Machine learning–enabled identification of material phase transitions based on experimental data: Exploring collective dynamics in ferroelectric relaxors

Exploration of phase transitions and construction of associated phase diagrams are of fundamental importance for condensed matter physics and materials science alike, and remain the focus of extensive research for both theoretical and experimental studies. For the latter, comprehensive studies invol...

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Detalles Bibliográficos
Autores principales: Li, Linglong, Yang, Yaodong, Zhang, Dawei, Ye, Zuo-Guang, Jesse, Stephen, Kalinin, Sergei V., Vasudevan, Rama K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2018
Materias:
Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5903900/
https://www.ncbi.nlm.nih.gov/pubmed/29670940
http://dx.doi.org/10.1126/sciadv.aap8672

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5903900/
https://www.ncbi.nlm.nih.gov/pubmed/29670940
http://dx.doi.org/10.1126/sciadv.aap8672

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