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高阶非简谐性塑造了石墨烯中的声子流体动力学效应。

High-Order Anharmonicities Shape Phonon Hydrodynamic Effects in Graphene.

作者信息

Tur-Prats Jordi, Han Zherui, Beardo Albert, Ruan Xiulin, Alvarez F Xavier

机构信息

Departament de Física, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain.

School of Mechanical Engineering and the Birck Nanotechnology Center, Purdue University, West Lafayette, Indiana 47907-2088, United States.

出版信息

Nano Lett. 2025 Jul 23;25(29):11203-11209. doi: 10.1021/acs.nanolett.5c00855. Epub 2025 Jul 9.

DOI:10.1021/acs.nanolett.5c00855
PMID:40635367
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12291587/
Abstract

Prominent phonon hydrodynamic phenomena were predicted in graphene at low temperatures due to the abundance of momentum-conserving three-phonon interactions. Recent studies, however, have shown that higher-order interactions constitute an additional resistive channel that significantly reduces the thermal conductivity of this material. Here, we show that the occurrence of hydrodynamic effects in graphene is severely conditioned by four-phonon interactions. Contrary to conventional understanding, we first demonstrate that the collective limit assumption, in which the phonon distribution is fully correlated, is not adequate to understand the hydrodynamic transport mechanisms in graphene. Then we report the key hydrodynamic parameters, namely the nonlocal length and the heat flux relaxation time, and we show that they are significantly reduced if considering full anharmonicity. Finally, we discuss observable implications in a variety of experimental configurations and we critically review previous predictions on the necessary conditions for the manifestation of collective phonon behavior and phonon hydrodynamics.

摘要

由于存在大量动量守恒的三声子相互作用,在低温下的石墨烯中预测到了显著的声子流体动力学现象。然而,最近的研究表明,高阶相互作用构成了一个额外的电阻通道,显著降低了这种材料的热导率。在这里,我们表明,石墨烯中流体动力学效应的出现受到四声子相互作用的严重制约。与传统认识相反,我们首先证明,声子分布完全相关的集体极限假设不足以理解石墨烯中的流体动力学传输机制。然后我们报告了关键的流体动力学参数,即非局部长度和热流弛豫时间,并且我们表明,如果考虑完全非谐性,它们会显著降低。最后,我们讨论了在各种实验配置中可观测的影响,并批判性地回顾了先前关于集体声子行为和声子流体动力学表现的必要条件的预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86bb/12291587/ec0efeb5902e/nl5c00855_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86bb/12291587/256a854472d6/nl5c00855_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86bb/12291587/4fd264addf73/nl5c00855_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86bb/12291587/ec0efeb5902e/nl5c00855_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86bb/12291587/256a854472d6/nl5c00855_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86bb/12291587/4fd264addf73/nl5c00855_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86bb/12291587/ec0efeb5902e/nl5c00855_0003.jpg

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