Work

The Gaussian process distribution of relaxation times: A machine learning tool for the analysis and prediction of electrochemical impedance spectroscopy data

Year: 2019

Type: article

Source: Electrochimica Acta

DOI: 10.1016/j.electacta.2019.135316

Authors: Jiapeng Liu, Francesco Ciucci

Institution: Hong Kong University of Science and Technology

Language: English

Topic: Gaussian Processes and Bayesian Inference

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: Research Grants Council, University Grants Committee, Guangzhou Science and Technology Program key projects

Awards: Advanced SOFC anodes with in situ exsolved nanoparticles: characterizations from the macro to the nanoscale and computational studies, G8060646889, Chemically and electrochemically driven nanoparticle egress from A-site-deficient perovskites: A computational and experimental study of nanoparticle growth, Ba segregation in La-substituted BaFeO3: in-situ and ex-situ characterization and computational modeling.

OpenAlex ID: W2991224188

FWCI: 4.427

Cites: 91

Cited by: 206

Related to: 10