Advancing Graphene Imaging for Clear Identification of Lattice Defects: The Application of Revolve Sphere Levelling to Scanning Tunnelling Microscopy Images

Application of revolve sphere levelling (RSL) as a practical and effective image processing tool for enhancing scanning tunnelling microscopy (STM) images of graphene atomic lattices is presented. Low-cost, ambient, and non-invasive STM methods overcome limitations of traditional imaging methods like scanning transmission electron microscopy (STEM) and transmission electron microscopy (TEM) that can introduce or alter defects in graphene. Utilizing high-quality graphene synthesized via Paragraf's patented Metal-Organic Chemical Vapor Deposition (MOCVD) method, RSL, which is easily implemented via the Gwyddion software package, effectively highlights the hexagonal lattice structure and specific defect structures. This provides clarity of the atomic structure that traditional methods struggle to achieve. This research emphasizes the utility of RSL in materials science for defect identification in graphene, and points to future research in optimizing RSL for a broader range of defects and applications in other 2D materials.

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Publication Details

Journal
ACS Omega
Published
2024-10-14
DOI
https://doi.org/10.1021/acsomega.4c04675
Citations
2
Primary Topic
Graphene research and applications
Type
article
Field-Weighted Citation Impact
0.23
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article

Advancing Graphene Imaging for Clear Identification of Lattice Defects: The Application of Revolve Sphere Levelling to Scanning Tunnelling Microscopy Images

Yiwei Sun, Ross Griffin, Lok Yi Lee, D. Bandyopadhyay
2 citations
ACS Omega
Graphene research and applications
0.23
article

Advancing Graphene Imaging for Clear Identification of Lattice Defects: The Application of Revolve Sphere Levelling to Scanning Tunnelling Microscopy Images

Yiwei Sun, Ross Griffin, Lok Yi Lee, D. Bandyopadhyay
article en
2 citations

Abstract

Application of revolve sphere levelling (RSL) as a practical and effective image processing tool for enhancing scanning tunnelling microscopy (STM) images of graphene atomic lattices is presented. Low-cost, ambient, and non-invasive STM methods overcome limitations of traditional imaging methods like scanning transmission electron microscopy (STEM) and transmission electron microscopy (TEM) that can introduce or alter defects in graphene. Utilizing high-quality graphene synthesized via Paragraf's patented Metal-Organic Chemical Vapor Deposition (MOCVD) method, RSL, which is easily implemented via the Gwyddion software package, effectively highlights the hexagonal lattice structure and specific defect structures. This provides clarity of the atomic structure that traditional methods struggle to achieve. This research emphasizes the utility of RSL in materials science for defect identification in graphene, and points to future research in optimizing RSL for a broader range of defects and applications in other 2D materials.

ACS OmegaVol. 9(43)
Rutherford Appleton Laboratory (GB), École Polytechnique Fédérale de Lausanne (CH)
Climate action
Openalex Percentile: Top 51%
Graphene research and applications
0.23
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