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:
-
- 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
- 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)
- Kanazawa Univ. (Japan). Division of Electric Engineering and Computer Science
- Kanazawa Univ. (Japan). Nano Life Science Inst. (WPI-NanoLSI)
- Publication Date:
- Research Org.:
- Oak Ridge National Laboratory (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. 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. 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 = {Thu Jun 21 00:00:00 EDT 2018},
month = {Thu Jun 21 00:00:00 EDT 2018}
}
Web of Science
Figures / Tables:
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