Modeling electrochemical impedance spectroscopy

By F. Ciucci. Current Opinion in Electrochemistry, 2019

396 citations recorded by the source corpus.

Abstract Electrochemical impedance spectroscopy (EIS) is a powerful technique that is used for characterizing electrochemical systems. The EIS data can be correlated with many key physical properties, including rates of diffusion and reaction, and microstructural features. However, the EIS analysis is prone to the potential ambiguities in interpretation. Judicious modeling and its combination with statistics can be used to overcome these challenges and enhance the insight one can gain from EIS.

Subfields: Electrical and Electronic Engineering, Electrochemistry, Materials Chemistry

View Paper: https://www.semanticscholar.org/paper/ba00aefb1c3f2a0f5a1657af39d85ff50b2d7195

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Jiapeng Liu
2. T. Wan
3. F. Ciucci

In Electrochemistry

1. T. Wan
2. Jiapeng Liu
3. F. Ciucci

In Materials Chemistry

1. T. Wan
2. Jiapeng Liu
3. F. Ciucci

Citations in the corpus

• A Bayesian view on the Hilbert transform and the Kramers-Kronig transform of electrochemical impedance data: Probabilistic estimates and quality scores (2020, background): “Obtaining information across such a broad range of timescales allows one to gain insights from many disparate physicochemical phenomena.[17]”