Large tunability of lattice thermal conductivity of monolayer silicene via mechanical strain

Han Xie, Tao Ouyang, Éric Germaneau, Guangzhao Qin, Ming Hu, and Hua Bao
Phys. Rev. B 93, 075404 – Published 2 February 2016

Abstract

Strain engineering is one of the most promising and effective routes toward continuously tuning the electronic and optic properties of materials, while thermal properties are generally believed to be insensitive to mechanical strain. In this paper, the strain-dependent thermal conductivity of monolayer silicene under uniform biaxial tension is computed by solving the phonon Boltzmann transport equation with interatomic force constants extracted from first-principles calculations. Unlike the commonly believed understanding that thermal conductivity only slightly decreases with increased tensile strain for bulk materials, it is found that the thermal conductivity of silicene can increase dramatically with strain. Depending on the size, the maximum thermal conductivity of strained silicene can be a few times higher than that of the unstrained case. Such an unusual strain dependence is mainly attributed to the dramatic enhancement in the acoustic phonon lifetime. Such enhancement plausibly originates from the flattening of the buckling of the silicene structure upon stretching, which is unique for silicene as compared with other common two-dimensional materials. Our findings offer perspectives on modulating the thermal properties of low-dimensional structures for applications such as thermoelectrics, thermal circuits, and nanoelectronics.

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  • Received 2 September 2015
  • Revised 2 January 2016

DOI:https://doi.org/10.1103/PhysRevB.93.075404

©2016 American Physical Society

Physics Subject Headings (PhySH)

Condensed Matter, Materials & Applied Physics

Authors & Affiliations

Han Xie1, Tao Ouyang2, Éric Germaneau3, Guangzhao Qin2, Ming Hu2,4,*, and Hua Bao1,†

  • 1University of Michigan–Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai 200240, China
  • 2Institute of Mineral Engineering, Division of Materials Science and Engineering, Faculty of Georesources and Materials Engineering, RWTH Aachen University, Aachen 52064, Germany
  • 3Center for High Performance Computing, Shanghai Jiao Tong University, Shanghai 200240, China
  • 4Aachen Institute for Advanced Study in Computational Engineering Science (AICES), RWTH Aachen University, Aachen 52062, Germany

  • *Author to whom correspondence should be addressed: hum@ghi.rwth-aachen.de
  • Author to whom correspondence should be addressed: hua.bao@sjtu.edu.cn

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Issue

Vol. 93, Iss. 7 — 15 February 2016

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