Title:    Distribution of Relaxation Times for the Analysis of Large EIS Datasets

Time:    2026-04-13 14:30

Lecturer:  Prof. Francesco Ciucci

University of Bayreuth, Germany

Venue:    Room 202, Lu-Jiaxi Building

Abstract：

Electrochemical impedance spectroscopy (EIS) is a powerful technique for electrochemical characterization in research. However, interpreting EIS data is challenging and typically relies on non-unique equivalent circuit models. The distribution of relaxation time (DRT) method offers an alternative but requires solving an ill-posed inverse problem. To address this, we employ a Bayesian statistical framework.

The Bayesian approach's flexibility lets us incorporate prior knowledge into the DRT problem. We introduce two prior models. The first treats regularization penalty coefficients as multivariate random vectors, enabling timescale-dependent regularization that improves DRT recovery over traditional methods. The second prior is for the weights of the fitting residuals, allowing for anomaly detection in EIS data by treating them as random vectors. This enhances DRT recovery's robustness against experimental noise. We extend this approach to Gaussian processes and neural networks, demonstrating Bayesian statistics' efficacy for hyperparameter determination and for handling multidimensional, experiment-state-dependent data.

Bio of the Lecturer：

Prof. Francesco Ciucci is a University Professor at the University of Bayreuth, Germany, specializing in Electrode Design for Electrochemical Energy Storage. Before this, he served in various roles at HKUST. Prof. Ciucci holds degrees from the Politecnico di Milano and the École Centrale de Paris, and earned his Ph.D. from Caltech, where he was a Bechtel Fellow. His postdoctoral work was conducted at the University of Heidelberg. Prof. Ciucci's research focuses on solid-state energy storage and conversion technologies, with numerous high-impact publications. He is a Fellow of the Royal Society of Chemistry and was listed among Stanford's top 0.5% most influential scientists in Energy and Nanoscience Nanotechnology. He co-founded Solid-X Ltd., a solid-state battery company.