Thermal transport properties of two-dimensional boron dichalcogenides from a first-principles and machine learning approach  

作　　者：邱占均 胡晏箫 李顶 胡涛 肖红 冯春宝 李登峰 Zhanjun Qiu;Yanxiao Hu;Ding Li;Tao Hu;Hong Xiao;Chunbao Feng;Dengfeng Li(School of Science,Chongqing University of Posts and Telecommunications,Chongqing 400065,China;Institute for Advanced Sciences,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)

机构地区：[1]School of Science,Chongqing University of Posts and Telecommunications,Chongqing 400065,China [2]Institute for Advanced Sciences,Chongqing University of Posts and Telecommunications,Chongqing 400065,China

出　　处：《Chinese Physics B》2023年第5期7-13,共7页中国物理B（英文版）

基　　金：Scientific and Technological Research of Chongqing Municipal Education Commission(Grant No.KJZD-K202100602);the funding of Institute for Advanced Sciences of Chongqing University of Posts and Telecommunications(Grant No.E011A2022326)。

摘　　要：The investigation of thermal transport is crucial to the thermal management of modern electronic devices.To obtain the thermal conductivity through solution of the Boltzmann transport equation,calculation of the anharmonic interatomic force constants has a high computational cost based on the current method of single-point density functional theory force calculation.The recent suggested machine learning interatomic potentials(MLIPs)method can avoid these huge computational demands.In this work,we study the thermal conductivity of two-dimensional MoS_(2)-like hexagonal boron dichalcogenides(H-B_(2)VI_(2);V I=S,Se,Te)with a combination of MLIPs and the phonon Boltzmann transport equation.The room-temperature thermal conductivity of H-B_(2)S_(2)can reach up to 336 W·m^(-1)·K^(-1),obviously larger than that of H-B_(2)Se_(2)and H-B_(2)Te_(2).This is mainly due to the difference in phonon group velocity.By substituting the different chalcogen elements in the second sublayer,H-B_(2)VIV I′have lower thermal conductivity than H-B_(2)VI_(2).The room-temperature thermal conductivity of B2STe is only 11%of that of H-B_(2)S_(2).This can be explained by comparing phonon group velocity and phonon relaxation time.The MLIP method is proved to be an efficient method for studying the thermal conductivity of materials,and H-B_(2)S_(2)-based nanodevices have excellent thermal conduction.

关 键 词：boron dichalcogenides thermal conductivity machine learning interatomic potentials first-principles calculation 

分 类 号：O469[理学—凝聚态物理] TP181[理学—电子物理学]