Revealing ferroelectric switching character using deep recurrent neural networks

Autor: Joshua C. Agar, Brett Naul, Shishir Pandya, Stefan van der Walt, Joshua Maher, Yao Ren, Long-Qing Chen, Sergei V. Kalinin, Rama K. Vasudevan, Ye Cao, Joshua S. Bloom, Lane W. Martin
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Nature Communications, Vol 10, Iss 1, Pp 1-11 (2019)
Druh dokumentu: article
ISSN: 2041-1723
DOI: 10.1038/s41467-019-12750-0
Popis: The scale and dimensionality of imaging data means information is commonly overlooked. Here, using recurrent neural networks we understand temporal dependencies in hyperspectral imagery, enabling the observation of differences in ferroelectric switching mechanisms in PbZr0.2Ti0.8O3 thin films due to formation of charged domain walls.
Databáze: Directory of Open Access Journals