methane leads to high ionic yields [with respect to both CI (isobutane) and EI]. Under EI conditions, practically only fragment ions are observed, with the complete loss of molecular weight. In contrast under CI(CH(4) ) conditions, [M-F](+) ions are produced. Under these conditions, the behavior of oxygen-containing molecules is strongly different from that of perfluoropentane. This is because oxygen can greatly stabilize the formation of the [M-F](+) carbocation by a π-electron donor effect, especially in the case of cyclic structures. Moreover, π-stabilization can be considered a useful tool to rationalize the position of tertiary carbon atom in trifluoromethyl-perfluoro-pyrane isomeric ions. The experimental data formed the starting point for the theoretical calculation, which allowed us to explore the mechanisms of the reactions of CH(5) (+) ions with selected perfluorocompounds. The computational methods used show that a direct protonation of the perfluoroethers (PFEs) by CH(5) (+) as well as iBu(+) is very unlikely. In the theoretical calculations, the PFE molecule served rather as the F(-) donor, and the elimination of HF molecule occurred when the PFE molecule was placed close to H(+) or CH(5) (+) ions. The fact that the latter is very unstable and decomposes to a proton and methane molecule explains why the use of methane in CI is so successful in the generation of [M-F](+) ion. In contrast, the isobutonium cation rearranges to an isopropyl cation/methane complex rather than that it abstracts F(-) from the PFE molecule. Similar results can be expected for other PFEs and perfluoroalkanes (PFAs) because both CH(5) (+) and H(+) were able to abstract the HF molecule also by attacking along the perfluoroalkyl chain of the PFE.     

Sampling and analytical framework for routine environmental monitoring of organic pollutants

Dubious data would lead to incorrect interpretations and consequently faulty conclusions. Environmental monitoring results therefore have to be unambiguous to avoid misunderstanding the problems under investigation. Representative sampling and appropriate laboratory procedures are keys to acquiring quality data in order to draw unbiased conclusions.Although a large number of studies on organic pollutants have been published, few efforts have been directed towards instituting a systematic framework from sampling design to instrumental analysis. Generally, the main components in such a framework should include sampling design, sample preparation, sample extraction, extract purification and fractionation, and quantification (including qualitative and quantitative analyses).This review outlines the sampling and analytical framework appropriate for routine monitoring of organic pollutants, particularly persistent organic pollutants widely occurring in the environment. We emphasize statistically-based sampling schemes and quality-assurance and quality-control measures desirable for environmental monitoring programs.By way of demonstrating their importance, we especially review procedures for collecting unconventional environmental samples (e.g., human blood, breast milk, human hair, fish and bird tissues, and ice and snow) and analytical methods for typical emerging organic chemicals.     

探讨二元颗粒混合物取样误差的新的数学模型

采用新的数学模型研究二元颗粒混合物的取样误差,首次提出了取样的逻辑质量单元的理论,探讨了逻辑质量单元的物理意义,建立了按质量取样的标准偏差的计算公式.应用颗粒药品二元混合物的取样实验,证实了该公式的正确性.     

取样方差估计值的精度与样本数目之间的关系

通过数学推导建立了取样方差估计值的精度与样本数目之间的定量关系。实验也证明,取样方差估计值的标准偏差与样本数目的平方根之积可近似为一常数。应用蒙特卡罗技术模拟随机取样,对该关系式进行了验证,并探讨了取样方差估计值的分布规律,表明其规律对于组分含量服从正态分布,均匀随机分布及多项分布总体是相似的。     

计算机模拟地质化验室分样及取样常数Ks的估算

提出了计算机模拟地质化验室取样过程,考察取样误差与取样量、样品粒度之间关系,并估算取样常数.实验所得的误差与取样量之间的关系与Ingamells的取样方程一致,取样常数及取样常数和样品粒度关系式也与Ingamells推导的相符.由于计算机模拟是一颗颗取样,不用预设分布模式,不存在分析方法误差和分样操作误差的叠加,误差完...     

分层性物质的组合取样误差与份样数目之间的关系及其Monte Carlo模拟

本文从理论上研究了分层性物质的组合取样误差与份样数目之间的定量关系，表明份样数目与组合取样相对标准偏差的平方之积为一常数，称为组合取样常数，它与Ｉｎｇａｍ ｅｌｌｓ 和Ｓｗ ｉｔｚｅｒ 提出的取样常数是相似的，表示６８％ 置信度下组合取样的相对标准偏差达到１％ 时的份样数目。应用Ｍｏｎｔｅ Ｃａｒｌｏ 模拟技术对该理论进行了验证，结果令人满意。     

粒状物质的微观均匀度及其对取样误差的影响分析

研究物质的取样属性与以取样误差之间的关系是分析化学取样学的重要内容。从微观角度探讨了物质的理论性质及其对取样误差的影响。以碳化硅为例,考察了粒度分布、组分随粒度的变化以及均匀度因子等,分析了取样误差的来源。首次通过粒度分级成功地对碳化硅进行了分层,并对分层取样和随机取样的误差进行了分析和讨论,为制定合理的取样方案提供了有利的依据。本文的研究方法可适用于所有粒状物质的取样,同时也为分析化学取样学的深     

Detection of calcium phosphate crystals in the joint fluid of patients with osteoarthritis - analytical approaches and challenges

Clinically, osteoarthritis (OA) is characterised by joint pain, stiffness after immobility, limitation of movement and, in many cases, the presence of basic calcium phosphate (BCP) crystals in the joint fluid. The detection of BCP crystals in the synovial fluid of patients with OA is fraught with challenges due to the submicroscopic size of BCP, the complex nature of the matrix in which they are found and the fact that other crystals can co-exist with them in cases of mixed pathology. Routine analysis of joint crystals still relies almost exclusively on the use of optical microscopy, which has limited applicability for BCP crystal identification due to limited resolution and the inherent subjectivity of the technique. The purpose of this Critical Review is to present an overview of some of the main analytical tools employed in the detection of BCP to date and the potential of emerging technologies such as atomic force microscopy (AFM) and Raman microspectroscopy for this purpose.     

Detection limits and goodness-of-fit measures for the two-component model of chemical analytical error

The utility of analytical chemistry measurements in most applications is dependent on an assessment of measurement error. This paper demonstrates the use of a two-component error model in setting limits of detection and related concepts and introduces two goodness-of-fit statistics for assessing the appropriateness of the model for the data at hand. The model is applicable to analytical methods in which high concentrations are measured with approximately constant relative standard deviation. At low levels, the relative standard deviation cannot stay constant, since this implies vanishingly small absolute standard deviation. The two-component model has approximately constant standard deviation near zero concentration, and approximately constant relative standard deviation at high concentrations, a pattern that is frequently observed in practice. Here we discuss several important applications of the model to environmental monitoring and also introduce two goodness-of-fit statistics, to ascertain whether the data exhibit the error structure assumed by the model, as well as to look for problems with experimental design.