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Ultrafast current imaging by Bayesian inversion

Spectroscopic measurements of current–voltage curves in scanning probe microscopy is the earliest and one of the most common methods for characterizing local energy-dependent electronic properties, providing insight into superconductive, semiconductor, and memristive behaviors. However, the quasista...

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Autores principales: Somnath, S., Law, K. J. H., Morozovska, A. N., Maksymovych, P., Kim, Y., Lu, X., Alexe, M., Archibald, R., Kalinin, S. V., Jesse, S., Vasudevan, R. K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5802759/
https://www.ncbi.nlm.nih.gov/pubmed/29410417
http://dx.doi.org/10.1038/s41467-017-02455-7
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author Somnath, S.
Law, K. J. H.
Morozovska, A. N.
Maksymovych, P.
Kim, Y.
Lu, X.
Alexe, M.
Archibald, R.
Kalinin, S. V.
Jesse, S.
Vasudevan, R. K.
author_facet Somnath, S.
Law, K. J. H.
Morozovska, A. N.
Maksymovych, P.
Kim, Y.
Lu, X.
Alexe, M.
Archibald, R.
Kalinin, S. V.
Jesse, S.
Vasudevan, R. K.
author_sort Somnath, S.
collection PubMed
description Spectroscopic measurements of current–voltage curves in scanning probe microscopy is the earliest and one of the most common methods for characterizing local energy-dependent electronic properties, providing insight into superconductive, semiconductor, and memristive behaviors. However, the quasistatic nature of these measurements renders them extremely slow. Here, we demonstrate a fundamentally new approach for dynamic spectroscopic current imaging via full information capture and Bayesian inference. This general-mode I–V method allows three orders of magnitude faster measurement rates than presently possible. The technique is demonstrated by acquiring I–V curves in ferroelectric nanocapacitors, yielding >100,000 I–V curves in <20 min. This allows detection of switching currents in the nanoscale capacitors, as well as determination of the dielectric constant. These experiments show the potential for the use of full information capture and Bayesian inference toward extracting physics from rapid I–V measurements, and can be used for transport measurements in both atomic force and scanning tunneling microscopy.
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spelling pubmed-58027592018-02-09 Ultrafast current imaging by Bayesian inversion Somnath, S. Law, K. J. H. Morozovska, A. N. Maksymovych, P. Kim, Y. Lu, X. Alexe, M. Archibald, R. Kalinin, S. V. Jesse, S. Vasudevan, R. K. Nat Commun Article Spectroscopic measurements of current–voltage curves in scanning probe microscopy is the earliest and one of the most common methods for characterizing local energy-dependent electronic properties, providing insight into superconductive, semiconductor, and memristive behaviors. However, the quasistatic nature of these measurements renders them extremely slow. Here, we demonstrate a fundamentally new approach for dynamic spectroscopic current imaging via full information capture and Bayesian inference. This general-mode I–V method allows three orders of magnitude faster measurement rates than presently possible. The technique is demonstrated by acquiring I–V curves in ferroelectric nanocapacitors, yielding >100,000 I–V curves in <20 min. This allows detection of switching currents in the nanoscale capacitors, as well as determination of the dielectric constant. These experiments show the potential for the use of full information capture and Bayesian inference toward extracting physics from rapid I–V measurements, and can be used for transport measurements in both atomic force and scanning tunneling microscopy. Nature Publishing Group UK 2018-02-06 /pmc/articles/PMC5802759/ /pubmed/29410417 http://dx.doi.org/10.1038/s41467-017-02455-7 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Somnath, S.
Law, K. J. H.
Morozovska, A. N.
Maksymovych, P.
Kim, Y.
Lu, X.
Alexe, M.
Archibald, R.
Kalinin, S. V.
Jesse, S.
Vasudevan, R. K.
Ultrafast current imaging by Bayesian inversion
title Ultrafast current imaging by Bayesian inversion
title_full Ultrafast current imaging by Bayesian inversion
title_fullStr Ultrafast current imaging by Bayesian inversion
title_full_unstemmed Ultrafast current imaging by Bayesian inversion
title_short Ultrafast current imaging by Bayesian inversion
title_sort ultrafast current imaging by bayesian inversion
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5802759/
https://www.ncbi.nlm.nih.gov/pubmed/29410417
http://dx.doi.org/10.1038/s41467-017-02455-7
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