{
  "abstract": "Machine-learning interatomic potentials enable large-scale atomistic simulations of vanadium alloys relevant to fusion applications, but reliable training and validation remain challenging in multicomponent systems. Here, we develop a descriptor-based DeepMD-DPA1 potential for the V-Ti-Cr system using a two-stage workflow: broad configuration sampling driven by the MatterSim foundation model followed by fine-tuning to density-functional-theory data computed with VASP. The model achieves root-mean-square errors of 9.2 meV/atom for energies and 0.23 eV/angstrom for force components. Using this potential in large-cell LAMMPS simulations, we compute Young's modulus, bulk modulus, and Poisson's ratio for V-4Ti-xCr and V-xTi-4Cr alloys at T = 300 K and T = 1073 K. We find that increasing Cr fraction increases the elastic moduli of the alloy, while increasing Ti fraction decreases them; all compositions are softer at 1073 K than at 300 K. Two-phase simulations give a melting temperature for pure V of 1950 K, in good agreement with experimental data.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.08291",
  "author_total": 5,
  "authors": [
    {
      "name": "G. S. Demyanov"
    },
    {
      "name": "D. V. Minakov"
    },
    {
      "name": "S. B. Saltykov"
    },
    {
      "name": "P. R. Levashov"
    },
    {
      "name": "N. M. Chtchelkatchev"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/fzbg2ze3y2vkn.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.08291",
  "fulltext_url": null,
  "id": "fzbg2ze3y2vkn",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.08291",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cond-mat.mtrl-sci"
    ],
    [
      "openalex",
      "2505|Fusion materials and technologies"
    ]
  ],
  "openalex": "W7221056930",
  "pdf_url": "https://arxiv.org/pdf/2610.08291",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-06",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/fzbg2ze3y2vkn.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:27:22Z",
      "native_id": "2610.08291",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.08291"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:cond-mat.mtrl-sci",
      "subfield": "condensed-matter"
    }
  ],
  "title": "Mechanical properties of V-4Ti-4Cr alloy from molecular dynamics with a neural-network potential",
  "title_text": "Mechanical properties of V-4Ti-4Cr alloy from molecular dynamics with a neural-network potential",
  "type": "preprint",
  "updated_at": "2026-10-30T12:27:22Z",
  "url": "https://research.draconitic.com/paper/fzbg2ze3y2vkn",
  "venue": "arXiv",
  "versions": []
}