{
  "id": "2412.14953",
  "version": "v1",
  "published": "2024-12-19T15:34:21.000Z",
  "updated": "2024-12-19T15:34:21.000Z",
  "title": "The liquid-liquid phase transition of hydrogen and its critical point: Analysis from ab initio simulation and a machine-learned potential",
  "authors": [
    "Mathieu Istas",
    "Scott Jensen",
    "Yubo Yang",
    "Markus Holzmann",
    "Carlo Pierleoni",
    "David M. Ceperley"
  ],
  "categories": [
    "cond-mat.stat-mech"
  ],
  "abstract": "We simulate high-pressure hydrogen in its liquid phase close to molecular dissociation using a machine-learned interatomic potential. The model is trained with density functional theory (DFT) forces and energies, with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional. We show that an accurate NequIP model, an E(3)-equivariant neural network potential, accurately reproduces the phase transition present in PBE. Moreover, the computational efficiency of this model allows for substantially longer molecular dynamics trajectories, enabling us to perform a finite-size scaling (FSS) analysis to distinguish between a crossover and a true first-order phase transition. We locate the critical point of this transition, the liquid-liquid phase transition (LLPT), at 1200-1300 K and 155-160 GPa, a temperature lower than most previous estimates and close to the melting transition.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2024-12-19T15:34:21.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "liquid-liquid phase transition",
      "ab initio simulation",
      "critical point",
      "machine-learned potential",
      "true first-order phase transition"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}