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VERSION:2.0
PRODID:-//University of Liverpool Computer Science Seminar System//v2//EN
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DTSTAMP:20260921T235627Z
UID:Seminar-MIF-1431@lxserverM.csc.liv.ac.uk
ORGANIZER:CN=Othon Michail:MAILTO:Othon.Michail@liverpool.ac.uk
DTSTART:20240325T140000
DTEND:20240325T150000
SUMMARY:MIF Series
DESCRIPTION:Daniel Widdowson: Ultra-fast detection of (near-)duplicate structures across major crystal databases.\n\nThe Cambridge Structural Database (CSD) and the Crystallography Open Database (COD) contain thousands of structures. Large portions of these databases overlap, often because their entries originate from the same publication. Constructing a list of CSD-COD cross entries is difficult because data can be reformatted in the curation process, many data points do not reliably distinguish or identify crystals, and most ways of finding matches are slow, requiring the order of 10^10 comparisons. Using geometry-based structural invariants (PDD [1]: Pointwise Distance Distribution and its simplified version AMD [2]: Average Minimum Distance), we compared all-vs-all entries in the CSD and COD, discovering the extent of their overlap for the first time. Using these invariants, we compared 1,214,848 entries from the CSD against 508,392 from COD, taking only 17 minutes on a typical desktop computer. Over 400,000 crystals were matched, an overlap of 33% of the CSD and 80% of COD. We also found a significant overlap of COD with the ICSD (over 50,000 entries), as well as at least minor overlaps with the Materials Project database. We additionally searched for duplicate entries, finding several thousand in both the CSD and COD, many of which are not listed anywhere as known duplicates.\n[1] Neural Information Processing Systems 35, 24625-24638 (2022).\n[2] MATCH Communications Math. Computer Chemistry 87, 529-559 (2022).\n\nhttps://www.csc.liv.ac.uk/research/seminars/abstract.php?id=1431
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