化学模式识别技术评价中药厚朴质量的研究

本文对不同产地和市售的二十四种厚朴药材及饮片的萃取液进行了高效液相色谱、气相色谱及紫外光谱分析;对所得数据用主成分分析进行分类,概括出不同样品化学成分的异同,认为大叶木兰可做为厚朴的代用品,而在陕西安康购得的样品不应做厚朴使用,后者经生药学鉴定为厚朴伪品凹叶木兰。化学模式识别技术可为寻找药材的代用品、评价中药质量及鉴定伪劣药材提供依据。     

Patterns in the precision of quantitative data from multicomponent gas chromatographic or gas chromatographic-mass spectrometric analysis

The dispersion of the quantitative results in the analysis of volatile compounds from multicomponent mixtures by different fractionation techniques (solid-phase microextraction and direct thermal desorption) followed by GC or GC-MS presents nonrandom patterns related to the existence of different factors in the fractionation process or in the chromatographic separation which affect, to a different extent, the recovery of the sample components. Statistical techniques have been used to show the relative importance of these factors. The improvement in data precision achieved by using volatile compound concentration ratios is discussed.     

SBS单组分橡胶防水涂料

探讨了SBS单组分橡胶防水涂料的组成、制备方法及其对性能的影响因素,详细地介绍了该涂料在防水工程应用上的两大独特优势:(1)优异的抗基层形变能力。这一优势,使其具备了屋面防水专用材料和特效材料的条件,解决了以往防水材料一直不能解决的“零点开裂”问题。(2)创造出多种复合防水工法,既克服和解决了卷材与涂料的各自缺点,又发挥了各自的优点,使这种复合防水层成为最有效的防水层。     

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．     

主成分回归-紫外光度法同时测定食用香料麦芽酚和乙基麦芽酚

报道了一种快速、简便的同时测定食用香料麦芽酚、乙基麦芽酚光度法,方法基于在pH2.87的B R缓冲溶液中对麦芽酚和乙基麦芽酚两组分混合溶液进行光度测定,所得的重叠波谱数据用主成分回归法(PCR)、经典最小二乘法(CLS)和偏最小二乘法(PLS)等化学计量学方法进行处理,结果表明主成分回归法(PCR)的预报误差最小。对样品进行测定,获得了较好的定量分析结果。麦芽酚和乙基麦芽酚的线性范围均为1.0～20.0mg·L-1;检出限分别为0.4347和0 5589mg·L-1。     

Modeling of the relationship between electroosmotic flow and separation parameters in capillary zone electrophoresis using artificial neural networks and experimental design

The prediction of migration time of electroosmotic flow (EOF) marker was achieved by applying artificial neural networks (ANN) model based on principal component analysis (PCA) and standard normal distribution simulation to the input variables. The voltage of performance, the temperature in the capillary, the pH and the ionic strength of background electrolytes (BGE) were applied as the input variables to ANN. The range of the performance voltage studied was from 15 to 27 kV, and that of the temperature in the capillary was from 20 to 30 °C. For the pH values studied, the range was from 5.15 to 8.04. The range of the ionic strength investigated in this paper was from 0.040 to 0.097. The prediction abilities of ANN with different pre-processing procedure to the input variables were compared. Under the same performance conditions, the average prediction error of the migration time of the EOF marker was 5.46% with RSD = 1.76% according to 10 parallel runs of the optimized ANN structure by the proposed approach, and that of the 10 parallel predictions of the optimal ANN structure for the different performance conditions was 12.95% with RSD = 2.29% according to the proposed approach. The study showed that the proposed method could give better predicted results than other approaches discussed.     

Combining synchronous fluorescence spectroscopy with multivariate methods for the analysis of petrol-kerosene mixtures

Synchronous fluorescence spectroscopy (SFS) is a rapid, sensitive and nondestructive method suitable for the analysis of multifluorophoric mixtures. The present study demonstrates the use of SFS and multivariate methods for the analysis of petroleum products which is a complex mixture of multiple fluorophores. Two multivariate techniques principal component regression (PCR) and partial least square regression (PLSR) have been successfully applied for the classification of petrol-kerosene mixtures. Calibration models were constructed using 35 samples and their validation was carried out with varying composition of petrol and kerosene in the calibration range. The results showed that the method could be used for the estimation of kerosene in kerosene-mixed petrol. The model was found to be sensitive, detecting even 1% contamination of kerosene in petrol.     

Chemical Constituents of the Essential Oil of <Emphasis Type="Italic">Nepeta oxyodonta</Emphasis>

Water-distilled essential oil from the aerial parts of Nepeta oxyodonta Boiss. was analyzed by GC/MS for the first time. Fifty-eight components were identified. The major components were (E)-caryophyllene (12.6%), spathulenol (8.5%), β-bourbonene (8.1%), germacrene-D (7.4%), α-cadinol (7.3%), germacrene-D-4-ol (6.8%), T-cadinol (5.6%), and caryophyllene oxide (5.3%).__________Published in Khimiya Prirodnykh Soedinenii, No. 2, pp. 141–142, March–April, 2005.     

Effect of the Measurement Temperature on the Dispersive Component of the Surface Free Energy of a Heat Treated SiO2 Xerogel

The surface free energy of a monolithic silica xerogel treated at 1000°C has been measured by inverse gas chromatography in the temperature range 25–150°C using n-alkanes. Values of the dispersive component, _S ^D, vary from 49.07 mJ·m^–2 at 25°C to 17.20 mJ·m^–2 at 150°C. The _S ^D value obtained at 25°C is lower than that found for amorphous and crystalline silicas but higher than that found for glass fibres meaning that the heat treatment at 1000°C changes drastically the structure of the silica xerogel showing a surface similar to a glass. However, the higher value of _S ^D in comparison to glass fibres can be attributed to the mesoporous structure present in the silica xerogel. In the temperature range of 60–90°C there exists an abrupt change of the _S ^D values as well as in the dispersive component of the surface enthalpy, h _S ^D. Such abrupt change can be attributed to an entropic contribution of the surface free energy.     

Rapid and sensitive method for determining free amino acids in honey by gas chromatography with flame ionization or mass spectrometric detection

This paper describes a rapid, sensitive and specific method for determination of free amino acids in honey involving a new reaction of derivatization and gas chromatography (GC) with flame ionization (FID) and mass spectrometric (MS) detection. The method allows the determination of 22 free amino acids in honey samples in a short time: 8 and 5 min for GC-FID and GC-MS, respectively. Quantitation was performed using Norvaline as internal standard, with detection limits ranging between 0.112 and 1.795 mg/L by GC-FID and between 0.001 and 0.291 mg/L by GC-MS in the selected-ion monitoring mode. The method was validated and applied to a set of 74 honey samples belonging to four different botanical origins: eucaliptus, rosemary, orange and heather. The statistical treatment of data shows a correct classification of different origins over 90%.