Abstract
AC impedance spectroscopy is an important method for evaluating ionic, electronic, and dielectric properties of materials. In conventional analysis of AC impedance spectra, the selection of an equivalent circuit model and its initial parameters are visually determined from a Nyquist plot; this visual determination can be both inefficient and inaccurate. Thus, analysis based on a rigorous mathematical method is highly desirable. Here, we demonstrate the analysis of AC impedance spectra using Bayesian statistics. We apply the method to artificial AC impedance spectra generated from resistance (R) and capacitance (C) circuits, obtaining a high accuracy ratio (>90%) in model selection when the ratio of the time constants of two RC parallel circuits exceeds 3. Furthermore, this method is applied to an actual electrical circuit comprising a resistance and two RC parallel circuits, yielding highly accurate model selection and parameter estimation. The results demonstrate the effectiveness of the proposed method for AC impedance spectra.
Highlights
AC impedance spectroscopy is a popular method for analyzing the ionic, electronic, and dielectric properties of materials.1 During AC impedance measurements, an AC voltage is applied to a sample at different frequencies, and the electrical current is measured
We apply the method to artificial AC impedance spectra generated from resistance (R) and capacitance (C) circuits, obtaining a high accuracy ratio (>90%) in model selection when the ratio of the time constants of two RC parallel circuits exceeds 3
These results indicate that the estimation of σ is accurate and confirm that our Bayesian statistics approach can be applied to experimental AC impedance spectra
Summary
AC impedance spectroscopy is a popular method for analyzing the ionic, electronic, and dielectric properties of materials. During AC impedance measurements, an AC voltage is applied to a sample at different frequencies, and the electrical current is measured. During AC impedance measurements, an AC voltage is applied to a sample at different frequencies, and the electrical current is measured This method enables the quantitative analysis of intra- and inter-grain electrical conductivity as well as the evaluation of each elementary process in devices, including fuel cells, supercapacitors, lithium batteries, and solar cells.. In the conventional analysis of dielectrics and ionic/electronic conductors, the number of RC parallel circuits and the initial model parameters are visually determined from the Nyquist plot; this visual determination can be both inefficient and inaccurate. Our analysis succeeded with high accuracy when applied to an actual electrical circuit These results indicate that the proposed method is suitable for AC impedance spectra analysis, opening the way to unambiguous and systematic analysis of such data
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