{
  "abstract": "Solid-state hydrogen storage materials are promising candidates for safe and compact hydrogen storage; however, data-driven discovery in this field remains limited by the availability of large-scale, well-curated datasets. Here, we present the Digital Hydrogen Platform (DigHyd: www.dighyd.org ), a rigorously curated database comprising > 4,000 experimental literature sources and > 30,000 data entries on hydrogen storage materials, constructed through AI-assisted literature mining combined with human-in-the-loop validation. In addition to gravimetric hydrogen storage density (w), DigHyd also covers thermodynamic parameters, specifically the enthalpy (∆H) and entropy (∆S) changes associated with hydrogenation reactions, primarily defined as $$\\:M+\\frac{1}{2}{\\text{H}}_{2}\\rightleftharpoons\\:M\\text{H}$$ . These parameters were obtained by manually analyzing multi-temperature pressure-composition-temperature (PCT) data using van’t Hoff analysis. By focusing on ∆H and ∆S rather than fixing equilibrium pressure at a single temperature, DigHyd enables flexible evaluation of equilibrium behavior under application-specific operating conditions. Statistical analyses reveal distinct distributions of thermodynamic parameters across material classes, together with broad compositional variability within representative hydride systems. As a representative application, we performed composition-based symbolic-regression modeling using a curated single-phase or near-single-phase subset, which achieved predictive performance comparable to state-of-the-art black-box models while providing compact, physically interpretable relationships for w, $$\\:{P}_{\\text{e}\\text{q},\\text{R}\\text{T}}$$ (equilibrium pressure at room temperature), ∆H, or ∆S. The resulting descriptor map identifies recurring physical factors, including host atomic mass, lattice geometry, elastic stiffness, metal filling factor, and electronegativity-derived descriptor correlations, which rationalize the trade-off between w and $$\\:{P}_{\\text{e}\\text{q},\\text{R}\\text{T}}$$ . Overall, DigHyd provides a rigorously curated thermodynamic dataset that serves as a reliable basis for data-driven analyses of hydrogen storage materials and supports systematic exploration of structure–property relationships.",
  "abstract_shown": true,
  "affiliations": [
    "Advanced Institute for Materials Research (WPI-AIMR), Tohoku University, Sendai, 980-8577, Japan",
    "Unprecedented-scale Data Analytics Center, Tohoku University, Sendai, 980-8578, Japan",
    "Frontier Research Institute for Interdisciplinary Sciences (FRIS), Tohoku University, Sendai, 980-8577, Japan",
    "Department of Materials Engineering, The University of Tokyo, Tokyo, 113-8656, Japan",
    "Institute for Materials Research, Tohoku University, Sendai, 980-8577, Japan",
    "Institute of Fluid Science, Tohoku University, Sendai, 980-8577, Japan"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 11,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Seong‐Hoon Jang",
      "orcid": "0000-0001-6026-636X"
    },
    {
      "affs": [
        0,
        2
      ],
      "name": "Di ZHANG",
      "orcid": "0000-0001-6347-9344"
    },
    {
      "affs": [
        0
      ],
      "name": "Xue Jia",
      "orcid": "0009-0003-6591-4284"
    },
    {
      "affs": [
        0
      ],
      "name": "Hung Ba Tran",
      "orcid": "0000-0001-5508-3956"
    },
    {
      "affs": [
        0,
        2
      ],
      "name": "Linda Zhang",
      "orcid": "0000-0003-3841-544X"
    },
    {
      "affs": [
        3
      ],
      "name": "Ryuhei Sato",
      "orcid": "0000-0002-5503-0982"
    },
    {
      "affs": [
        2
      ],
      "name": "Yusuke Hashimoto",
      "orcid": "0000-0002-1886-9332"
    },
    {
      "affs": [
        4
      ],
      "name": "Toyoto Sato",
      "orcid": "0000-0002-0527-1235"
    },
    {
      "affs": [
        5
      ],
      "name": "K. Konno",
      "orcid": "0000-0002-5978-2655"
    },
    {
      "affs": [
        0,
        4
      ],
      "name": "Shin‐ichi Orimo",
      "orcid": "0000-0002-4216-0446"
    },
    {
      "affs": [
        0
      ],
      "name": "Hao Li",
      "orcid": "0000-0002-7577-1366"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/dhwy5km359wyg.bib",
  "cited_by": 7,
  "doi": "10.1007/s00339-026-09903-6",
  "fulltext_url": null,
  "id": "dhwy5km359wyg",
  "issns": [
    "0947-8396",
    "1432-0630"
  ],
  "landing_url": "https://doi.org/10.1007/s00339-026-09903-6",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
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      "openalex",
      "2505|Hydrogen Storage and Materials"
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  "openalex": "W7138243153",
  "pdf_url": "https://link.springer.com/content/pdf/10.1007/s00339-026-09903-6.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-04",
  "publisher": "Springer Science+Business Media",
  "ris": "https://research.draconitic.com/paper/dhwy5km359wyg.ris",
  "sources": [
    {
      "first_seen": "2026-11-05T13:21:14Z",
      "native_id": "W7138243153",
      "source": "openalex",
      "url": "https://doi.org/10.1007/s00339-026-09903-6"
    }
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  "subjects": [
    {
      "field": "chemistry",
      "origin": "openalex:2505|Hydrogen Storage and Materials",
      "subfield": "materials-polymers"
    }
  ],
  "title": "Digital hydrogen platform (DigHyd): a rigorously curated database for hydrogen storage materials empowered by AI-assisted literature mining",
  "title_text": "Digital hydrogen platform (DigHyd): a rigorously curated database for hydrogen storage materials empowered by AI-assisted literature mining",
  "type": "peer-reviewed",
  "updated_at": "2026-11-08T13:20:57Z",
  "url": "https://research.draconitic.com/paper/dhwy5km359wyg",
  "venue": "Applied Physics A",
  "versions": []
}