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 <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.
Highlights
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
We report a fundamentally new approach to the problem, based on the combination of full information capture from the current amplifier, AC excitation, and Bayesian inference in order to recover I–V curves at rates hundreds of times faster than the current state of the art
The use of general-mode I–V (G-IV) and Bayesian inference has allowed for detection and quantitative mapping of the switching response in nanoscale ferroelectric capacitors at unprecedented resolution, at speeds of standard scanning
Summary
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. Enhancing the speed of acquisition is of critical importance to enable further advances in a multitude of fields within nanoscience In this communication, we report a fundamentally new approach to the problem, based on the combination of full information capture from the current amplifier, AC excitation (as opposed to standard DC voltage waveforms), and Bayesian inference in order to recover I–V curves at rates hundreds of times faster than the current state of the art. We report a fundamentally new approach to the problem, based on the combination of full information capture from the current amplifier, AC excitation (as opposed to standard DC voltage waveforms), and Bayesian inference in order to recover I–V curves at rates hundreds of times faster than the current state of the art We term this method ‘general-mode I–V’ (G-IV) acquisition, and show its utility via detection of switching currents in ferroelectric nanocapacitors, and compare it with standard IV acquisition on the same area. The method in general can be readily applied in both AFM and STM, and further allows access to current measurements as a function of frequency in the 10–100s Hz range, opening new avenues for nanoscale electronic measurements
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
