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Updated: Jun 16, 2025

Characterization of Thermal Transport in One-dimensional Solid Materials
Published on: January 26, 2014
Ultra-efficient and parameter-free computation of submicron thermal transport with phonon Boltzmann transport
Yue Hu1, Yongxing Shen1, Hua Bao1
1University of Michigan-Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai 200240, China.
Abstract:
Understanding thermal transport at the submicron scale is crucial for engineering applications, especially in the thermal management of electronics and tailoring the thermal conductivity of thermoelectric materials. At the submicron scale, the macroscopic heat diffusion equation is no longer valid and the phonon Boltzmann transport equation (BTE) becomes the governing equation for thermal transport. However, previous thermal simulations based on the phonon BTE have two main limitations: relying on empirical parameters and prohibitive computational costs. Therefore, the phonon BTE is commonly used for qualitatively studying the non-Fourier thermal transport phenomena of toy problems. In this work, we demonstrate an ultra-efficient and parameter-free computational method of the phonon BTE to achieve quantitatively accurate thermal simulation for realistic materials and devices. By properly integrating the phonon properties from first-principles calculations, our method does not rely on empirical material properties input. It can be generally applicable for different materials and the predicted results can match well with experimental results. Moreover, by developing a suitable ensemble of advanced numerical algorithms, our method exhibits superior numerical efficiency. The full-scale (from ballistic to diffusive) thermal simulation of a 3-dimensional fin field-effect transistor with 13 million degrees of freedom, which is prohibitive for existing phonon BTE solvers even on supercomputers, can now be completed within two hours on a single personal computer. Our method makes it possible to achieve the predictive design of realistic nanostructures for the desired thermal conductivity. It also enables accurately resolving the temperature profiles at the transistor level, which helps in better understanding the self-heating effect of electronics.
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