Transport Properties of Matter under Extreme Conditions

Understanding the electronic transport properties of iron under high temperatures and pressures is essential for constraining geophysical processes. The difficulty of reliably measuring these properties under Earth-core conditions calls for sophisticated theoretical methods that can support diagnostics. We compute the results of the electrical conductivity within the pressure and temperature ranges found in Earth’s core by simulating microscopic Ohm’s law using time-dependent density functional theory (TDDFT).
We are working on Spectral Neighbor Analysis Potential (SNAP) machine-learning potential for large-scale molecular dynamics simulations including coupling spin-lattice dynamics. The generated models can be used to simulate phenomena in iron, such as the interplay of phonon, and magnetic contributions to the thermal conductivity, or to perform high-pressure shock compression simulations.