{
  "abstract": "Chemists read 1 H and 13 C NMR daily, and it is tempting to paste the peak lists into a large language model. Given only those two peak lists for 105 molecules balanced by molecular complexity and compound classes, six frontier LLMs (Claude Opus 4.8, DeepSeek V4 Pro, Gemini 3.1 Pro, GPT-5.5, Grok 4.3, Qwen3.7-Max) and four specialized solvers (BLIND, NMRMind, NMRPeak, NMR-Solver) were compared. The best LLM (Gemini 3.1 Pro) solved 24% of structures, the best specialized model (BLIND) solved 69% of them. All models drift toward smaller molecules and drop groups silent in ¹H NMR like halogens, nitriles, diazo.",
  "abstract_shown": true,
  "affiliations": [
    "A.N. Nesmeyanov Institute of Organoelement Compounds of Russian Academy of Sciences, 28 Vavilova St., Moscow, Russian Federation, 119234"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Fedor Kliuev"
    },
    {
      "affs": [
        0
      ],
      "name": "Ivan Smirnov"
    },
    {
      "affs": [
        0
      ],
      "name": "Mikhail A. Losev"
    },
    {
      "affs": [
        0
      ],
      "name": "Oleg I. Afanasyev",
      "orcid": "0000-0002-6224-6407"
    },
    {
      "affs": [
        0
      ],
      "name": "Denis Chusov"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7mt7yamjwg1r6.bib",
  "cited_by": 0,
  "doi": "10.26434/chemrxiv.15006195/v2",
  "fulltext_url": null,
  "id": "7mt7yamjwg1r6",
  "issns": [],
  "landing_url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15006195/v2",
  "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",
      "1607|Molecular spectroscopy and chirality"
    ]
  ],
  "openalex": "W7213981463",
  "pdf_url": "https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15006195/v2",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-22",
  "publisher": "American Chemical Society (ACS)",
  "ris": "https://research.draconitic.com/paper/7mt7yamjwg1r6.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:21Z",
      "native_id": "10.26434/chemrxiv.15006195",
      "source": "chemrxiv",
      "url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15006195/v2"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "openalex:1607|Molecular spectroscopy and chirality",
      "subfield": "physical"
    }
  ],
  "title": "Can AI Help Chemists To Solve NMR?",
  "title_text": "Can AI Help Chemists To Solve NMR?",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:21Z",
  "url": "https://research.draconitic.com/paper/7mt7yamjwg1r6",
  "venue": "ChemRxiv",
  "versions": []
}