Session: K9-10: NANOSCALE THERMAL TRANSPORT MODELING AND MACHINE LEARNING II

Paper Number: 138664

138664 - Physics-Integrated Hybrid Machine Learning Model for Phonon Bte 

Abstract: 

In recent times, the semiconductor industry has experienced significant progress, driving the demand for faster and more energy-efficient electronic devices. This development necessitates the miniaturization of transistors, leading to elevated hot spot temperatures which can adversely affect device longevity and reliability. Accurately predicting these temperatures is essential for transistor design optimization. At the nanoscale, traditional heat transfer models like Fourier's law are inadequate, and the Phonon Boltzmann Transport Equation (BTE) becomes essential for precise temperature profiling. However, BTE's nonlinear and high-dimensional nature poses substantial challenges for traditional numerical solvers, especially when dealing with complex heat transfer in multi-material systems involving different geometries and interfaces. To address these challenges, this talk introduces a novel approach utilizing a Physics-integrated Neural Differentiable (PiNDiff) network. This innovative model is designed to preserve the mathematical structures inherent in the physics of BTE and the associated boundary conditions at interfaces. The PiNDiff network effectively integrates machine learning with physical laws, creating a hybrid model that not only navigates the complexities of BTE but also allows for the extraction of effective thermal conductivity (TC) from the data. This approach represents a significant advancement in the field of nanoscale heat transfer, demonstrating the potential of machine learning to solve complex, high-dimensional thermal transport problems.

Presenting Author: Wenjie Shang University of Notre Dame

Presenting Author Biography: Wenjie Shang is a 4th year graduate student working with Prof. Tengfei Luo in the deparment of Aerospace and Mechanical Engineering at University of Notre Dame.

Authors:

Wenjie Shang University of Notre Dame
Bo Zhang University of Notre Dame
Jiahang Zhou University of Notre Dame
Jyoti Panda University of Notre Dame
Tengfei Luo University of Notre Dame
Jianxun Wang University of Notre Dame