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

Journal Article · · Science Advances

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.

Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22). Materials Sciences & Engineering Division
Grant/Contract Number:
AC05-00OR22725
OSTI ID:
1607267
Journal Information:
Science Advances, Vol. 5, Issue 9; ISSN 2375-2548
Publisher:
AAASCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 55 works
Citation information provided by
Web of Science

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Cited By (2)