Dense hydrogen diffusion Monte Carlo (DMC) database

Many aspects of the phase diagram of dense hydrogen remain poorly understood, sometimes even qualitatively. Dense hydrogen is predicted become a high-temperature superconductor at sufficiently high pressure and is crucial in determining the structure of gas giant planets. Addressing the entire phase diagram with accurate ab initio simulations like diffusion Monte Carlo (DMC) is not currently feasible due to the computational cost, which limits studies to small system sizes. Recently, machine-learned interatomic potentials trained on ab initio data have been applied in large-scale molecular dynamics simulations to approach the accuracy of the ab initio methods without the finite size errors. Typically, these have relied on density functional theory to generate the training data. Here we provide the a large-scale DMC database for dense hydrogen, which allows training of machine-learned potentials with DMC accuracy.

Stable solid molecular hydrogen above 900K

Recently we used a new potential trained on this DMC data in large-scale path integral molecular dynamics simulations to study molecular hydrogen. We found a phase diagram with HCP and C2/c-24 phases and two new structures with Fmmm-4 molecular centers. The Fmmm-4 structures show a molecular orientational order transition from an ordered low-temperature structure to an isotropic high-temperature phase which melts to a molecular liquid with a maximum melting temperature of 1450K at 150 GPa. This finding will likely lead to new experimental studies of the melting curve for molecular hydrogen.

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