Performance Prediction of High-Entropy Perovskites La0.8Sr0.2MnxCoyFezO3 with Automated High-Throughput Characterization of Combinatorial Libraries and Machine Learning

© 2024 The Author(s). Advanced Materials published by Wiley‐VCH GmbH.

Bibliographische Detailangaben
Veröffentlicht in:Advanced materials (Deerfield Beach, Fla.). - 1998. - 36(2024), 50 vom: 12. Dez., Seite e2407372
1. Verfasser: Bozal-Ginesta, Carlota (VerfasserIn)
Weitere Verfasser: Sirvent, Juande, Cordaro, Giulio, Fearn, Sarah, Pablo-García, Sergio, Chiabrera, Francesco, Choi, Changhyeok, Laa, Lisa, Núñez, Marc, Cavallaro, Andrea, Buzi, Fjorelo, Aguadero, Ainara, Dezanneau, Guilhem, Kilner, John, Morata, Alex, Baiutti, Federico, Aspuru-Guzik, Alán, Tarancón, Albert
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2024
Zugriff auf das übergeordnete Werk:Advanced materials (Deerfield Beach, Fla.)
Schlagworte:Journal Article high entropy oxides high‐throughput experimentation machine learning perovskite oxides solid oxide fuel cells