Structure identification in high-resolution transmission electron microscopic images: an example on graphene

Area of Science:

• Materials Science
• Condensed Matter Physics
• Nanotechnology

Background:

• Understanding the link between microscopic structure and macroscopic properties is crucial for material systems.
• High-resolution transmission electron microscopy (HRTEM) provides atomic-level insights but manual analysis of large datasets is time-consuming.

Purpose of the Study:

• To develop an automated method for estimating atomic structure in two-dimensional (2D) materials.
• To reconstruct atom positions in graphene and analyze structural characteristics.

Main Methods:

• Automated atomic structure estimation using HRTEM image series.
• Extraction of lattice parameters in the frequency domain for initial atom positioning.
• Markov random field model simulation integrating image evidence and geometric priors for atom position refinement.
• Application of false discovery rate-controlled hypothesis testing for result interpretation.

Main Results:

• Successful reconstruction of carbon atom positions in graphene samples.
• Analysis of a pristine graphene sample revealed homogeneous carbon-carbon (C-C) bond lengths.
• Analysis of a graphene sample with a hole indicated regions of shorter C-C bond lengths, suggesting strain or buckling.

Conclusions:

• The developed method automates atomic structure analysis in 2D materials, significantly reducing analysis time.
• The technique accurately identifies structural variations, such as strain or buckling, in graphene.
• The method's precision is validated on simulated structures and experimental graphene samples.