Application of a Partial Least Squares Regression for the Determination of Nanomolar Concentrations of Scandium in the Presence of Nickel by Adsorptive Stripping Voltammetry

Abstract

AbstractThis paper presents the methodology of a very sensitive determination of scandium in excess of nickel by adsorptive stripping voltammetry on a mercury film electrode and PLS regression. A calibration set consisting of binary mixtures containing 5, 15, 25, 35 or 45×10−9 M Sc(III) and simultaneously 0.5–50×10−7 M of Ni(II) was used to develop the chemometric PLS calibrations. An external set containing synthetic mixtures of 10, 20, 30, 40×10−9 M Sc(III) and the same Ni(II) concentration as mentioned above was used to validate the model and evaluate predictive ability. The application of data pretreatment techniques involving baseline correction, smoothing, range‐scaling, mean‐centering and their influence on the PLS model complexity, were also investigated. In the effect, the model for Sc(III), including 6 latent variables, was constructed. The model fulfills validation criteria and is characterized by a good prediction ability (majority of the prediction errors are lower than 10%). This work shows significant progress in the development of a very sensitive analytical technique for the determination of scandium in the presence of different concentrations of nickel by application of multivariate calibration tools.