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Title: Full data acquisition in Kelvin Probe Force Microscopy: Mapping dynamic electric phenomena in real space

Abstract

Kelvin probe force microscopy (KPFM) has provided deep insights into the role local electronic, ionic and electrochemical processes play on the global functionality of materials and devices, even down to the atomic scale. Conventional KPFM utilizes heterodyne detection and bias feedback to measure the contact potential difference (CPD) between tip and sample. This measurement paradigm, however, permits only partial recovery of the information encoded in bias- and time-dependent electrostatic interactions between the tip and sample and effectively down-samples the cantilever response to a single measurement of CPD per pixel. This level of detail is insufficient for electroactive materials, devices, or solid-liquid interfaces, where non-linear dielectrics are present or spurious electrostatic events are possible. Here, we simulate and experimentally validate a novel approach for spatially resolved KPFM capable of a full information transfer of the dynamic electric processes occurring between tip and sample. General acquisition mode, or G-Mode, adopts a big data approach utilising high speed detection, compression, and storage of the raw cantilever deflection signal in its entirety at high sampling rates (> 4 MHz), providing a permanent record of the tip trajectory. We develop a range of methodologies for analysing the resultant large multidimensional datasets involving classical, physics-based andmore » information-based approaches. Physics-based analysis of G-Mode KPFM data recovers the parabolic bias dependence of the electrostatic force for each cycle of the excitation voltage, leading to a multidimensional dataset containing spatial and temporal dependence of the CPD and capacitance channels. We use multivariate statistical methods to reduce data volume and separate the complex multidimensional data sets into statistically significant components that can then be mapped onto separate physical mechanisms. Overall, G-Mode KPFM offers a new paradigm to study dynamic electric phenomena in electroactive interfaces as well as offer a promising approach to extend KPFM to solid-liquid interfaces.« less

Authors:
 [1];  [1];  [1];  [1];  [1];  [1]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Sciences (CNMS)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1295108
Grant/Contract Number:
AC05-00OR22725
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Scientific Reports
Additional Journal Information:
Journal Volume: 6; Journal ID: ISSN 2045-2322
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY

Citation Formats

Balke, Nina, Kalinin, Sergei V., Jesse, Stephen, Collins, Liam, Belianinov, Alex, and Somnath, Suhas. Full data acquisition in Kelvin Probe Force Microscopy: Mapping dynamic electric phenomena in real space. United States: N. p., 2016. Web. doi:10.1038/srep30557.
Balke, Nina, Kalinin, Sergei V., Jesse, Stephen, Collins, Liam, Belianinov, Alex, & Somnath, Suhas. Full data acquisition in Kelvin Probe Force Microscopy: Mapping dynamic electric phenomena in real space. United States. doi:10.1038/srep30557.
Balke, Nina, Kalinin, Sergei V., Jesse, Stephen, Collins, Liam, Belianinov, Alex, and Somnath, Suhas. Fri . "Full data acquisition in Kelvin Probe Force Microscopy: Mapping dynamic electric phenomena in real space". United States. doi:10.1038/srep30557. https://www.osti.gov/servlets/purl/1295108.
@article{osti_1295108,
title = {Full data acquisition in Kelvin Probe Force Microscopy: Mapping dynamic electric phenomena in real space},
author = {Balke, Nina and Kalinin, Sergei V. and Jesse, Stephen and Collins, Liam and Belianinov, Alex and Somnath, Suhas},
abstractNote = {Kelvin probe force microscopy (KPFM) has provided deep insights into the role local electronic, ionic and electrochemical processes play on the global functionality of materials and devices, even down to the atomic scale. Conventional KPFM utilizes heterodyne detection and bias feedback to measure the contact potential difference (CPD) between tip and sample. This measurement paradigm, however, permits only partial recovery of the information encoded in bias- and time-dependent electrostatic interactions between the tip and sample and effectively down-samples the cantilever response to a single measurement of CPD per pixel. This level of detail is insufficient for electroactive materials, devices, or solid-liquid interfaces, where non-linear dielectrics are present or spurious electrostatic events are possible. Here, we simulate and experimentally validate a novel approach for spatially resolved KPFM capable of a full information transfer of the dynamic electric processes occurring between tip and sample. General acquisition mode, or G-Mode, adopts a big data approach utilising high speed detection, compression, and storage of the raw cantilever deflection signal in its entirety at high sampling rates (> 4 MHz), providing a permanent record of the tip trajectory. We develop a range of methodologies for analysing the resultant large multidimensional datasets involving classical, physics-based and information-based approaches. Physics-based analysis of G-Mode KPFM data recovers the parabolic bias dependence of the electrostatic force for each cycle of the excitation voltage, leading to a multidimensional dataset containing spatial and temporal dependence of the CPD and capacitance channels. We use multivariate statistical methods to reduce data volume and separate the complex multidimensional data sets into statistically significant components that can then be mapped onto separate physical mechanisms. Overall, G-Mode KPFM offers a new paradigm to study dynamic electric phenomena in electroactive interfaces as well as offer a promising approach to extend KPFM to solid-liquid interfaces.},
doi = {10.1038/srep30557},
journal = {Scientific Reports},
number = ,
volume = 6,
place = {United States},
year = {Fri Aug 12 00:00:00 EDT 2016},
month = {Fri Aug 12 00:00:00 EDT 2016}
}

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