A Bayesian Approach to Autonomous Analysis of Electrochemical Impedance Spectra
Abstract
Electrochemical impedance spectroscopy (EIS) is a valuable characterization tool for a wide variety of materials due to its ability to probe transport and reaction pathways over a broad range of timescales. Recently, developments in experimental techniques have increased the use of EIS in high-throughput materials characterization. However, extraction of meaningful insight from high-volume EIS data streams is often stymied by the complexity of processing and analyzing impedance spectra. To address this challenge, we present a framework for fully autonomous analysis of EIS data leveraging Bayesian methods to obtain both the distribution of relaxation times (DRT) and equivalent circuit fits.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Nov 23, 2020
- Source ID
- 10.1149/ma2020-02402508mtgabs
Entities
People
- Andriy Zakutayev
- Jake Huang
- Meagan C Papac
- Ryan O'Hayre