loading page

Large-scale atomistic simulations of magnesium oxide exsolution driven by machine learning potentials: Implications for the early geodynamo
  • Jie Deng
Jie Deng
Princeton University

Corresponding Author:[email protected]

Author Profile


The precipitation of magnesium oxide (MgO) from the Earth’s core has been proposed as a potential energy source to power the geodynamo prior to the inner core solidification. Yet, the stable phase and exact amount of MgO exsolution remain elusive. Here we utilize an iterative learning scheme to develop a unified deep learning interatomic potential for the Mg-Fe-O system valid over a wide pressure-temperature range. This potential enables direct, large-scale simulations of MgO exsolution processes at the Earth’s core-mantle boundary. Our results suggest that Mg exsolves in the form of crystalline Fe-poor ferropericlase as opposed to a liquid MgO component presumed previously. The solubility of Mg in the core is limited, and the present-day core is nearly Mg-free. The resulting exsolution rate is small yet nonnegligible, suggesting that MgO exsolution can provide a potentially important energy source, although it alone may be difficult to drive an early geodynamo.
22 Apr 2024Submitted to ESS Open Archive
26 Apr 2024Published in ESS Open Archive