Tunable Goos-Hänchen Shift Surface Plasmon Resonance Sensor Based on Graphene-hBN Heterostructure

Area of Science:

• Optoelectronics
• Materials Science
• Nanotechnology

Background:

• Infrared sensors require high sensitivity and stability for various applications.
• Graphene-hexagonal boron nitride (hBN) heterostructures offer unique electronic and optical properties.
• Enhancing the Goos-Hänchen (GH) shift is a key strategy for improving sensor performance.

Purpose of the Study:

• To theoretically investigate a bimetallic sensor based on a graphene-hBN heterostructure.
• To explore methods for enhancing the Goos-Hänchen (GH) shift in the infrared band.
• To achieve high sensitivity and stability in infrared sensing applications.

Main Methods:

• Theoretical study of a bimetallic sensor utilizing a graphene-hBN heterostructure.
• Analysis of the Goos-Hänchen (GH) shift by adjusting sensor parameters.
• Optimization of Fermi level, graphene layers, and hBN thickness.

Main Results:

• A Goos-Hänchen (GH) shift of 182.09 λ was achieved by tuning sensor parameters.
• A high sensitivity of 2.02 × 10^5 λ/RIU was obtained under specific conditions (monolayer graphene, 20 nm gold, 15 nm silver, 492 nm hBN).
• The designed heterogeneous infrared sensor demonstrates high sensitivity and strong stability.

Conclusions:

• The theoretical study provides a foundation for designing new high-sensitivity infrared sensors.
• Graphene-hBN heterostructures are promising for advanced infrared sensing technologies.
• Optimizing material parameters is crucial for maximizing sensor performance.