{
  "abstract": "Comparing crystal structures, whether to identify polymorphs, follow a phase transition, or search a database for a known motif, requires a descriptor that encodes the chemistry of a crystal while remaining invariant to the arbitrary choices made during structure determination or descriptor construction. RINSE (Reciprocal-space INvariant Spectral Embedding) is such a fingerprint, computed from a crystal’s diffraction pattern. By projecting the intensity-weighted reciprocal lattice onto a combined radial and spherical-harmonic basis, RINSE produces a compact power spectrum that is invariant to crystal orientation and to the choice of unit-cell representation, in tens of milliseconds per structure. The descriptor is inspired by the Smooth Overlap of Atomic Positions (SOAP) kernel but maps the full periodic structure rather than a local atomic neighbourhood. A locality-sensitive hash derived from principal-component analysis of the descriptor space enables rapid approximate retrieval of structurally similar crystals, and provides a convenient pronounceable identifier for a related group of structures. The RINSE code is freely available as an open-source Python package.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Chemistry",
    "Durham University"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Thomas Fellowes"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "John S. O. Evans"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Aurora J. Cruz-Cabeza"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/emh64r3bmtpcz.bib",
  "cited_by": 0,
  "doi": "10.26434/chemrxiv.15008615/v1",
  "fulltext_url": null,
  "id": "emh64r3bmtpcz",
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  "landing_url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008615/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"
    ]
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  "openalex": "W7212194441",
  "pdf_url": "https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15008615/v1",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-10",
  "publisher": "American Chemical Society (ACS)",
  "ris": "https://research.draconitic.com/paper/emh64r3bmtpcz.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:19Z",
      "native_id": "10.26434/chemrxiv.15008615",
      "source": "chemrxiv",
      "url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008615/v1"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "openalex:2505|Machine Learning in Materials Science",
      "subfield": "materials-polymers"
    }
  ],
  "title": "RINSE: A reciprocal-space fingerprint for comparing crystal structures",
  "title_text": "RINSE: A reciprocal-space fingerprint for comparing crystal structures",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:19Z",
  "url": "https://research.draconitic.com/paper/emh64r3bmtpcz",
  "venue": "ChemRxiv",
  "versions": []
}