Fitting·Sensitify Studio

Circuit fitting

Fit EIS data to equivalent circuit models and extract physical parameters from impedance spectra.

A Nyquist plot does not directly tell you how fast charge transfer is or how thick a coating has grown. Circuit fitting translates the spectrum into physical numbers: solution resistance, charge-transfer resistance, double-layer capacitance.

Model the interface as a small electrical circuit whose elements correspond to physical processes, then adjust the element values until the simulated impedance matches the measured spectrum.

When to use it

→Characterising new electrodes: Rct quantifies how easy electron transfer is, Cdl reports on the electrochemically active area.
→Coating integrity: a defect-free coating shows a single large semicircle; pinholes and water uptake introduce a second time constant.
→Battery and fuel-cell diagnostics: separate ohmic loss (Rs), interfacial loss (Rct), and mass-transport loss (Warburg).
→Mechanism discrimination: different mechanisms map onto different circuits; the fit tells you which one the data supports.

How it works

Pick an equivalent circuit and provide starting values for each element. Studio runs a non-linear least-squares fit (Levenberg-Marquardt) against the complex impedance at every measured frequency.

The fit minimises a weighted residual so neither the low-frequency nor high-frequency end dominates. Modulus weighting is the default; proportional weighting is available for spectra that span many decades.

Fit quality is reported as χ² and a residual plot. Flat residuals mean the model captures the data; systematic trends mean the model is wrong or incomplete.

Sensitify Studio

Parameters you set

Model

Typical: Randles + Warburg for aqueous redox

Built-in circuits: Rs, Rs+C, Randles (Rs+Rct‖Cdl), Randles+Warburg, Rs+Rct‖CPE, two-time-constant (coating + interface). Custom circuits compose from R, C, CPE, L, and W elements.

Weighting

Typical: Modulus

Scales residuals before minimisation. Modulus weighting treats each decade equally; proportional weighting emphasises relative error.

Initial guesses

Starting values for each element. Good guesses speed convergence and avoid local minima. Studio auto-estimates from the shape of the spectrum; override manually when needed.

Frequency window

Crop noisy endpoints or non-stationary regions out of the fit. Defaults to the full acquired range.

Example

Walkthrough

Fit a Randles + Warburg circuit to a coated-steel sample

1Open the EIS spectrum in Studio and switch to the Nyquist view.
2Analyse → Circuit fit → pick Randles + Warburg.
3Accept the auto-generated initial guesses and leave weighting at Modulus.
4Run the fit. The simulated impedance overlays the data in real time.
5Inspect the residual plot. A flat band around zero confirms the model fits.

Result

Rs, Rct, Cdl, and σ (Warburg coefficient) with 95 % confidence intervals and a χ² figure of merit. One click exports the parameter table as CSV or as a PDF addendum to the figure.

In Sensitify Studio

Circuit fitting lives under Analyse → Circuit fit in Sensitify Studio. Pick a built-in model or compose your own in the editor, run the fit, and overlay the simulated impedance on your data. Parameter values, confidence intervals, and residuals export directly to PDF for figure-ready output.

Step-by-step in docs

Fit a circuit

Other analysis tools

Peak finding

Detection

Integration

Processing

Filtering

Processing