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Title: High-veracity functional imaging in scanning probe microscopy via Graph-Bootstrapping

Abstract

The key objective of scanning probe microscopy (SPM) techniques is the optimal representation of the nanoscale surface structure and functionality inferred from the dynamics of the cantilever. This is particularly pertinent today, as the SPM community has seen a rapidly growing trend towards simultaneous capture of multiple imaging channels and complex modes of operation involving high-dimensional information-rich datasets, bringing forward the challenges of visualization and analysis, particularly for cases where the underlying dynamic model is poorly understood. To meet this challenge, we present a data-driven approach, Graph-Bootstrapping, based on low-dimensional manifold learning of the full SPM spectra and demonstrate its successes for high-veracity mechanical mapping on a mixed polymer thin film and resolving irregular hydration structure of calcite at atomic resolution. Using the proposed methodology, we can efficiently reveal and hierarchically represent salient material features with rich local details, further enabling denoising, classification, and high-resolution functional imaging.

Authors:
 [1]; ORCiD logo [2];  [3];  [4]; ORCiD logo [2]; ORCiD logo [2]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Inst. for Functional Imaging of Materials; Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Science (CNMS); Florida State Univ., Tallahassee, FL (United States). Dept. of Industrial and Manufacturing Engineering; Florida State Univ., Tallahassee, FL (United States). Dept. of Statistics
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Inst. for Functional Imaging of Materials; Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Science (CNMS)
  3. Kanazawa Univ. (Japan). Division of Electric Engineering and Computer Science
  4. Kanazawa Univ. (Japan). Nano Life Science Inst. (WPI-NanoLSI)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1491309
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Nature Communications
Additional Journal Information:
Journal Volume: 9; Journal Issue: 1; Journal ID: ISSN 2041-1723
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; 97 MATHEMATICS AND COMPUTING

Citation Formats

Li, Xin, Collins, Liam F., Miyazawa, Keisuke, Fukuma, Takeshi, Jesse, Stephen, and Kalinin, Sergei V. High-veracity functional imaging in scanning probe microscopy via Graph-Bootstrapping. United States: N. p., 2018. Web. doi:10.1038/s41467-018-04887-1.
Li, Xin, Collins, Liam F., Miyazawa, Keisuke, Fukuma, Takeshi, Jesse, Stephen, & Kalinin, Sergei V. High-veracity functional imaging in scanning probe microscopy via Graph-Bootstrapping. United States. doi:https://doi.org/10.1038/s41467-018-04887-1
Li, Xin, Collins, Liam F., Miyazawa, Keisuke, Fukuma, Takeshi, Jesse, Stephen, and Kalinin, Sergei V. Thu . "High-veracity functional imaging in scanning probe microscopy via Graph-Bootstrapping". United States. doi:https://doi.org/10.1038/s41467-018-04887-1. https://www.osti.gov/servlets/purl/1491309.
@article{osti_1491309,
title = {High-veracity functional imaging in scanning probe microscopy via Graph-Bootstrapping},
author = {Li, Xin and Collins, Liam F. and Miyazawa, Keisuke and Fukuma, Takeshi and Jesse, Stephen and Kalinin, Sergei V.},
abstractNote = {The key objective of scanning probe microscopy (SPM) techniques is the optimal representation of the nanoscale surface structure and functionality inferred from the dynamics of the cantilever. This is particularly pertinent today, as the SPM community has seen a rapidly growing trend towards simultaneous capture of multiple imaging channels and complex modes of operation involving high-dimensional information-rich datasets, bringing forward the challenges of visualization and analysis, particularly for cases where the underlying dynamic model is poorly understood. To meet this challenge, we present a data-driven approach, Graph-Bootstrapping, based on low-dimensional manifold learning of the full SPM spectra and demonstrate its successes for high-veracity mechanical mapping on a mixed polymer thin film and resolving irregular hydration structure of calcite at atomic resolution. Using the proposed methodology, we can efficiently reveal and hierarchically represent salient material features with rich local details, further enabling denoising, classification, and high-resolution functional imaging.},
doi = {10.1038/s41467-018-04887-1},
journal = {Nature Communications},
number = 1,
volume = 9,
place = {United States},
year = {2018},
month = {6}
}

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Figures / Tables:

Figure 1 Figure 1: Concept of manifold-physics inference. The properties of the surface that define the scanning probe microscopy (SPM) signal form a lowdimensional parameter space, for example, defined by the Young and Poisson moduli and the work of adhesion. These properties are translated onto a (very high dimensional) response space bymore » means of the imaging mechanism of the cantilever/microscope. Aside from possible discontinuities due to changes in imaging regimes, points that are in close proximity in the parameter space will generally be in close proximity in the response space, forming a complex non-linear manifold« less

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