How to check and correct non-stationary EIS measurements using EC-Lab® (corrosion) AN69/1Latest updated: November 20, 2020
This application note presents the various tools available in EC-Lab® that can be used to check and correct the non-stationarity of your EIS measurements. Using galvano control, the proprietary Non-Stationary Distorsion indicator, and the instantaneous impedance analysis tool Z Inst, users can ensure that EIS measurements are correctly interpreted and fitted. This application note shows the use of such tools on data obtained on a corroding electrode.
For valid Electrochemical Impedance Spectroscopy (EIS) measurements, the system under investigation should be linear, stable, causal, and stationary [1,2]. In this note, the term “stationarity” comprises steady-state and time-invariance.
Steady-state is the state of a system after its transient state. For example, an R/C circuit submitted to a potential or current step is in a transient state and sees its response change after a certain amount of time has passed.
Time-variance refers to a system where parameters define its transfer function change with time. As an example, a corroding electrode whose polarization resistance changes over time, either because of corrosion or of passivation, is a time-variant system.
The two properties may be difficult to separate.
The most classical use of EIS in corrosion is for the determination of the polarization resistance Rp using the Stern or Wagner-Traud relationship [3-7]. A corroding system is a non-stationary system specifically after the first instant of immersion. The change in parameters can greatly affect the impedance data, especially at lower frequencies .
In this first part of application note 69, we will present various tools implemented in EC-Lab® to help check and correct the time-variance of measurements. These tools will be applied to measurements on a corroding mild steel electrode. The second part will apply these tools to a discharging battery .
Corrosion EIS Non-stationary 4D impedance NSD modelling analysis