Data-Driven Investigation of Aqueous Zinc Anode Degradation Using Design of Experiments and Bayesian Optimization

Zenodo (CERN European Organization for Nuclear Research) 2026 Dataset Open access

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Authors: Klara Neumayr, Pronoy Dutta, Christian Prehal
DOI: 10.5281/zenodo.18618782
Cited by: 0

Abstract

Raw data set of the publication K. Neumayr, P. Dutta, C. Prehal, Data-Driven Investigation of Aqueous Zinc Anode Degradation Using Design of Experiments and Bayesian Optimization, 2026

Fields of Study & Subjects

Advanced battery technologies research Machine Learning in Materials Science Optimal Experimental Design Methods

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
12 February 2026
Language
EN
Document type
Dataset