Ion dynamics exhibits inherent multiscale characteristics because it contains both atomistic and hydrodynamic behaviors. Although atomic-scale ab initio molecular dynamics is the subject of intense research on warm dense matter, the macroscopic relaxation process contained in the zero-frequency mode of the ionic dynamic structure factor (DSF) cannot be demonstrated due to the limitation of simulation sizes. Here, we fill this gap via the machine-learning deep potential method. To capture the ion dynamics near the hydrodynamic limit with ab initio accuracy, an accurate and efficient electron-temperature-dependent interatomic potential was constructed. We quantitatively verify the consistency of thermal diffusivities obtained from hydrodynamics and the fluctuation-dissipation theorem and further provide a microscopic perspective of energy transport to understand the zero-frequency mode of DSF. As implemented in two temperature states, a competitive mechanism is found to account for the damping of the zero-frequency mode.

• Received 12 January 2021
• Revised 21 April 2021
• Accepted 19 July 2021

DOI:https://doi.org/10.1103/PhysRevResearch.3.033116

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

Published by the American Physical Society