Suppr超能文献

复杂混合物中化合物同系物的鉴定与定量:气相色谱/质谱色谱图的自协方差研究

Identification and quantification of homologous series of compound in complex mixtures: autocovariance study of GC/MS chromatograms.

作者信息

Pietrogrande Maria Chiara, Zampolli Maria Grazia, Dondi Francesco

机构信息

Department of Chemistry, University of Ferrara, Via L. Borsari, 46, 44100 Ferrara, Italy.

出版信息

Anal Chem. 2006 Apr 15;78(8):2579-92. doi: 10.1021/ac051491e.

Abstract

The paper describes a method for determining homologous classes of compounds in a multicomponent complex chromatogram obtained under programming elution conditions. The method is based on the computation of the autocovariance function of the experimental chromatogram (EACVF). The EACVF plot, if properly interpreted, can be regarded as a "class chromatogram" i.e., a virtual chromatogram formed by peaks whose positions and heights allow identification and quantification of the different homologous series, even if they are embedded in a random complex chromatogram. Theoretical models were developed to describe complex chromatograms displaying random retention pattern, ordered sequences or a combination of them. On the basis of theoretical autocovariance function, the properties of the chromatogram can be experimentally evaluated, under well-defined conditions: in particular, the two components of the chromatogram, ordered and random, can be identified. Moreover, the total number of single components (SCs) and the separated number of the SCs belonging to the random and ordered components can be determined, when the two components display the same concentration. If the mixture contains several homologous series with common frequency and different phase values, the number and identity of the different homologous series as well as the number of SCs belonging to each of them can be evaluated. Moreover, the power of the EACVF method can be magnified by applying it to the single ion monitoring (SIM) signals to selectively detect specific compound classes in order to identify the different homologous series. By this way, a full "decoding" of the complex multicomponent chromatogram is achieved. The method was validated on synthetic mixtures containing known amount of SCs belonging to homologous series of hydrocarbon, alcohols, ketones, and aromatic compounds in addition to other not structurally related SCs. The method was applied to both the total ion monitoring (TIC) and the SIM signals, to describe step by step the essence of the procedure. Moreover, the systematic use of both SIM and TIC can simplify the decoding procedure of complex chromatograms by singling out only specific compound classes or by confirming the identification of the different homologous series. The method was further applied to a sample containing unknown number of compounds and homologous series (a petroleum benzin, bp 140-160 degrees C): the results obtained were meaningful in terms of both the identified number of components and identified homologous series.

摘要

本文描述了一种用于确定在程序洗脱条件下获得的多组分复杂色谱图中化合物同系物类别的方法。该方法基于实验色谱图自协方差函数(EACVF)的计算。如果对EACVF图进行恰当解读,它可被视为一张“类别色谱图”,即由一些峰形成的虚拟色谱图,这些峰的位置和高度能够对不同的同系物系列进行鉴定和定量,即便它们包含在一张随机的复杂色谱图中。已开发出理论模型来描述呈现随机保留模式、有序序列或二者组合的复杂色谱图。基于理论自协方差函数,可在明确的条件下通过实验评估色谱图的性质:特别是能够识别色谱图的两个组成部分,即有序部分和随机部分。此外,当这两个部分具有相同浓度时,可确定单一组分(SC)的总数以及属于随机和有序部分的SC的分离数量。如果混合物包含几个具有相同频率和不同相位值的同系物系列,则可评估不同同系物系列的数量和特性以及属于每个系列的SC的数量。此外,将EACVF方法应用于单离子监测(SIM)信号,以选择性地检测特定的化合物类别,从而识别不同的同系物系列,可增强该方法的效能。通过这种方式,可实现对复杂多组分色谱图的完整“解码”。该方法在含有已知量的属于烃、醇、酮和芳香化合物同系物系列的SC以及其他与结构无关的SC的合成混合物上得到了验证。该方法应用于总离子监测(TIC)和SIM信号,逐步描述了该程序的本质。此外,系统地使用SIM和TIC可通过仅挑选出特定的化合物类别或通过确认不同同系物系列的鉴定来简化复杂色谱图的解码程序。该方法进一步应用于一个含有未知数量化合物和同系物系列的样品(沸点为140 - 160℃的石油醚):就已鉴定的组分数量和已鉴定的同系物系列而言,所获得的结果具有意义。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验