An ab initio dataset of size-dependent effective thermal conductivity for advanced technology transistors
Han Xie(谢涵)1,2, Ru Jia(贾如)3, Yonglin Xia(夏涌林)3, Lei Li(李磊)1, Yue Hu(胡跃)4, Jiaxuan Xu(徐家璇)3, Yufei Sheng(盛宇飞)3, Yuanyuan Wang(王元元)1,5,†, and Hua Bao(鲍华)6,‡
1 School of Energy and Materials, Shanghai Polytechnic University, Shanghai 201209, China; 2 Institute of Integrated Circuits, Shanghai Polytechnic University, Shanghai 201209, China; 3 University of Michigan-Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai 200240, China; 4 CTG Wuhan Science and Technology Innovation Park, China Three Gorges Corporation, Wuhan 430010, China; 5 Shanghai Thermophysical Properties Big Data Professional Technical Service Platform, Shanghai Polytechnic University, Shanghai 201209, China; 6 Global Institute of Future Technology, Shanghai Jiao Tong University, Shanghai 200240, China
Abstract As the size of transistors shrinks and power density increases, thermal simulation has become an indispensable part of the device design procedure. However, existing works for advanced technology transistors use simplified empirical models to calculate effective thermal conductivity in the simulations. In this work, we present a dataset of size-dependent effective thermal conductivity with electron and phonon properties extracted from ab initio computations. Absolute in-plane and cross-plane thermal conductivity data of eight semiconducting materials (Si, Ge, GaN, AlN, 4H-SiC, GaAs, InAs, BAs) and four metallic materials (Al, W, TiN, Ti) with the characteristic length ranging from 5 nm to 50 nm have been provided. Besides the absolute value, normalized effective thermal conductivity is also given, in case it needs to be used with updated bulk thermal conductivity in the future.
Fund: Project supported by the National Key R&D Project from Ministry of Science and Technology of China (Grant No. 2022YFA1203100), the National Natural Science Foundation of China (Grant No. 52122606), and the funding from Shanghai Polytechnic University.
Corresponding Authors:
Yuanyuan Wang, Hua Bao
E-mail: wangyuanyuan@sspu.edu.cn;hua.bao@sjtu.edu.cn
Cite this article:
Han Xie(谢涵), Ru Jia(贾如), Yonglin Xia(夏涌林), Lei Li(李磊), Yue Hu(胡跃), Jiaxuan Xu(徐家璇), Yufei Sheng(盛宇飞), Yuanyuan Wang(王元元), and Hua Bao(鲍华) An ab initio dataset of size-dependent effective thermal conductivity for advanced technology transistors 2025 Chin. Phys. B 34 046501
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