A novel strategy on the spectrochromatographic analysis of a quaternary mixture by parallel factor analysis model

Abstract

Poor chromatographic resolution is one of the main challenges in chromatographic analysis. Partially separated chromatographic peaks frequently occur, due to the nature of analytes and the demand for fast analysis using high flow rates and shorter columns. Modeling of chromatographic three-way data using suitable chemometric tools enables determining co-eluted peaks without using additional experimental efforts. In this paper, parallel factor analysis (PARAFAC) was applied to chromatographic data for the quantitative resolution of a quaternary mixture at the co-elution condition of acetaminophen, aspirin, ascorbic acid, and guaifenesin in a spectrochromatogram. The spectrochromatograms of the calibration set, validation set, and real samples were arranged as a three-way array. In the next step, the PARAFAC model was implemented to decompose the spectrochromatographic array into trilinear components, corresponding to spectral, chromatographic, and relative concentration profiles of the analytes. The chromatographic and spectral modes were used for the qualitative analysis of components, whereas the analytes in commercial tablets were quantified from their individual profiles in their concentration mode. This study indicated that the application of the PARAFAC model provided a novel strategy for determining overlapping peaks in a chromatogram to perform the analysis of multicomponent mixtures with reduced runtime and without additional efforts.