Ultrafast current imaging by Bayesian inversion

Somnath, Suhas; Law, Kody J. H.; Morozovska, Anna; Maksymovych, Petro; Kim, Yunseok; Lu, Xiaoli; Alexe, Marin; Archibald, Richard K; Kalinin, Sergei V; Jesse, Stephen; Vasudevan, Rama K

doi:10.13139/OLCF/1410993

Title: Ultrafast current imaging by Bayesian inversion

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 analysis. This "general-mode I-V"method allows three orders of magnitude faster rates than presently possible. The technique is demonstrated by acquiring I-V curves in ferroelectric nanocapacitors, yielding >100,000 I-V curves in <20 minutes. This allows detection of switching currents in the nanoscale capacitors, as well as determination of dielectric constant. These experiments show the potential for the use of full information capture and Bayesian inference towards extracting physics from rapid I-V measurements, and can be used for transport measurements in both atomic force and scanning tunneling microscopy. The data was analyzed using pycroscopy - an open-source python package available at https://github.com/pycroscopy/pycroscopy

Authors:: Somnath, Suhas; Law, Kody J. H.; Morozovska, Anna; Maksymovych, Petro; Kim, Yunseok; Lu, Xiaoli; Alexe, Marin; Archibald, Richard K; Kalinin, Sergei V; Jesse, Stephen; Vasudevan, Rama K

Publication Date:: Fri Jan 01 00:00:00 EST 2016

DOE Contract Number:: DEAC0500OR22725

Research Org.:: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)

Sponsoring Org.:: USDOE Office of Science (SC)

Subject:: 36 MATERIALS SCIENCE; 97 MATHEMATICS AND COMPUTING

Keywords:: Bayesian Inference, current imaging, lead zirconium titanate, PZT

OSTI Identifier:: 1410993

DOI:: https://doi.org/10.13139/OLCF/1410993

Citation Formats


                    Somnath, Suhas, Law, Kody J. H., Morozovska, Anna, Maksymovych, Petro, Kim, Yunseok, Lu, Xiaoli, Alexe, Marin, Archibald, Richard K, Kalinin, Sergei V, Jesse, Stephen, and Vasudevan, Rama K. Ultrafast current imaging by Bayesian inversion.  United States: N. p., 2016. 
        Web.  doi:10.13139/OLCF/1410993.

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                    Somnath, Suhas, Law, Kody J. H., Morozovska, Anna, Maksymovych, Petro, Kim, Yunseok, Lu, Xiaoli, Alexe, Marin, Archibald, Richard K, Kalinin, Sergei V, Jesse, Stephen, & Vasudevan, Rama K. Ultrafast current imaging by Bayesian inversion.  United States.  doi:https://doi.org/10.13139/OLCF/1410993

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                    Somnath, Suhas, Law, Kody J. H., Morozovska, Anna, Maksymovych, Petro, Kim, Yunseok, Lu, Xiaoli, Alexe, Marin, Archibald, Richard K, Kalinin, Sergei V, Jesse, Stephen, and Vasudevan, Rama K. 2016.  
"Ultrafast current imaging by Bayesian inversion".  United States.  doi:https://doi.org/10.13139/OLCF/1410993.  https://www.osti.gov/servlets/purl/1410993. Pub date:Fri Jan 01 00:00:00 EST 2016

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@article{osti_1410993,

  title        = {Ultrafast current imaging by Bayesian inversion},

  author       = {Somnath, Suhas and Law, Kody J. H. and Morozovska, Anna and Maksymovych, Petro and Kim, Yunseok and Lu, Xiaoli and Alexe, Marin and Archibald, Richard K and Kalinin, Sergei V and Jesse, Stephen and Vasudevan, Rama K},

  abstractNote = {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 analysis. This "general-mode I-V"method allows three orders of magnitude faster rates than presently possible. The technique is demonstrated by acquiring I-V curves in ferroelectric nanocapacitors, yielding >100,000 I-V curves in <20 minutes. This allows detection of switching currents in the nanoscale capacitors, as well as determination of dielectric constant. These experiments show the potential for the use of full information capture and Bayesian inference towards extracting physics from rapid I-V measurements, and can be used for transport measurements in both atomic force and scanning tunneling microscopy. The data was analyzed using pycroscopy - an open-source python package available at https://github.com/pycroscopy/pycroscopy},

  doi          = {10.13139/OLCF/1410993},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Fri Jan 01 00:00:00 EST 2016},

  month        = {Fri Jan 01 00:00:00 EST 2016}

}

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