Methodology of multicriteria optimization in chemical analysis Some applications in stripping voltammetry

Multicriteria optimization, widely used in engineering, does not much used in the optimization of analytical signals. The aim of this paper is to show the usefulness of the desirability function to optimize instrumental responses obtained in instrumental analysis. The simultaneous optimization of a signal and of its variability is a generic question of interest to any chemical analyst. It is clear that the improvement of the two responses forms the basis of the validation of any analytical method, and affects all the figures of merit: accuracy (trueness and precision), capability of detection, robustness, sensitivity, etc. Furthermore, in the specific case of electroanalysis, an improvement in the signal may implicitly mean an increase of the signal in the blank, such that the "net signal" may not improve. This experimental approach (surface response methodology plus desirability) to multicriteria optimization has been applied to three cases of growing complexity. Thus, in the determination of Cu(II) by differential pulse anodic stripping voltammetry the simultaneous maximization of the peak current and minimization of its standard deviation is looked for. Whereas, in the determinations of Ni(II) and indomethacin by differential pulse adsorptive stripping voltammetry, the simultaneous maximization of the peak current and minimization of the blank signal is desired. In all the cases, the experimental conditions where the optima are found for each individual response are just opposite, so it is required to look for a certain compromise, that is achieved using the desirability function.