Large-scale simulation of thermal conductivity in CaSiO3 perovskite with neuroevolution potential

Abstract

Lattice thermal conductivity (klat) of mantle minerals is a key factor in determining the Earth's energy budget and influences its dynamic processes. Here, we trained a neuroevolution machine learning potential for CaSiO3 perovskite (CaPv), the third most abundant mineral of the lower mantle, to investigate the klat of pyrolitic aggregates at the core–mantle boundary (CMB). We show that the klat of two types of pyrolitic aggregates has increased by 7% and 5% upon the addition of CaPv, demonstrating its significance in shaping the thermal structure of Earth's interior. Considering other mantle minerals and iron content, as well as the global distribution of temperature, we evaluated the heat flow across the CMB to be 7.98 ± 0.4 TW. The estimated heat flow is inconsistent with the value derived from the Fe alloy, which might suggest the presence of a thermally or chemically stratified layer atop the outer core.