Complex numbers-partial least-squares applied to the treatment of electrochemical impedance spectroscopy data

This work investigated the application of partial least-squares regression of complex numbers on multivariate data obtained by electrochemical impedance spectroscopy (EIS). The use of complex numbers-PLS was evaluated in the individual determination of two well-known redox probes: ferrocyanide and hydroquinone. The predictive ability of complex numbers-PLS was evaluated for EIS spectra obtained at different applied potentials and perturbation amplitudes, and was also compared to that obtained with PLS applied to EIS data presented as real numbers - only the real or imaginary part of the complex impedance, or the absolute impedance or the phase angle. It is shown that complex numbers-PLS is more efficient (better prediction models) when more complex electrochemical systems (hydroquinone) are probed. Excellent predictions were obtained for the determination of hydroquinone and catechol in the direct analysis of spiked tap water samples with EIS and complex numbers-PLS.