Abstract
The most popular technique for characterizing various electrochemical devices such as fuel cells, water electrolysis or batteries is electrochemical impedance spectroscopy (EIS). However, due to the coupling of dynamic phenomena with similar time constants, EIS often fails to separate the contributions of individual processes to overall performance losses. In this case, obtaining useful information from the EIS spectra can bebe difficult and the interpretation of the observed patterns is unclear. In this talk, I show that new dynamical methods based on the use of nonlinearities in the system response (nonlinear frequency response analysis (NFRA) [1]), non-electrical inputs (concentration-alternating frequency response analysis (cFRA) [2]), or data-driven analyses (Loewner framework [3]) can provide additional information for understanding electrochemical conversion processes. Our current examples are related to the study of polymer electrolyte membrane electrolysis and polymer electrolyte membrane fuel cell.
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