Differential impedance analysis — Extensions and applications in machine learning
Leonard Voss, Alfred Liedtke, Robert J. Martin · Electrochimica Acta · 2024
The technique of differential impedance analysis (DIA) has shown promising results in identifying appropriate model orders when applied to electrochemical impedance spectroscopy (EIS) measurements of a given medium. However, even with this method it remains challenging to reliably deduce general material properties of the medium from impedance data alone. Here, we discuss a number of possible extensions and modifications of the technique and, in particular, an extension of the process from mere model order identification to a complete modelling approach. In addition, the combination of DIA and machine learning methods to predict material properties is explored. Our results were validated with impedance measurements between 20 Hz and 1 MHz of moulding sand containing varying amounts of quartz and chromite sand as well as bentonite and carbon.