Optimized phonon band discretization scheme for efficiently solving the non-gray Boltzmann transport equation

TL;DR

This paper introduces an improved phonon band discretization scheme that significantly reduces computational costs while maintaining high accuracy in solving the non-gray phonon Boltzmann transport equation for nanoscale thermal transport.

Contribution

The authors propose a novel band discretization method using mean free path domain subdivision and Gauss-Legendre quadrature, enabling accurate solutions with fewer phonon bands.

Findings

Achieves <1% error with fewer than 10 phonon bands

Reduces computational time and memory requirements

Applicable to multiple representative materials

Abstract

Phonon Boltzmann transport equation (BTE) is an important tool for studying the nanoscale thermal transport. Because phonons have a large spread in their properties, the non-gray (i.e. considering different phonon bands) phonon BTE is needed to accurately capture the nanoscale transport phenomena. However, BTE solvers generally require large computational cost. Non-gray modeling imposes significant additional complexity to the numerical simulations, which hinders the modeling of real nanoscale systems. In this work, we address this issue by a systematic investigation on the phonon band discretization scheme using real material properties of four representative materials, including silicon, gallium arsenide, diamond, and lead telluride. We find that the schemes used in previous studies require at least a few tens of bands to ensure the accuracy, which requires large computational costs. We then propose an improved band discretization scheme, in which we divide the mean free path domain into two subdomains, one on either side of the inflection point of the mean free path accumulated thermal conductivity and adopt the Gauss-Legendre quadrature for each subdomain. With this scheme, the solution of phonon BTE converges (error < 1%) with less than 10 phonon bands for all these materials. The proposed scheme allows to significantly reduce the time and memory consumption of the numerical BTE solver, which is an important step towards large-scale phonon BTE simulation for real materials.