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Fabrication of Gate-tunable Graphene Devices for Scanning Tunneling Microscopy Studies with Coulomb Impurities

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Low-energy electron reflectivity from graphene: first-principles computations and approximate models.

R M Feenstra¹, M Widom

¹Department of Physics, Carnegie Mellon University, Pittsburgh, PA 15213, USA. feenstra@cmu.edu

Ultramicroscopy

|March 20, 2013

Summary

A new computational method calculates electron reflectivity from surfaces, revealing key energy bands in multilayer graphene. This method accurately predicts electron states, aiding in understanding graphene

Keywords:

Electron reflectivity Graphene Low-energy electron microscopy Surface

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Area of Science:

Computational Physics
Materials Science
Surface Science

Background:

Understanding electron behavior at material surfaces is crucial for electronics.
Low-energy electron reflectivity provides insights into surface electronic structure.
Graphene's unique electronic properties make it a key material for advanced applications.

Purpose of the Study:

To develop a first-principles computational method for calculating low-energy electron reflectivity.
To apply this method to multilayer graphene systems.
To investigate the electronic structure and surface states of graphene using this novel approach.

Main Methods:

Developed a computational method based on first-principles electronic structure calculations.
Applied the method to free-standing multilayer graphene slabs.
Constructed a localized tight-binding model for comparison and validation.

Main Results:

Identified two distinct bands of reflectivity minima in multilayer graphene (0-8 eV and 14-22 eV).
Observed n-1 reflectivity zeros per band for an n-layer graphene slab, corresponding to transmission resonances.
Discovered two additional image-potential states near the vacuum level, totaling 2n states.

Conclusions:

The developed computational method accurately predicts electron reflectivity and surface states.
The tight-binding model effectively reproduces the results from first-principles calculations.
This work provides a powerful tool for studying electron-surface interactions in layered materials like graphene.