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Ultra-efficient and parameter-free computation of submicron thermal transport with phonon Boltzmann transport equation

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摘要 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the thermal conductivity of thermoelectric materials.At the submicron scale,the macroscopic heat diffusion equation is no longer valid and the phonon Boltzmann transport equation(BTE)becomes the governing equation for thermal transport.However,previous thermal simulations based on the phonon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.
出处 《Fundamental Research》 CAS CSCD 2024年第4期907-915,共9页 自然科学基础研究(英文版)
基金 We thank Minhua Wen,Shenpeng Wang,and Yongzhi Liu from Shanghai Jiao Tong University for valuable help with parallelization.We thank Dr.Chuang Zhang from Southern University of Science and Technology for valuable discussions on the synthetic iterative method.We thank Dr.Saeid Zahiri from Petrosazan Pasargad Asia,Yucheng Shi from the University of Chicago,Xinyue Han from Carnegie Mellon University and Ziyou Wu from the University of Michigan for valuable help in developing the code.Y.H.and H.B.acknowledge the support by the National Natural Science Foundation of China(52122606).The computations in this paper were run on theπ2.0 cluster supported by the Center for High Performance Computing at Shanghai Jiao Tong University.
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