Deep learning ferroelectric polarization distributions from STEM data via with and without atom finding
Abstract Over the last decade, scanning transmission electron microscopy (STEM) has emerged as a powerful tool for probing atomic structures of complex materials with picometer precision, opening the pathway toward exploring ferroelectric, ferroelastic, and chemical phenomena on the atomic scale. An...
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| Auteurs principaux: | , , , , , , |
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| Format: | article |
| Langue: | EN |
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Nature Portfolio
2021
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| Accès en ligne: | https://doaj.org/article/cc3e9a82689c4472ba644777e5a547c8 |
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