{
  "abstract": "Whether large language models (LLMs) can contribute to non-trivial science, beyond summarising literature and writing routine code, is an open question. We report a case study in which an LLM (Claude) was asked to formulate, implement, verify and parameterise a new equation of state of the statistical associating fluid theory (SAFT) family. The target was a SAFT-VR variant for polar and dipolar molecules in which the segments interact through the isotropic multipolar potential (IMP) of Müller and Gelb, expressed as a temperature-dependent sum of Sutherland terms and treated with the Barker–Henderson perturbation theory of SAFT-VR Mie and SAFT-VR Sum. Over three sessions the LLM produced a stepby-step derivation, a 600-line implementation in the open-source Julia package Clapeyron.jl, a suite of 97 verification tests, a parameter-estimation pipeline applied to DIPPR data for six cyclic ethers, ketones and a sulfide, and a comparison with the group-contribution SAFT-γ",
  "abstract_shown": true,
  "affiliations": [
    "IFP Energies nouvelles, 1 et 4 avenue de Bois-Préau, Rueil-Malmaison, France, 92852",
    "Department of Chemical Engineering",
    "Imperial College London"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Werner A. Müller"
    },
    {
      "affs": [
        0
      ],
      "name": "Benoit Creton"
    },
    {
      "affs": [
        0
      ],
      "name": "Carlos Nieto-Draghi"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "Erich A. Müller",
      "orcid": "0000-0002-1513-6686"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/2ydzt0d8qk67m.bib",
  "cited_by": 0,
  "doi": "10.26434/chemrxiv.15010080/v1",
  "fulltext_url": null,
  "id": "2ydzt0d8qk67m",
  "issns": [],
  "landing_url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010080/v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2204|Phase Equilibria and Thermodynamics"
    ]
  ],
  "openalex": "W7220947328",
  "pdf_url": "https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15010080/v1",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-08",
  "publisher": "American Chemical Society (ACS)",
  "ris": "https://research.draconitic.com/paper/2ydzt0d8qk67m.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:22Z",
      "native_id": "10.26434/chemrxiv.15010080",
      "source": "chemrxiv",
      "url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010080/v1"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "source:chemrxiv",
      "subfield": "general"
    }
  ],
  "title": "Large language models as collaborators in molecular thermodynamics: a case study of the LLM-assisted development of SAFT-VR IMP, an equation of state for polar fluids",
  "title_text": "Large language models as collaborators in molecular thermodynamics: a case study of the LLM-assisted development of SAFT-VR IMP, an equation of state for polar fluids",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:22Z",
  "url": "https://research.draconitic.com/paper/2ydzt0d8qk67m",
  "venue": "ChemRxiv",
  "versions": []
}