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Stable Solid Molecular Hydrogen above 900 K from a Machine-Learned Potential Trained with Diffusion Quantum Monte Carlo

Niu, Hongwei·Yang, Yubo·Jensen, Scott·Holzmann, Markus·Pierleoni, Carlo·Ceperley, David M.
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Abstract

Here, we survey the phase diagram of high-pressure molecular hydrogen with path integral molecular dynamics using a machine-learned interatomic potential trained with quantum Monte Carlo forces and energies. Besides the HCP and C2/c–24 phases, we find two new stable phases both with molecular centers in the Fmmm–4 structure, separated by a molecular orientation transition with temperature. The high temperature isotropic Fmmm–4 phase has a reentrant melting line with a maximum at higher temperature (1450 K at 150 GPa) than previously estimated and crosses the liquid-liquid transition line around 1200 K and 200 GPa.

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08 HYDROGEN75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITYartificial neural networkscompressed hydrogendeep learningdiffusion quantum Monte Carloelectronic structureequations of statefirst-principles calculationshigh pressurehydrogenmachine learningmolecular dynamicspath-integral Monte Carlopath-integral methodsphase diagramsphase transitionsquantum monte Carlo

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Niu, Hongwei, Yang, Yubo, Jensen, Scott, Holzmann, Markus, Pierleoni, Carlo, Ceperley, David M.. 2023-02-17. Stable Solid Molecular Hydrogen above 900 K from a Machine-Learned Potential Trained with Diffusion Quantum Monte Carlo. https://doi.org/10.1103/physrevlett.130.076102

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