Optimizing thermal transport in graphene nanoribbon based on phonon resonance hybridization

Xiao Wan, Dengke Ma, Dongkai Pan, Lina Yang, Nuo Yang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

40 Citations (Scopus)

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 nanopillared 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 increase of number for nanopillared structure, which is severed as the 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.

Original languageEnglish
Article number100445
JournalMaterials Today Physics
Volume20
DOIs
Publication statusPublished - Sept 2021

Keywords

  • Atomic Green's function
  • Bayesian optimization
  • Graphene nanoribbon
  • Phonon local resonance
  • Thermal transport property

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