Two-dimensional correlation spectroscopy has been a successful tool in examining chemical phenomena for decades. Since 1976, this method has proven its capability many times. A lot of useful information has been revealed about a number of molecules: from simple molecules thru polymers to large biomolecules by this technique. It can be applied to several measurement systems. Although basically spectroscopic data is used such as NMR, IR, NIR, FT-IR, Raman, UV-VIS, X-ray, fluorescence or mass spectrometry. Despite its wide range of applications, it has not gained popularity in chromatography. There are only a few studies in this area and most of these publications report about gel chromatography or use a unique technique in two-dimensional correlation spectroscopy called sample-sample correlation.

In the present study we introduce a computational tool, which can be used to analyze the similarities and differences simultaneously in numerous chromatograms. In our experiments we examine the applicability of the algorithm used in spectroscopy for analyzing chromatograms. Two-dimensional correlation can be applied for the evaluation of a number of chromatographic data. We present the properties of the two-dimensional spectra, that is how the spectra respond to the changes in the chromatograms. And last, we demonstrate by a measurement comparing HPLC columns how this method can be used in practice.