Automated curve resolution applied to data from multi-detection instruments Original Research Article

This work presents a method for automated resolution of multicomponent data. The proposed procedures corrects background, cuts the data into smaller sub matrices, and resolves complex overlapping systems without human intervention. Basic constraints on concentration and spectral profiles are defined and used for determining the number of components and for cutting complex peak clusters into smaller sub matrices. The procedures are applied to multicomponent data from high performance liquid chromatography with diode array detection (HPLC-DAD), flow injection analysis with diode array detection (FIA-DAD), and gas chromatography–mass spectrometry (GC–MS).