Title: Real space lattice dynamics and mechanical stability of iron at inner core conditions

Abstract:

The mechanical stability of body-centered cubic (bcc) iron was investigated at pressure and temperature conditions found in the Earth’s inner core using ab initio molecular dynamics and a novel Gaussian process regression methodology that operates on graph kernels and quantifies the similarity of mathematical graphs that encode the atomic configurations, learning the potential energy of the configuration.

The machine learning model performs at the same level as other state-of-the-art models. Atoms in the super cell were displaced in the direction of the first, second, and third nearest-neighbors from selected configurations that included thermal atomic displacements, and forces exerted on the displaced atoms were computed by numerical differentiation of the potential energy predicted by the machine learning models. In the pressure range between 300 and 360 GPa, bcc iron is mechanically unstable below 1000K and mechanically stable above 3000K, with transient dynamics that partially follow the Bain path in between.