Topological data analysis assisted machine learning for polar topological structures in oxide superlattices

Ferroelectric topological phases and phase transitions have been extensively investigated recently due to the rich physical insights and potential applications in next-generation electronic devices. However, precisely predicting the topological phase transitions under different internal and external...

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Veröffentlicht in:	Acta materialia Jg. 282; S. 120467
Hauptverfasser:	Du, Guanshihan, Zhou, Linming, Huang, Yuhui, Wu, Yongjun, Hong, Zijian
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.01.2025
Schlagworte:	Machine learning Persistent homology Polar topological structures Topological data analysis Persistent homology Polar topological structures Topological data analysis Machine learning
ISSN:	1359-6454
Online-Zugang:	Volltext
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