{
  "abstract": "Accelerated materials discovery produces experimental characterization data at a scale that requires evaluation to assess the chemical outcomes. For example, high-throughput materials synthesis approaches generate large arrays of powder X-ray diffraction (PXRD) patterns from complex phase assemblages, in which signals from known and unknown products overlap. Identifying unknown crystalline phases still relies on expert assessment of unexplained reflections and does not scale with data generation. We introduce AriadneX, a tool for high-throughput multiphase PXRD analysis that curates a diffraction basis library appropriate to the chemistry, assigns known phases to each sample, and extracts structured diffraction signal unaccounted for by the library as an anomaly pattern. The coupled task of phase recovery and anomaly detection is formulated as a mixed-integer optimization problem with crystallographic constraints and constraints inspired by optimal transport (OT). In controlled leaveone-out tests, the method prioritizes samples containing deliberately withheld known phases. Applied to a realworld discovery dataset, AriadneX resolves two families of distinct unexplained diffraction patterns and estimates their Bragg diffraction patterns, consistent with the two unknown crystalline phases identified by human experts.",
  "abstract_shown": true,
  "affiliations": [
    "School of Computer Science and Informatics",
    "University of Liverpool",
    "Leverhulme Research Centre for Functional Materials Design, Materials Innovation Factory",
    "Department of Chemistry"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Zhuoran Yang"
    },
    {
      "affs": [
        2,
        1
      ],
      "name": "Christopher M. Collins"
    },
    {
      "affs": [
        3,
        1
      ],
      "name": "Luke M. Daniels"
    },
    {
      "affs": [
        3,
        1
      ],
      "name": "Christopher J. Hampson"
    },
    {
      "affs": [
        3,
        1
      ],
      "name": "Nataliya L. Gulay"
    },
    {
      "affs": [
        3,
        1
      ],
      "name": "Matthew S. Dyer"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Vladimir V. Gusev"
    },
    {
      "affs": [
        2,
        1,
        3
      ],
      "name": "Matthew J. Rosseinsky"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/ertrmsbsd5fpe.bib",
  "cited_by": 0,
  "doi": "10.26434/chemrxiv.15010300/v1",
  "fulltext_url": null,
  "id": "ertrmsbsd5fpe",
  "issns": [],
  "landing_url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010300/v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2505|Machine Learning in Materials Science"
    ]
  ],
  "openalex": "W7221625463",
  "pdf_url": "https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15010300/v1",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-12",
  "publisher": "American Chemical Society (ACS)",
  "ris": "https://research.draconitic.com/paper/ertrmsbsd5fpe.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:22Z",
      "native_id": "10.26434/chemrxiv.15010300",
      "source": "chemrxiv",
      "url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010300/v1"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "openalex:2505|Machine Learning in Materials Science",
      "subfield": "materials-polymers"
    }
  ],
  "title": "AriadneX: Unknown Crystalline Phase Discovery from Anomaly-Aware Unmixing of Powder X-Ray Diffraction Patterns",
  "title_text": "AriadneX: Unknown Crystalline Phase Discovery from Anomaly-Aware Unmixing of Powder X-Ray Diffraction Patterns",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:22Z",
  "url": "https://research.draconitic.com/paper/ertrmsbsd5fpe",
  "venue": "ChemRxiv",
  "versions": []
}