Application of Raman dispersion spectroscopy in 3‐way multivariate data analysis

Abstract

AbstractIn this paper a new application of Raman dispersion spectroscopy (RADIS) is proposed, namely as a source of 3‐way data in multivariate analysis of classification problems, i.e. problems where different molecular species are identified in a number of samples. Owing to the coherent nature of the absorption–emission sequence in the Raman process, the unpolarized data generated by RADIS are born as 3‐way multivariate data. To demonstrate the potential of RADIS, a series of classification problems have been constructed and analyzed. By using computer‐simulated Raman and RADIS data it is shown that the 3‐way RADIS data obtained from very few samples, using only a few laser frequencies and a few Raman bands, can in general provide highly reliable results in classification problems without any a priori knowledge about the number of different molecular species in the samples. Quantitative comparisons have been made between a principal component analysis (PCA) of the 2‐way Raman data and a Tucker 3 analysis of the corresponding 3‐way RADIS data. It is found that the 3‐way RADIS data will give rise to a recognition ratio equal to 100% even in the worst case where no conclusions about the number of different molecular species in the samples can be drawn from the PCA of the 2‐way Raman data. It is shown that only the raw RADIS data are needed for the multivariate analysis, so that the use of internal standards, corrections for self‐absorption and other corrections necessary in molecular dynamics problems can be avoided. The results do not depend very much on the particular excitation wavenumbers used. Furthermore in most cases the fluorescence background does not influence the results. These facts together with the increased availability of solid state lasers with a variety of wavenumbers makes it easy to implement the proposed application of RADIS in practice. Copyright © 2007 John Wiley & Sons, Ltd.