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

M Ziatdinov, O Dyck, X Li, BG Sumpter, S Jesse… - Science …, 2019 - science.org
Science advances, 2019science.org
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 …
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.
AAAS
以上显示的是最相近的搜索结果。 查看全部搜索结果