对聚合物混合物的谱库搜索结果列表进行多变量分析

Multivariate Analysis of a Hit List from a Spectral Search of a Polymer Mixture

Abstract

This application note describes a new method that combines cheminformatics tools with chemometrics tools for Principal Component  Analysis  (PCA)  in  an  intuitive  environment  for performing  multivariate  analyses  on  spectral  as  well  as chromatographic data.   A new patent-pending technology Overlap Density Heatmaps (ODHs) allows the comparative visualization of large datasets of spectra or chromatograms and are used for visual data mining and analysis to assess the similarities and dissimilarities in large amounts of spectral,chromatographic, and other graphical data.

Currently, the use of PCA to analyze and visualize spectral hit lists generated from searching one or more reference databases is not a widely known technique. However, as more case studies and applications are introduced, it is expected that this technique will rapidly become more commonplace in the laboratory.   In this case study, this new   approach for spectroscopic analysis will be examined as applied to polymeric IR data using a combination of PCA and ODH technologies to analyze a query and the hit list resulting from an IR spectral search and to perform an overall analysis of a database.

Conclusions

Principal Component Analysis (PCA) appears to be a valuable tool to analyze the results of standard spectral searches-a spectral query and hit list-providing useful insights into the nature of the compounds in the hit list relative to the query.

Overlap Density Heatmaps (ODHs) not only confirm the value of the  technique,  but  are  also  a  useful  complement  to  the multivariate processing capabilities afforded by PCA.   This technique  is  an  excellent  tool  to  identify  components  in mixtures and can be used effectively in the polymer industry to analyze polymeric samples. It is more precise than spectral subtraction, which performs the point-by-point subtraction of one spectrum from another, and it is especially useful when analyzing mixtures or composite spectra.