Validation of dynamic electrochemical impedance spectrograms using autocorrelation function

Validation of impedance data is essential for checking the reliability of experimental data. Kramers – Kronig transformation is used to verify data obtained from classical Electrochemical Impedance Spectroscopy (EIS) measurements. Data obtained from Dynamic Electrochemical Impedance Spectroscopy (DEIS) could be validated in the same way, but in this case, there is no information about internal consistency between every single spectrum in the whole spectrogram. To address these challenges, the authors proposed an approach using the autocorrelation function ACF to validate DEIS time series. The reasoning conducted showed that ACF function is appropriate tool for validating DEIS spectrograms.