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This content will become publicly available on November 9, 2017

Title: Data mining graphene: Correlative analysis of structure and electronic degrees of freedom in graphenic monolayers with defects

The link between changes in the material crystal structure and its mechanical, electronic, magnetic, and optical functionalities known as the structure-property relationship is the cornerstone of the contemporary materials science research. The recent advances in scanning transmission electron and scanning probe microscopies (STEM and SPM) have opened an unprecedented path towards examining the materials structure property relationships on the single-impurity and atomic-configuration levels. Lacking, however, are the statistics-based approaches for cross-correlation of structure and property variables obtained in different information channels of the STEM and SPM experiments. Here we have designed an approach based on a combination of sliding window Fast Fourier Transform, Pearson correlation matrix, linear and kernel canonical correlation, to study a relationship between lattice distortions and electron scattering from the SPM data on graphene with defects. Our analysis revealed that the strength of coupling to strain is altered between different scattering channels which can explain coexistence of several quasiparticle interference patterns in the nanoscale regions of interest. In addition, the application of the kernel functions allowed us extracting a non-linear component of the relationship between the lattice strain and scattering intensity in graphene. Lastly, the outlined approach can be further utilized to analyzing correlations in various multi-modalmore » imaging techniques where the information of interest is spatially distributed and has usually a complex multidimensional nature.« less
Authors:
 [1] ;  [2] ;  [2] ;  [2] ;  [1] ;  [1]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  2. Tokyo Institute of Technology, Tokyo (Japan)
Publication Date:
OSTI Identifier:
1334464
Grant/Contract Number:
AC05-00OR22725
Type:
Accepted Manuscript
Journal Name:
Nanotechnology
Additional Journal Information:
Journal Volume: 27; Journal Issue: 49; Journal ID: ISSN 0957-4484
Publisher:
IOP Publishing
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), Basic Energy Sciences (BES) (SC-22)
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE scanning probe microscopy; direct data mining; graphene; correlative analysis