Second-order advantage in determining Co (II) in real samples using kinetic-spectrophotometric data matrices and multivariate curve resolution-alternating least square approach

Abstract

In the present study, multivariate curve resolution coupled to alternating least-squares (MCR-ALS) was used to analyze kinetic-spectroscopic second-order data. The purpose of the study was to achieve important sec ond-order advantage under the conditions of extreme spectral overlapping among sample components. The obtained experimental data indicated that MCR-ALS, unlike other second-order multivariate calibration algorithms, can conveniently handle the investigated analytical problem provided that matrix augmentation is implemented in the spectral mode instead of the usual kinetic mode. In this work, row-wise augmentation was used to break rank deficiency under conditions of extreme spectral overlapping among sample components. The approach was applied to determine Cobalt (II) based on its oxidation reaction with Fe (III) and 1, 10-phenantroline in micellar media. The results indicated good analytical performance toward the analyte despite the intense spectral overlapping and the presence of unexpected constituents in the test samples. The maximum and minimum band boundaries of feasible solutions corresponding to the species profiles were estimated by multivariate curve resolution. The results of the study indicated that unique solution can be practically obtained using MCR-ALS under the selection of suitable constraints such as trilinearity.