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Plasmonic eigenmodes in individual and bow-tie graphene nanotriangles
Weihua Wang1, Thomas Christensen1, Antti-Pekka Jauho2
11] Center for Nanostructured Graphene (CNG), Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark [2] Department of Photonics Engineering, Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark.
Quantum effects in nanoscale graphene plasmonics are revealed. Edge termination (armchair vs. zigzag) significantly alters quantum plasmon frequencies and spectral features, even in 20nm structures, challenging classical models.
Area of Science:
- Condensed Matter Physics
- Materials Science
- Nanotechnology
Background:
- Classical electrodynamics models nanostructured graphene using computationally intensive 3D simulations.
- Efficient modeling of graphene's optical properties is crucial for nanotechnology applications.
Purpose of the Study:
- To develop an efficient 2D electrostatic approach for modeling nanostructured graphene.
- To investigate quantum effects on plasmon modes in graphene triangles and dimers.
- To compare classical and quantum mechanical treatments of graphene's optical response.
Main Methods:
- Developed a 2D electrostatic approach restricted to the graphene sheet.
- Performed tight-binding calculations with random-phase approximation for quantum effects.
- Investigated 20nm equilateral graphene triangles and dimers, analyzing optical response classically and quantum mechanically.
Main Results:
- Quantum plasmon frequencies show blueshifts for armchair edges and redshifts for zigzag edges, unlike classical models.
- Zigzag edges exhibit unique spectral features linked to electronic edge states.
- Plasmon hybridization in dimers shows energy splitting, strongest classically, reduced for armchair, and minimal for zigzag edges.
Conclusions:
- Even small 20nm graphene structures exhibit distinct quantum plasmonic features.
- Atomic-scale edge termination details significantly influence graphene's optical response.
- The proposed 2D electrostatic method offers an efficient alternative for modeling nanostructured graphene.
