The Inorganic Crystal Structure Database (ICSD)—Present and Future
Abstract
The Inorganic Crystal Structure Database (ICSD) is a comprehensive collection of crystal structure entries for inorganic materials. ICSD is produced by Fachinformationszentrum Karlsruhe, Germany, and the National Institute of Standards and Technology, US. The WWW interface is developed in cooperation with the Institut Laue-Langevin, Grenoble. The ICSD is disseminated in computerized formats with scientific software tools to exploit the content of the database. ICSD includes records of all inorganic crystal structures with atomic coordinates published since 1913. The data base contains 70 102 records as of July 2003. All data are recorded by experts and are checked several times. Apart from updating, data integrity and completeness are important objectives. Incorporation of missing structures, evaluation and correction of data, with the help of authors, users and experts are ongoing activities. This review article gives an overview of the product portfolio and the current activities.
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Experimental approaches over decades have catalogued 20,000 computationally stable structures out of 200,000 entries in the Inorganic Crystal Structure Database.
“Experimental approaches over the decades have catalogued 20,000 computationally stable structures (out of a total of 200,000 entries) in the Inorganic Crystal Structure Database (ICSD)15,18.”
From Scaling deep learning for materials discovery (2023) · cites this paper as [15]
In the ICSD, the top two space groups are centrosymmetric Pnma and P21/c, accounting for approximately 16% of all structures (∼8% each); in the Stable Structure database, Pnma is ranked 16th with 1.56% and P21/c is found in only 0.7%.
“For example, the top two space groups in the ICSD are centrosymmetric Pnma and P21/c, accounting for approximately 16% of all structures, with ∼8% in each case. By contrast, Pnma is ranked 16th in Stable Structure database with 1.56% of the structures, while P21/c is found in only 0.7% of the structures, which is an order of magnitude lower than in the ICSD.”
From Artificial Intelligence Driving Materials Discovery? Perspective on the Article: Scaling Deep Learning for Materials Discovery (2024) · cites this paper as [15]
The space group distribution of the predicted compounds in the Stable Structure database is strikingly different from that in the ICSD.
“We have found that the space groups of the predicted compounds (Table 1) have a distribution that is strikingly different from those in the Inorganic Crystal Structure Database (ICSD),15”
From Artificial Intelligence Driving Materials Discovery? Perspective on the Article: Scaling Deep Learning for Materials Discovery (2024) · cites this paper as [15]
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- Authors
- Hellenbrandt, M.
- Affiliations
- FIZ Karlsruhe – Leibniz Institute for Information Infrastructure (DE)
- Corresponding author
- Hellenbrandt, Mariette
- Venue
- Crystallography Reviews
- Publisher
- Informa UK Limited
- Published
- 2004-01
- Volume
- 10
- Issue
- 1
- Pages
- 17-22
- ISSN
- 0889-311X (ISSN-L)
- 1476-3508
- OpenAlex
- W2023972500
- Cited by
- 684
- References
- 0
- Citations by year
- 2026: 67 · 2025: 83 · 2024: 97 · 2023: 54 · 2022: 84 · 2021: 75 · 2020: 70 · 2019: 64 · 2018: 34 · 2017: 20 · 2016: 11 · 2015: 2 · 2014: 2 · 2013: 1 · 2012: 1
- FWCI
- 1.53
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Crystallography Reviews (publishedVersion)
- Topics
- Physical Sciences › Chemistry › Inorganic Chemistry › Crystal structures of chemical compounds
- Physical Sciences › Materials Science › Electronic, Optical and Magnetic Materials › Crystal Structures and Properties
- Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
- Keywords
- Inorganic Crystal Structure Database, inorganic crystal structures, crystallographic data, atomic coordinates, data completeness, web interface
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