# Phonon thermal transport in 2H, 4H and 6H silicon carbide from first principles

## TL;DR

This study uses first-principles calculations to analyze phonon-mediated thermal conductivity in different silicon carbide polytypes, revealing how structural variations influence heat transport properties.

## Contribution

It provides a detailed ab initio analysis of thermal conductivities in 2H, 4H, and 6H SiC, elucidating the effects of phonon branches and scattering mechanisms.

## Key findings

- Thermal conductivity decreases with increasing polytype number.
- In-plane conductivity exceeds cross-plane conductivity across temperatures.
- Electron scattering minimally affects thermal transport at typical conditions.

## Abstract

Silicon carbide (SiC) is a wide band gap semiconductor with a variety of industrial applications. Among its many useful properties is its high thermal conductivity, which makes it advantageous for thermal management applications. In this paper we present \textit{ab initio} calculations of the in-plane and cross-plane thermal conductivities, $\kappa_{\text{in}}$ and $\kappa_{\text{out}}$, of three common hexagonal polytypes of SiC: 2H, 4H and 6H. The phonon Boltzmann transport equation is solved iteratively using as input interatomic force constants determined from density functional theory. Both $\kappa_{\text{in}}$ and $\kappa_{\text{out}}$ decrease with increasing $n$ in $n$H SiC because of additional low-lying optic phonon branches. These optic branches are characterized by low phonon group velocities, and they increase the phase space for phonon-phonon scattering of acoustic modes. Also, for all $n$, $\kappa_{\text{in}}$ is found to be larger than $\kappa_{\text{out}}$ in the temperature range considered. At electron concentrations present in experimental samples, scattering of phonons by electrons is shown to be negligible except well below room temperature where it can lead to a significant reduction of the lattice thermal conductivity. This work highlights the power of \textit{ab initio} approaches in giving quantitative, predictive descriptions of thermal transport in materials. It helps explain the qualitative disagreement that exists among different sets of measured thermal conductivity data and provides information of the relative quality of samples from which measured data was obtained.