Decoding complex multicomponent chromatograms by Fourier Analysis
Decoding complex multicomponent chromatograms by Fourier Analysis
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DOI：
10.1007/bf02505597
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发表时间：
1997-01-01
期刊：
影响因子：
1.7
通讯作者：
Felinger, A
中科院分区：
文献类型：
--
作者：
Dondi, F;Pietrogrande, MC;Felinger, A
目前的工作讨论了许多属性-分类为可观察的，内在的或隐藏的-这可以设想为任何复杂的多组分色谱。讨论如何解码此类色谱图，即从可观察到的色谱图中确定固有和/或隐藏属性。有两个主要步骤。第一种是基于傅立叶分析（FA）并确定固有属性：即，可检测的单个组分的数量;它们在可用色谱空间和峰容量上的分布。第二个评估隐藏的属性：即，不完全分离的影响、由一种或多种单一组分产生的峰的数量以及它们的纯度。应用统计峰重叠度（SDO）理论可以得到隐含属性，并讨论了SDO步长对FA结果的依赖程度。此外，还讨论了指数分布对单组分峰位间距和峰高分布的参考作用。最后，提出了一个简化的图形FA程序，并在这一领域的主要成就进行了审查。
The present work discusses the many attributes - classified as observable, intrinsic or hidden - which can be conceived for any complex multicomponent chromatogram. Discussion ensues on how to decode such chromatograms, i.e. determining the intrinsic and/or hidden attributes from those which can be observed. There are two main steps. The first is based on Fourier Analysis (FA) and determines the intrinsic attributes: i.e., the number of single components which can be detected; their distribution over the available chromatographic space and peak capacity. The second evaluates the hid den attributes: i.e., the effects of incomplete separation, the number of peaks created by one or more single components as well as their degree of purity. The hidden attributes can be obtained by applying the theory of Statistical Degree of peak Overlapping (SDO) and the paper goes into the extent to which the SDO step depends on the FA results. In addition, the role Exponential distribution plays as a point of reference for the distribution of both single component peak position interdistances and peak heights is discussed. Finally, a simplified graphical FA procedure is presented and the main achievements in this field are reviewed.