Abstract
Heat transport in glasses over a wide temperature range is critical for applications in gate dielectrics and thermal insulators but remains poorly understood due to the challenges in modeling vibrational anharmonicity and configurational dynamics across the glass transition. Recent predictions show an unusual decrease in thermal conductivity (κ) with temperature in amorphous hafnia (a-HfO(2)), contrasting with the typical trend in glasses. Using molecular dynamics with a machine-learning-based neuroevolution potential, we compute κ of a-HfO(2) from 50 K to 2000 K. At low temperatures, the Wigner transport equation captures both anharmonicity and quantum statistics. Above 1200 K, atomic diffusion invalidates the quasiparticle picture, and we resort to the Green-Kubo method to capture convective transport. We further extend the Wigner transport equation to supercooled a-HfO(2), revealing the crucial role of low-frequency modes in facilitating heat transport. The computed κ, based on both Green-Kubo and Wigner transport theories, increases continuously with temperature up to 2000 K.