Abstract
Electrochemical Impedance Spectroscopy (EIS) is a much valued research tool for studying electrochemical cells, systems and devises. With this non-invasive technique mass and charge transport and storage is studied by measuring the response to a sinusoidal perturbation signal (voltage or current) over a wide frequency range. The frequency dependent relation between perturbation and response can be presented as a complex valued impedance, admittance, dielectric, etc. Acquisition of the spectra is relatively easy with modern automated Frequency Response Analysis (FRA) systems, but the interpretation is often complicated. Lack of experience can lead to misinterpretation and inadequate presentation of results. Data validation with a Kramers-Kronig consistency check is an essential starting point for the data analysis process. The Complex Nonlinear Least Squares (CNLS) analysis method, based on an Equivalent Circuit Model (ECM) or a special transfer function is still the most used procedure for data interpretation. Inversion of impedance data to a Distribution Function of Relaxation Times (DFRT) is gaining significant attention. Sufficient knowledge of, and experience with these techniques is required for arriving at a trustworthy result. Unfortunately, many manuscripts lack a thorough evaluation of the obtained results. In several cases these problems pass uncorrected the peer review system. This contribution provides a brief overview of mistakes quite often made in EIS analysis. It tries to provide guidance for the inexperienced scientists. Simultaneously, to support prospective reviewers of EIS related manuscripts, a checklist is presented with common EIS analysis and interpretation errors.
| Original language | English |
|---|---|
| Article number | 146892 |
| Number of pages | 14 |
| Journal | Electrochimica acta |
| Volume | 537 |
| Early online date | 11 Jul 2025 |
| DOIs | |
| Publication status | Published - 10 Oct 2025 |
Keywords
- UT-Hybrid-D
- Data validation
- Distribution function of relaxation times (DFRT)
- Electrochemical Impedance Spectroscopy (EIS)
- Inductive Effects
- Complex nonlinear least squares analysis (CNLS)