Big, Deep, and Smart Data in Scanning Probe Microscopy

Sergei V. Kalinin, Evgheni Strelcov, Alex Belianinov, Suhas Somnath, Rama K. Vasudevan, Eric J. Lingerfelt, Richard K. Archibald, Chaomei Chen, Roger Proksch, Nouamane Laanait, Stephen Jesse

Research output: Contribution to journalArticlepeer-review

96 Scopus citations

Abstract

Scanning probe microscopy (SPM) techniques have opened the door to nanoscience and nanotechnology by enabling imaging and manipulation of the structure and functionality of matter at nanometer and atomic scales. Here, we analyze the scientific discovery process in SPM by following the information flow from the tip-surface junction, to knowledge adoption by the wider scientific community. We further discuss the challenges and opportunities offered by merging SPM with advanced data mining, visual analytics, and knowledge discovery technologies.

Original languageEnglish
Pages (from-to)9068-9086
Number of pages19
JournalACS Nano
Volume10
Issue number10
DOIs
StatePublished - Oct 25 2016

Funding

The research on developing advanced SPM methods and analysis was conducted at the Center for Nanophase Materials Sciences, which is a DOE Office of Science User Facility (S.V.K., E.S., A.B., S.S., R.K.V., N.L., and S.J.). Research by E.J.L. on developing the HPC data analysis and stewardship infrastructure is sponsored by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the U.S. Department of Energy. N.L. was supported by the Eugene P. Wigner Fellowship at Oak Ridge National Laboratory. R.K.A. acknowledges the Compute and Data Environment for Science (CADES) for continuous support. The mathematical aspects were sponsored by the applied mathematics program at the DOE and the computational aspects made use of the Oak Ridge Leadership Computing Facility, a DOE Office of Science User Facility at ORNL supported under contract no. DEAC05-00OR22725. This manuscript has been authored by UTBattelle, LLC, with the U.S. Department of Energy.

FundersFunder number
Compute and Data Environment for Science
U.S. Department of Energy
Office of Science
Oak Ridge National LaboratoryDEAC05-00OR22725

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