Machine Learning-Assisted Battery Electrode Microstructure Characterization through Secondary-Ions Imaging - Forschungsportal der Justus-Liebig-Universität Gießen:

Meeting Abstract

Machine Learning-Assisted Battery Electrode Microstructure Characterization through Secondary-Ions Imaging

Autorenliste: Lombardo, Teo; Kern, Christine; Rohnke, Marcus; Sann, Joachim; Janek, Jürgen

Jahr der Veröffentlichung: 2023

Zeitschrift: ECS Meeting abstracts

Bandnummer: 2023

Heftnummer: 01

DOI Link: https://doi.org/10.1149/MA2023-011398mtgabs

Konferenz: 243rd ECS Meeting with the Eighteenth International Symposium on Solid Oxide Fuel Cells

Verlag: Electrochemical Society

Autoren/Herausgeber

- Uni.-Prof. Dr. Jürgen Janek

Zitierstile

Harvard-Zitierstil: Lombardo, T., Kern, C., Rohnke, M., Sann, J. and Janek, J. (2023) Machine Learning-Assisted Battery Electrode Microstructure Characterization through Secondary-Ions Imaging, ECS Meeting abstracts, 2023(01), Article 398. https://doi.org/10.1149/MA2023-011398mtgabs

APA-Zitierstil: Lombardo, T., Kern, C., Rohnke, M., Sann, J., & Janek, J. (2023). Machine Learning-Assisted Battery Electrode Microstructure Characterization through Secondary-Ions Imaging. ECS Meeting abstracts. 2023(01), Article 398. https://doi.org/10.1149/MA2023-011398mtgabs