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 ${\mathrm{SiO}}_2$ remains unknown. Here, we calculate the lattice thermal conductivities of seifertite and pyrite-type ${\mathrm{SiO}}_2$ 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 ab-initio-level accuracy. To demonstrate our methodology, we also compute the thermal conductivity using the phonon quasiparticle approach combined with the Wigner transport equation (WTE). Comparison with the Green-Kubo results allows us to quantify the particlelike and wavelike contributions and to infer a possible additional contribution from overdamped vibrational modes that lie beyond the phonon quasiparticle framework. Overall, the Green-Kubo method predicts up to 22% higher thermal conductivity as it fully captures heat transport channels even at high temperatures. The 19% reduction in thermal conductivity across the phase transition from seifertite to the pyrite-type phase suggests the potential formation of a thermally resistive layer in the mantle of super-Earths.

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• Earth's interior
• Interatomic & molecular potentials
• Lattice thermal conductivity
• Phonons
• Extrasolar planets
• Density functional calculations
• Machine learning