Ultrafast current imaging by Bayesian inversion

S. Somnath, K. J. H. Law, A. N. Morozovska, P. Maksymovych, Y. Kim, X. Lu, M. Alexe, R. Archibald, S. V. Kalinin, S. Jesse and R. K. Vasudevan ()
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S. Somnath: Oak Ridge National Laboratory
K. J. H. Law: Oak Ridge National Laboratory
A. N. Morozovska: National Academy of Sciences of Ukraine
P. Maksymovych: Oak Ridge National Laboratory
Y. Kim: Sungkyunkwan University (SKKU)
X. Lu: Xidian University
M. Alexe: University of Warwick
R. Archibald: Oak Ridge National Laboratory
S. V. Kalinin: Oak Ridge National Laboratory
S. Jesse: Oak Ridge National Laboratory
R. K. Vasudevan: Oak Ridge National Laboratory

Nature Communications, 2018, vol. 9, issue 1, 1-11

Abstract: Abstract 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

Date: 2018
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DOI: 10.1038/s41467-017-02455-7

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