Parametric signal fitting by gaussian peak adjustment: A new multivariate curve resolution method for non-bilinear voltammetric measurements Original Research Article

A new methodology based on the fitting of signals to parametric functions is proposed for the multivariate curve resolution (MCR) analysis of overlapping and peak-shaped voltammetric signals which progressively get broader or narrower and move along the potential axis, thus causing a dramatic loss of linearity. The method is based on the least squares fitting of gaussian functions at both sides of the peaks by using adjustable parameters for the peak height, position and symmetry. It consists of several home-made programs written in Matlab environment, which are freely available as supplementary material of the present work. The application to the systems Zn(II)–oxalate, and to the phytochelatin PC5 in a wide pH range provides excellent results as compared to these of more conventional linear methods, which raises good expectations about future application to electrochemical and even non-electrochemical data.