{
  "abstract": "We investigate the melting behavior of calcium oxide (CaO) under extreme conditions, a problem that remains poorly constrained due to experimental limitations despite its relevance for geophysical and technological applications. We develop a Machine Learning Interatomic Potential (MLIP) for CaO with PANNA 2.0 and the LATTE descriptor, training it on a dataset of $\\sim$12,000 configurations including solid, liquid, interfacial, and void-containing structures, extracted from ab-initio molecular dynamics data employing PBEsol exchange-correlation functional. We perform large-scale molecular dynamics simulations to compute the melting temperature at ambient pressure using both the void-nucleated melting (VNM) and two-phase coexistence (TPC) methods, obtaining $T_m=3055\\pm11$ K and $T_m=2847\\pm15$ K, respectively.\\\\ We calculate an enthalpy of fusion of $ΔH_f\\sim73$ kJ/mol, in agreement with thermodynamic assessments and ab initio calculations. We also reproduce the thermal expansion and obtain a volume increase of $\\sim$29% at Tm, consistent with the corresponding decrease in density extracted from spatially resolved number density profiles. Finally, we calculate the high-pressure melting curve of CaO up to 20 GPa, providing one of the very few computational determinations of this quantity to date. The results confirm that the overheating ratio $η$ is not constant under pressure, increasing from 17% at ambient pressure to 24% at 20 GPa, confirming previous findings and ruling out the assumption of a fixed overheating ratio. Our results establish MLIP-based simulations as a robust and efficient framework for investigating phase stability in ionic oxides and provide new insight into the melting behavior of CaO under extreme conditions.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2605.14793",
  "author_total": 2,
  "authors": [
    {
      "name": "Francesca Menescardi"
    },
    {
      "name": "Stefano de Gironcoli"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/fhgkc55gcqwbe.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2605.14793",
  "fulltext_url": null,
  "id": "fhgkc55gcqwbe",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2605.14793",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cond-mat.mtrl-sci"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://arxiv.org/pdf/2605.14793",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-16",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/fhgkc55gcqwbe.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:22:01Z",
      "native_id": "2605.14793",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2605.14793"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:cond-mat.mtrl-sci",
      "subfield": "condensed-matter"
    }
  ],
  "title": "Melting Behavior and Phase Stability of CaO from Neural Network Potentials: a Molecular Dynamics Study",
  "title_text": "Melting Behavior and Phase Stability of CaO from Neural Network Potentials: a Molecular Dynamics Study",
  "type": "preprint",
  "updated_at": "2026-10-30T12:22:01Z",
  "url": "https://research.draconitic.com/paper/fhgkc55gcqwbe",
  "venue": "arXiv",
  "versions": []
}