Optimizing Thermal Transport in Graphene Nanoribbon Based on Phonon Resonance Hybridization

TL;DR

This paper presents a method to optimize thermal transport in graphene nanoribbons by designing pillared nanostructures that leverage phonon resonance hybridization, achieving minimized thermal conductance through advanced computational techniques.

Contribution

It introduces a novel design of pillared nanostructures for graphene nanoribbons and combines Green's function with Bayesian optimization to control phonon transport.

Findings

Thermal conductance decreases non-monotonically with more pillared structures.

Resonator structures block phonon transport, reducing conductance.

Molecular dynamics simulations confirm the optimized design's effectiveness.

Abstract

As a critical way to modulate thermal transport in nanostructures, phonon resonance hybridization has become an issue of great concern in the field of phonon engineering. In this work, we optimized phonon transport across graphene nanoribbon and obtained minimized thermal conductance by means of designing pillared nanostructures based on resonance hybridization. Specifically, the optimization of thermal conductance was performed by the combination of atomic Green` s function and Bayesian optimization. Interestingly, it is found that thermal conductance decreases non-monotonically with the increasing of number for pillared structure, which is severed as resonator and blocks phonon transport. Further mode-analysis and atomic Green` s function calculations revealed that the anomalous tendency originates from decreased phonon transmission in a wide frequency range. Additionally, nonequilibrium molecular dynamics simulations are performed to verify the results with the consideration of high-order phonon scattering. This finding provides novel insights into the control of phonon transport in nanostructures.