Big Data and Deep data in scanning and electron microscopies: functionality from multidimensional data sets

Belianinov, Alex; Vasudevan, Rama K; Strelcov, Evgheni; Steed, Chad A; Yang, Sang Mo; Tselev, Alexander; Jesse, Stephen; Biegalski, Michael D; Shipman, Galen M; Symons, Christopher T; Borisevich, Albina Y; Archibald, Richard K; Kalinin, Sergei

doi:10.1186/s40679-015-0006-6

Title: Big Data and Deep data in scanning and electron microscopies: functionality from multidimensional data sets

Journal Article · Wed May 13 00:00:00 EDT 2015 · Advanced Structural and Chemical Imaging

DOI:https://doi.org/10.1186/s40679-015-0006-6· OSTI ID:1214489

Belianinov, Alex ^[1]; Vasudevan, Rama K ^[1]; Strelcov, Evgheni ^[1]; Steed, Chad A ^[1]; Yang, Sang Mo ^[2]; Tselev, Alexander ^[1]; Jesse, Stephen ^[1]; Biegalski, Michael D ^[1]; Shipman, Galen M ^[1]; Symons, Christopher T ^[1]; Borisevich, Albina Y ^[1]; Archibald, Richard K ^[1]; Kalinin, Sergei ^[1]

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Seoul National Univ. (Korea, Republic of)

The development of electron, and scanning probe microscopies in the second half of the twentieth century have produced spectacular images of internal structure and composition of matter with, at nanometer, molecular, and atomic resolution. Largely, this progress was enabled by computer-assisted methods of microscope operation, data acquisition and analysis. The progress in imaging technologies in the beginning of the twenty first century has opened the proverbial floodgates of high-veracity information on structure and functionality. High resolution imaging now allows information on atomic positions with picometer precision, allowing for quantitative measurements of individual bond length and angles. Functional imaging often leads to multidimensional data sets containing partial or full information on properties of interest, acquired as a function of multiple parameters (time, temperature, or other external stimuli). Here, we review several recent applications of the big and deep data analysis methods to visualize, compress, and translate this data into physically and chemically relevant information from imaging data.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Sciences (CNMS)

Sponsoring Organization:: USDOE Office of Science (SC)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1214489

Journal Information:: Advanced Structural and Chemical Imaging, Vol. 1, Issue 6; ISSN 2198-0926

Publisher:: SpringerCopyright Statement

Country of Publication:: United States

Language:: English

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