Thermal conductivity of seifertite and pyrite-type SiO$_2$: A comparative study

TL;DR

This study calculates and compares the lattice thermal conductivities of seifertite and pyrite-type SiO2 using advanced molecular dynamics simulations with machine learning potentials, revealing significant differences relevant to planetary science.

Contribution

It introduces a novel methodology combining Green-Kubo MD simulations with machine learning potentials for accurate thermal conductivity prediction of SiO2 phases.

Findings

Green-Kubo method predicts up to 119% higher thermal conductivity than phonon quasiparticle approach.

Thermal conductivity decreases by 19% across the phase transition from seifertite to pyrite-type SiO2.

Results suggest a potential thermally insulating layer in super-Earth mantles.

Abstract

Thermal conductivity is a fundamental material property that plays a crucial role in understanding the dynamics and evolution of planetary interiors. Despite its importance, the thermal conductivity of seifertite and pyrite-type SiO$_2$ remains unknown. Here, we calculate the lattice thermal conductivities of seifertite and pyrite-type SiO$_2$ using the Green-Kubo method based on molecular dynamics (MD) simulations driven by two machine learning potentials (MLPs) constructed from the SCAN and PBEsol exchange-correlation functionals, with $\textit{ab initio}$-level accuracy. To demonstrate our methodology, we also compute thermal conductivities using the phonon quasiparticle approach for comparison. Overall, the Green-Kubo method predicts up to 119 % higher thermal conductivity with a temperature dependence close to $T^{-1}$, as it fully captures diffusion-like phonons at high temperatures that are missed by the phonon quasiparticle approach. The 19 % reduction in thermal conductivity across the phase transition from seifertite to the pyrite-type phase suggests the potential formation of a thermally insulating layer in the mantle of super-Earths.