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Published on: July 24, 2015
Mapping of local electrical properties in epitaxial graphene using electrostatic force microscopy
Tim Burnett1, Rositza Yakimova, Olga Kazakova
1National Physical Laboratory, Teddington, TW11 0LW, United Kingdom.
Electrostatic force microscopy (EFM) successfully characterized epitaxial graphene on silicon carbide, even with surface contaminants. A new EFM spectroscopy method precisely distinguishes graphene layers and domains, aiding imaging optimization.
Area of Science:
- Materials Science
- Surface Science
- Nanotechnology
Background:
- Epitaxial graphene on silicon carbide (SiC) is a promising material for electronics.
- Characterizing graphene layers, especially on SiC, is challenging due to surface adsorbates.
- Local electrical properties are crucial for understanding graphene device performance.
Purpose of the Study:
- To present local electrical characterization of epitaxial graphene on 4H-SiC(0001) using Electrostatic Force Microscopy (EFM).
- To demonstrate EFM's capability in identifying graphene layers despite topographical hindrances from adsorbates.
- To introduce and validate a novel EFM spectroscopy technique for distinguishing graphene domains.
Main Methods:
- Utilized Electrostatic Force Microscopy (EFM) for imaging.
- Performed characterization under ambient conditions and at elevated temperatures.
- Developed and applied a new EFM spectroscopy method measuring EFM phase versus DC bias.
Main Results:
- EFM effectively identified graphene with varying layer numbers on 4H-SiC(0001).
- Adsorbates on the surface did not prevent successful graphene layer identification via EFM.
- The novel EFM spectroscopy rigorously distinguished different graphene domains.
- Optimized EFM imaging parameters were facilitated by the new technique.
Conclusions:
- EFM is a powerful tool for local electrical characterization of epitaxial graphene on SiC.
- The developed EFM spectroscopy offers a robust method for differentiating graphene domains.
- This work facilitates improved quality control and device optimization for graphene-based electronics.
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