Dynamical properties of hydrogen fluid at high pressures.

The properties of the hydrogen fluid at high pressures are still of interest to the scientific community. The experimentally unreachable dynamical properties could provide new insights into this field. In 2020 [Cheng et al., Nature 585, 217-220 (2020)], the machine-learned approach allows the calculation of the self-diffusion coefficient in the warm dense hydrogen with higher precision. After that, the work [van de Bund et al., Phys. Rev. Lett. 126(22), 225701 (2021)] reports the ab initio treatment of isotopic effects on diffusion in H2/D2 and a significant increase in its value in the region of the phase transition. Both works indicate the anomalous growth of diffusion, but the reasons for this phenomenon are unclear. In the present work, we reveal the plasma-like behavior of the diffusion growth. We apply the classical molecular dynamics method using a machine learning potential developed on the ab initio modeling for the prediction of diffusion and shear viscosity coefficients. We consider dependencies of the vibrational spectrum, molecule lifetime, diffusion, and shear viscosity coefficients on density along the isotherms in the temperature range from 600 to 1100 K.