Journal
MATERIALS TODAY PHYSICS
Volume 20, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.mtphys.2021.100445
Keywords
Graphene nanoribbon; Phonon local resonance; Thermal transport property; Atomic Green's function; Bayesian optimization
Funding
- National Key Research and Development Project of China [2018YFE0127800]
- National Natural Science Foundation of China [12005105]
- Fundamental Research Funds for the Central Universities [2019kfyRCPY045]
- Program for HUST Academic Frontier Youth Team
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In this study, phonon transport optimization in graphene nanoribbon was achieved by designing nanopillared nanostructures based on resonance hybridization. It was found that thermal conductance decreases non-monotonically with an increase in the number of nanopillared structures, blocking phonon transport. Insights into controlling phonon transport in nanostructures were provided through mode-analysis, calculations, and simulations.
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. (C) 2021 Elsevier Ltd. All rights reserved.
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