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Quantitative annular dark-field imaging of single-layer graphene
Shunsuke Yamashita1, Shogo Koshiya2, Kazuo Ishizuka3
1Surface Physics and Structure Unit, National Institute for Materials Science, 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan Department of Applied Chemistry, Kyushu University, 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan yamashita.shunsuke@nims.go.jp kimoto.koji@nims.go.jp.
This study presents a new quantification procedure for annular dark-field (ADF) imaging. This method enables accurate layer counting in graphene specimens by converting ADF images into quantitative data.
Area of Science:
- Materials Science
- Microscopy
- Condensed Matter Physics
Background:
- Annular dark-field (ADF) imaging is a powerful technique for materials characterization.
- Quantitative analysis in ADF imaging is crucial for high-sensitivity observations.
- Existing methods may not fully capture the nonlinear response of ADF systems.
Purpose of the Study:
- To develop and present a robust quantification procedure for annular dark-field (ADF) imaging.
- To enable accurate measurement of scattering intensity normalized by incident probe current.
- To apply the procedure for precise layer counting in graphene.
Main Methods:
- Developed an empirical equation to convert raw ADF images to quantitative ADF images.
- Incorporated the nonlinear response of the ADF imaging system into the quantification procedure.
- Precisely measured the inner and outer angles of the ADF detector for accurate analysis.
Main Results:
- The quantification procedure successfully implemented the nonlinear response of the ADF system.
- Quantitative ADF images of graphene specimens (1-4 layers) were obtained.
- The measured quantitative contrast of ADF images showed agreement with simulated images.
Conclusions:
- The developed quantification procedure provides accurate and reliable quantitative ADF imaging.
- This method allows for direct and precise counting of graphene layers.
- The procedure is critical for high-sensitivity observations and quantitative analysis in materials science.
