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Title: Building and exploring libraries of atomic defects in graphene: Scanning transmission electron and scanning tunneling microscopy study

Abstract

The presence and configurations of defects are primary components determining materials functionality. Their population and distribution are often nonergodic and dependent on synthesis history, and therefore rarely amenable to direct theoretical prediction. Here, dynamic electron beam–induced transformations in Si deposited on a graphene monolayer are used to create libraries of possible Si and carbon vacancy defects. Deep learning networks are developed for automated image analysis and recognition of the defects, creating a library of (meta) stable defect configurations. Density functional theory is used to estimate atomically resolved scanning tunneling microscopy (STM) signatures of the classified defects from the created library, allowing identification of several defect types across imaging platforms. This approach allows automatic creation of defect libraries in solids, exploring the metastable configurations always present in real materials, and correlative studies with other atomically resolved techniques, providing comprehensive insight into defect functionalities.

Authors:
ORCiD logo [1]; ORCiD logo [1];  [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]
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  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22). Materials Sciences & Engineering Division
OSTI Identifier:
1607267
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Science Advances
Additional Journal Information:
Journal Volume: 5; Journal Issue: 9; Journal ID: ISSN 2375-2548
Publisher:
AAAS
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE

Citation Formats

Ziatdinov, Maxim, Dyck, Ondrej, Li, Xin, Sumpter, Bobby G., Jesse, Stephen, Vasudevan, Rama K., and Kalinin, Sergei V. Building and exploring libraries of atomic defects in graphene: Scanning transmission electron and scanning tunneling microscopy study. United States: N. p., 2019. Web. doi:10.1126/sciadv.aaw8989.
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Ziatdinov, Maxim, Dyck, Ondrej, Li, Xin, Sumpter, Bobby G., Jesse, Stephen, Vasudevan, Rama K., & Kalinin, Sergei V. Building and exploring libraries of atomic defects in graphene: Scanning transmission electron and scanning tunneling microscopy study. United States. https://doi.org/10.1126/sciadv.aaw8989
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Ziatdinov, Maxim, Dyck, Ondrej, Li, Xin, Sumpter, Bobby G., Jesse, Stephen, Vasudevan, Rama K., and Kalinin, Sergei V. Fri . "Building and exploring libraries of atomic defects in graphene: Scanning transmission electron and scanning tunneling microscopy study". United States. https://doi.org/10.1126/sciadv.aaw8989. https://www.osti.gov/servlets/purl/1607267.
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@article{osti_1607267,
title = {Building and exploring libraries of atomic defects in graphene: Scanning transmission electron and scanning tunneling microscopy study},
author = {Ziatdinov, Maxim and Dyck, Ondrej and Li, Xin and Sumpter, Bobby G. and Jesse, Stephen and Vasudevan, Rama K. and Kalinin, Sergei V.},
abstractNote = {The presence and configurations of defects are primary components determining materials functionality. Their population and distribution are often nonergodic and dependent on synthesis history, and therefore rarely amenable to direct theoretical prediction. Here, dynamic electron beam–induced transformations in Si deposited on a graphene monolayer are used to create libraries of possible Si and carbon vacancy defects. Deep learning networks are developed for automated image analysis and recognition of the defects, creating a library of (meta) stable defect configurations. Density functional theory is used to estimate atomically resolved scanning tunneling microscopy (STM) signatures of the classified defects from the created library, allowing identification of several defect types across imaging platforms. This approach allows automatic creation of defect libraries in solids, exploring the metastable configurations always present in real materials, and correlative studies with other atomically resolved techniques, providing comprehensive insight into defect functionalities.},
doi = {10.1126/sciadv.aaw8989},
journal = {Science Advances},
number = 9,
volume = 5,
place = {United States},
year = {2019},
month = {9}
}
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https://doi.org/10.1126/sciadv.aaw8989
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    Works referencing / citing this record:

    Atomic Mechanisms for the Si Atom Dynamics in Graphene: Chemical Transformations at the Edge and in the Bulk
    journal, November 2019

    • Ziatdinov, Maxim; Dyck, Ondrej; Jesse, Stephen
    • Advanced Functional Materials, Vol. 29, Issue 52
    • DOI: 10.1002/adfm.201904480
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