Revealing ferroelectric switching character using deep recurrent neural networks
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...
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Autores principales: | 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 |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2019
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Materias: | |
Acceso en línea: | https://doaj.org/article/6c60e037e5014ff79246798588ae89fa |
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