A new X-ray scattering technique, with energy resolution down to 50 meV, now lets researchers measure sound waves and viscosity in matter crushed to planetary-core pressures. This matters because the interiors of planets like Uranus, and the behaviour of materials in fusion experiments, are governed by "warm dense matter"—a state between solid and plasma that is notoriously difficult to study. Current models of how heat and momentum move through such matter rely on guesswork. The team aims to measure the viscosity of iron and silicates under extreme conditions, combining experiments at free-electron lasers (LCLS and EuXFEL) with simulations using density functional theory and machine learning. This is fundamental science. There is no immediate practical application. But understanding how matter flows under extreme pressure is essential for modelling planetary formation, interpreting seismic data from gas giants, and designing inertial-confinement fusion targets. Past fundamental work on dense plasmas has fed into everything from astrophysical simulations to the development of next-generation laser systems. A reliable, scalable model of plasma hydrodynamics could eventually improve how we simulate any high-energy-density system, from stars to laboratory experiments.
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We have recently demonstrated a precision inelastic X-ray scattering technique at free electron lasers (FELs), with remarkable energy resolutions down to 50 meV. This breakthrough can revolutionize the study of ion dynamics in warm dense matter. Notably, this technique uncovered that acoustic waves in warm dense methane follow Birch's law, thus implying a sound speed of 5.9 km/s in Uranus's thermal boundary layer. However, there is the potential for much deeper insights to be gained from these measurements, particularly if the dynamics and transport properties of WDM can be measured in the hydrodynamic regime. Our objective is to embark on a comprehensive exploration of the viscosity of matter under extreme conditions, focusing on astrophysical materials such as iron and silicates. Our approach integrates experimental, computational, and theoretical components. Leveraging elastic and inelastic X-ray scattering at cutting-edge FEL facilities like LCLS and EuXFEL, we aim to acquire data that elucidates both thermodynamic traits and transport properties in dense matter. To further our understanding, we will combine the experimental data with computational and theoretical methods - density functional theory, Bohm molecular dynamics, wavepacket molecular dynamics, and holography. This fusion aims to unlock a comprehensive understanding of transport properties and the equations of state for strongly coupled plasmas. We will refine these models using machine learning, specifically employing deep symbolic regression, and attempt to extract accurate, scalable models for large- scale hydrodynamic plasma simulations.
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