Pyeis: A Python-Based Electrochemical Impedance Spectroscopy Analyzer and Simulator

Electrochemical Impedance Spectroscopy can be a powerful analytical tool for the electrochemist as it can have the ability of separating kinetics, double-layers, adsorption, and mass-transport from a current/voltage response. This can often be a difficult task as the response depends on a large parameter space, such as: electrode configuration, porosity, pore size morphology, reference electrode, distance between working- and reference electrode, interfacial layers that depends on, among other, electrolyte composition, current collectors, potential, temperature, etc. Electrochemical processes can be described through circuit elements and a combination of these are referred to as equivalent circuit elements that model the cell or interface in question. Classically, kinetic contributions are referred to as charge-transfer resistances, double-layer as capacitors and their derivatives, and mass-transport have a wide range of terms. PyEIS is an open-source platform that is able to simulate, evaluate data quality, fit, and plot electrochemical impedance spectroscopy data. It is built in a modular layout to facilitate add-ons, modifications, and it is therefore possible with relative ease to add any desired equivalent circuit. It is based on an open-source packages 4–6 and is written in Python, a modern high-level computing language commonly used by the scientific community. PyEIS will be available as a Python package and currently includes 27 equivalent circuits where some represent simple non-faradaic and faradaic systems, the impedance of macro disk- and microdisk electrodes with well-defined mass-transport regimes, as well as non-faradaic and faradaic porous electrodes with and without solid-state diffusion. PyEIS has the ability to simulate any equivalent circuit including the dependency on potential of the i) the charge-transfer resistance following Butler-Volmer or Marcus-Hush-Chidsey infinite or finite kinetic theories, ii) the mass-transport elements of the macro- and microdisk electrodes, and iii) the double-layer capacitance following the theories of Gouy-Chapman or Stern. This makes it possible to predict the impedance of any equivalent circuit following the potential dependency of the above-mentioned theories allowing the user to simulate and adjust experimental parameters to optimize experimental conditions. PyEIS also contains algorithms for the linear Kramers-Kronig validity analysis that investigate the experimental data quality for causality, li