Browsing by Author "Orazem, M. E."

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    Application of the kramers–kronig relations to multi-sine electrochemical impedance measurements
    (Institute of Physics Publishing, 2020) You, C.; Zabara, Mohammed Ahmed; Orazem, M. E.; Ulgut, Burak
    Impedance spectra obtained by fast Fourier transformation of the response to a multi-sine potential perturbation are shown to be consistent with the Kramers–Kronig relations, even for systems that are nonlinear and nonstationary. These results, observed for measurements on a Li/SOCl2 battery, were confirmed by numerical simulations. Consistency with the Kramers–Kronig relations was confirmed by use of the measurement model developed by Agrawal et al. and by a linear measurement model approach developed by Boukamp and implemented by Gamry. The present work demonstrates that application of the Kramers–Kronig relations to the results of multi-sine measurements cannot be used to determine whether the experimental system satisfies the conditions of linearity, causality and stability.
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    Utility of Lissajous plots for electrochemical impedance spectroscopy measurements: detection of non-linearity and non-stationarity
    (Electrochemical Society, Inc., 2024-01-10) Zabara, M. A.; Goh, J. M.; Gaudio, V. M.; Zou, L.; Orazem, M. E.; Ülgüt, Burak
    Correct interpretation of Electrochemical Impedance Spectroscopy (EIS) data is bound to the linearity and stationarity of the measurement. Current-Potential traces, also known as Lissajous figures for EIS measurements, contain valuable information regarding the linearity and the stationarity of the obtained data. Here, the behavior of the Lissajous figures is analyzed for various scenarios. The Lissajous analysis is shown to be helpful in the determination of the linearity and the stationarity of the data, especially for situations where Kramers-Kronig compatibility tests fail. The averaging of the Lissajous plots is shown to change the EIS results for non-linear and non-stationary systems. Further, the analysis of the Lissajous figures in the frequency domain by means of Fourier transforms is found to be very useful in differentiating between the non-linear and the non-stationary behaviors in the obtained data. The effect of averaging the Lissajous figures is also shown to make a difference when the system is non-stationary.