Application of multivariate curve resolution to the voltammetric data Factor analysis ambiguities in the study of weak consecutive complexation of metal ion with ligand

Abstract

Different techniques for factor analysis (FA) have been applied in the study of weak consecutive complexes of Cd(II) propanoate by analysing experimental matrices obtained from four electroanalytical techniques: normal pulse polarography (NPP), reverse normal pulse polarography (RNPP), differential pulse polarography (DPP) and differential pulse anodic stripping voltammetry (DPASV). All experiments were performed at a constant temperature, 25 ± 1 °C, in aqueous solutions having a constant cadmium ion concentration (10 and 20 μM), varying propanoate concentrations in the range 10–400 mM, a constant c(propanoic acid)-to- c(sodium propanoate) ratio (1: 50), and a constant ionic strength (2 M), obtained by addition of NaClO 4. From the experimental signals using DeFord and Hume's model, to calculate the experimental F 0 function model identification, β i estimates and corresponding standard error of stability constants were obtained using conventional fitting of polynomial (univariate hard modelling) to the experimental data, together with the recently proposed evolving polynomial fitting and optimized least squares extrapolation of F i functions. The same experimental data matrices were analysed by multivariate soft modelling approach using the following FA techniques: principal component analysis (PCA), evolving factor analysis (EFA) and constrained alternating least squares (ALS) optimization of individual and global (augmented) data matrices.