Abstract
The earth is thought to have gone through complex physicochemical changes during the accretion and magma ocean stages. To better understand this evolution process at the fundamental level, we investigate the behavior of a bulk earth melt system by simulating the composition Fe(35.7)Mg(19.0)Si(15.2)O(30.2) (in wt%) at high pressure. A deep neural network potential trained by first-principles data can enable accurate molecular dynamics simulation of large supercells that greatly enhances sampling for reliable evaluation of elemental partitioning. Our simulated system undergoes a phase separation in which the four elements clump together to different extents into two major domains. Based on the coordination and space-decomposition analyses, the inferred composition at 3000 K and 29.1 GPa contains 96.2, 0.1, 1.9 and 1.7 wt% of Fe, Mg, Si, and O, respectively, for the one domain and the corresponding elemental proportions are 3.0, 29.7, 22.0, and 45.3 wt% for the other domain. The predicted segregation thus leads to the formation of an iron-rich phase which corresponds to the metallic core and a magma ocean phase which corresponds to the silicate mantle. The metallic domain incorporates more silicon and more oxygen whereas the magma ocean domain gains more iron oxides at higher temperatures. Our predicted compositions compare favorably with those derived from experimental work for the equilibrium state metal and silicate reacting under high-pressure conditions.