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Title: Identifying local structural states in atomic imaging by computer vision

The availability of atomically resolved imaging modalities enables an unprecedented view into the local structural states of materials, which manifest themselves by deviations from the fundamental assumptions of periodicity and symmetry. Consequently, approaches that aim to extract these local structural states from atomic imaging data with minimal assumptions regarding the average crystallographic configuration of a material are indispensable to advances in structural and chemical investigations of materials. Here, we present an approach to identify and classify local structural states that is rooted in computer vision. This approach introduces a definition of a structural state that is composed of both local and non-local information extracted from atomically resolved images, and is wholly untethered from the familiar concepts of symmetry and periodicity. Instead, this approach relies on computer vision techniques such as feature detection, and concepts such as scale-invariance. We present the fundamental aspects of local structural state extraction and classification by application to simulated scanning transmission electron microscopy images, and analyze the robustness of this approach in the presence of common instrumental factors such as noise, limited spatial resolution, and weak contrast. Finally, we apply this computer vision-based approach for the unsupervised detection and classification of local structural states in anmore » experimental electron micrograph of a complex oxides interface, and a scanning tunneling micrograph of a defect engineered multilayer graphene surface.« less
Authors:
ORCiD logo [1] ;  [1] ;  [2] ;  [3]
  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)
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Materials Sciences and Technology Division
  3. 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). Materials Sciences and Technology Division
Publication Date:
OSTI Identifier:
1330726
Grant/Contract Number:
AC05-00OR22725
Type:
Published Article
Journal Name:
Advanced Structural and Chemical Imaging
Additional Journal Information:
Journal Volume: 2; Journal Issue: 1; Journal ID: ISSN 2198-0926
Publisher:
Springer
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:
74 ATOMIC AND MOLECULAR PHYSICS