Autonomous scanning probe microscopy with hypothesis learning: Exploring the physics of domain switching in ferroelectric materials

Using hypothesis-learning-driven automated scanning probe microscopy (SPM), we explore the bias-induced transformations that underpin the functionality of broad classes of devices and materials from batteries and memristors to ferroelectrics and antiferroelectrics. Optimization and design of these m...

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Detalles Bibliográficos
Autores principales: Liu, Yongtao, Morozovska, Anna N., Eliseev, Eugene A., Kelley, Kyle P., Vasudevan, Rama, Ziatdinov, Maxim, Kalinin, Sergei V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10028429/
https://www.ncbi.nlm.nih.gov/pubmed/36960442
http://dx.doi.org/10.1016/j.patter.2023.100704

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10028429/
https://www.ncbi.nlm.nih.gov/pubmed/36960442
http://dx.doi.org/10.1016/j.patter.2023.100704

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