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Cited by 10,297Crystal structures of chemical compoundsResearch Data Management PracticesCrystallography and molecular interactions

The Cambridge Structural Database

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Groom, Colin R., Bruno, Ian J., Lightfoot, Matthew P., Ward, Suzanna C.·2016·Acta Crystallographica Section B Structural Science, Crystal Engineering and Materials
DOI 10.1107/s2052520616003954PMC PMC4822653
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Abstract

The Cambridge Structural Database (CSD) contains a complete record of all published organic and metal–organic small-molecule crystal structures. The database has been in operation for over 50 years and continues to be the primary means of sharing structural chemistry data and knowledge across disciplines. As well as structures that are made public to support scientific articles, it includes many structures published directly as CSD Communications. All structures are processed both computationally and by expert structural chemistry editors prior to entering the database. A key component of this processing is the reliable association of the chemical identity of the structure studied with the experimental data. This important step helps ensure that data is widely discoverable and readily reusable. Content is further enriched through selective inclusion of additional experimental data. Entries are available to anyone through free CSD community web services. Linking services developed and maintained by the CCDC, combined with the use of standard identifiers, facilitate discovery from other resources. Data can also be accessed through CCDC and third party software applications and through an application programming interface.

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Crossref · 10.1107/s2052520616003954

Cites

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  • The largest data set of experimentally characterized metal-organic compounds is the set of structures obtained from X-ray diffraction in the Cambridge Structural Database (CSD).

    “The largest data set of experimentally characterized metal-organic compounds (e.g., MOFs or TMCs) is the set of structures obtained from X-ray diffraction in the Cambridge Structural Database (CSD) (25).”

    From Machine Learning for the Discovery, Design, and Engineering of Materials. (2022) · cites this paper as [25]

    In “The value of sharing crystal structures” (page unavailable), the paper says the CSD contains all published organic and metal–organic small-molecule crystal structures, including X-ray diffraction analyses. It does not establish that these structures are the largest dataset of all experimentally characterized metal–organic compounds, and it notes that the CSD also includes neutron diffraction analyses. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • Geometric structures of many TMCs are available (approximately 150,000 or more) in the CSD.

    “Geometric structures of many TMCs are available (∼150,000 or more) in the CSD (25).”

    From Machine Learning for the Discovery, Design, and Engineering of Materials. (2022) · cites this paper as [25]

    The Cambridge Structural Database section says the CSD surpassed 800,000 entries in 2015 and includes metal–organic structures, a category that includes structures containing transition metals. The available passage does not give a count specifically for transition-metal complexes, so it does not establish the claimed approximately 150,000 or more. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • Because structural data for TMCs has been widely available for some time, many early descriptors were motivated by analyzing CSD structures, even prior to the development of affordable computational modeling.

    “Because structural data for TMCs has been widely available for some time [e.g., from the CSD (25)], many early descriptors were motivated by analyzing CSD structures (76), even prior to the development of affordable computational modeling (e.g., with DFT).”

    From Machine Learning for the Discovery, Design, and Engineering of Materials. (2022) · cites this paper as [25]

  • The scale of new materials that can be screened for discovery has been transformed from hundreds by trial and error to thousands or millions.

    “As a result, the scale of new materials that can be screened for discovery has been transformed from hundreds by trial and error to thousands or millions.”

    From Machine Learning for the Discovery, Design, and Engineering of Materials. (2022) · cites this paper as [25]

    The Cambridge Structural Database section reports more than 800,000 recorded structures, and ‘Using the CSD > Accessibility and efficiency’ describes tools for searching them. Neither passage says that discovery screening expanded from hundreds of trial-and-error candidates to thousands or millions; searches for screening scale and trial and error found no such account. (LLM, conf=0.75)

    Experimental — accuracy not yet measured

  • Experimental data sets for the direct screening of transition-metal complexes and closely related MOF materials are relatively small and scarce.

    “Experimental data sets for the direct screening of transition-metal complexes (TMCs) and closely related MOF materials are relatively small and scarce.”

    From Machine Learning for the Discovery, Design, and Engineering of Materials. (2022) · cites this paper as [25]

    The Cambridge Structural Database section describes a large collection of organic and metal–organic crystal structures, while Future estimates that only 15% of determined structures are published. Neither passage addresses the size or scarcity of experimental datasets suitable for direct screening of transition-metal complexes or MOFs; searches for screening datasets and MOF materials found no such statement. (LLM, conf=0.75)

    Experimental — accuracy not yet measured

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Cites

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Research works printed but not linked: 3

  1. Burton, A., Koers, H., Manghi, P., La Bruzzo, S., Aryani, A., Diepenbroek, M. & Schindler, U. (2015). Metadata and Semantics Research, pp. 324–335. Dordrecht: Springer.
  2. Kennard, O. & Watson, D. G. (1970b). Molecular Structures and Dimensions, Vol. 1, Bibliography 1935–1969, General Organic Crystal Structures, p. ix. Dordrecht: Reidel.
  3. Reilly, A. M. et al. (2016). Acta Cryst. In the press.

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Authors
Groom, C. R., Bruno, I. J., Lightfoot, M. P., & Ward, S. C.
Affiliations
Cambridge Crystallographic Data Centre (GB)
Corresponding author
Groom, Colin R.
ORCID
Venue
Acta Crystallographica Section B Structural Science, Crystal Engineering and Materials
Publisher
International Union of Crystallography (IUCr)
Published
2016-04-01
Volume
72
Issue
2
Pages
171-179
ISSN
  • 2052-5192 (ISSN-L)
  • 2052-5206
DOI
10.1107/s2052520616003954
PMC
PMC4822653
OpenAlex
W2319902168
Cited by
10,297
References
45
Citations by year
2026: 706 · 2025: 1031 · 2024: 1204 · 2023: 1056 · 2022: 1037 · 2021: 1107 · 2020: 1109 · 2019: 1028 · 2018: 923 · 2017: 755 · 2016: 318 · 2015: 7 · 2014: 11
FWCI
396.85
Type
journal article
Language
en
Open access
Licence
Locations
  • Acta Crystallographica Section B Structural Science Crystal Engineering and Materials (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Topics
  • Physical Sciences › Chemistry › Inorganic Chemistry › Crystal structures of chemical compounds
  • Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
  • Physical Sciences › Chemistry › Physical and Theoretical Chemistry › Crystallography and molecular interactions
Keywords
Cambridge Structural Database, crystal structure, small-molecule crystallography, organic compounds, metal-organic compounds, data discovery

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