Quantification of flexoelectricity in PbTiO3/SrTiO3 superlattice polar vortices using machine learning and phase-field modeling
Flexoelectric coupling between strain gradients and polarization influences the physics of ferroelectric devices but it is difficult to directly probe its effects. Here, Li et al. use principal component analysis to compare STEM images with phase-field modeling and extract the flexoelectric contribu...
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Nature Portfolio
2017
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oai:doaj.org-article:5c2afb0ab0ce462a92da7d13496d55bb2021-12-02T14:42:34ZQuantification of flexoelectricity in PbTiO3/SrTiO3 superlattice polar vortices using machine learning and phase-field modeling10.1038/s41467-017-01733-82041-1723https://doaj.org/article/5c2afb0ab0ce462a92da7d13496d55bb2017-11-01T00:00:00Zhttps://doi.org/10.1038/s41467-017-01733-8https://doaj.org/toc/2041-1723Flexoelectric coupling between strain gradients and polarization influences the physics of ferroelectric devices but it is difficult to directly probe its effects. Here, Li et al. use principal component analysis to compare STEM images with phase-field modeling and extract the flexoelectric contributions.Q. LiC. T. NelsonS.-L. HsuA. R. DamodaranL.-L. LiA. K. YadavM. McCarterL. W. MartinR. RameshS. V. KalininNature PortfolioarticleScienceQENNature Communications, Vol 8, Iss 1, Pp 1-8 (2017) |
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Science Q Q. Li C. T. Nelson S.-L. Hsu A. R. Damodaran L.-L. Li A. K. Yadav M. McCarter L. W. Martin R. Ramesh S. V. Kalinin Quantification of flexoelectricity in PbTiO3/SrTiO3 superlattice polar vortices using machine learning and phase-field modeling |
description |
Flexoelectric coupling between strain gradients and polarization influences the physics of ferroelectric devices but it is difficult to directly probe its effects. Here, Li et al. use principal component analysis to compare STEM images with phase-field modeling and extract the flexoelectric contributions. |
format |
article |
author |
Q. Li C. T. Nelson S.-L. Hsu A. R. Damodaran L.-L. Li A. K. Yadav M. McCarter L. W. Martin R. Ramesh S. V. Kalinin |
author_facet |
Q. Li C. T. Nelson S.-L. Hsu A. R. Damodaran L.-L. Li A. K. Yadav M. McCarter L. W. Martin R. Ramesh S. V. Kalinin |
author_sort |
Q. Li |
title |
Quantification of flexoelectricity in PbTiO3/SrTiO3 superlattice polar vortices using machine learning and phase-field modeling |
title_short |
Quantification of flexoelectricity in PbTiO3/SrTiO3 superlattice polar vortices using machine learning and phase-field modeling |
title_full |
Quantification of flexoelectricity in PbTiO3/SrTiO3 superlattice polar vortices using machine learning and phase-field modeling |
title_fullStr |
Quantification of flexoelectricity in PbTiO3/SrTiO3 superlattice polar vortices using machine learning and phase-field modeling |
title_full_unstemmed |
Quantification of flexoelectricity in PbTiO3/SrTiO3 superlattice polar vortices using machine learning and phase-field modeling |
title_sort |
quantification of flexoelectricity in pbtio3/srtio3 superlattice polar vortices using machine learning and phase-field modeling |
publisher |
Nature Portfolio |
publishDate |
2017 |
url |
https://doaj.org/article/5c2afb0ab0ce462a92da7d13496d55bb |
work_keys_str_mv |
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1718389630575837184 |