Normalized radial distribution as a crystal structure descriptor: applications in comparative crystal chemistry and the 'search match' problem.

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Title: Normalized radial distribution as a crystal structure descriptor: applications in comparative crystal chemistry and the 'search match' problem.
Authors: Rashchenko, Sergey1,2 (AUTHOR) rashchenko@igm.nsc.ru
Source: Journal of Applied Crystallography. Jun2026, Vol. 59 Issue 3, p901-909. 9p.
Subjects: Crystal structure, Radial distribution function, Crystallography, Mathematical crystallography
Abstract: A crystal structure descriptor ('fingerprint function') based on a normalized radial distribution function is presented. Unlike earlier prototypes developed mainly for use in crystal structure prediction, data mining and machine‐learning workflows, the presented approach is focused on applications in the field of comparative crystal chemistry. Its prospective applications include the classification of large datasets of chemically heterogeneous crystal structures or 'search match' problems, when structures homeotypic to a given structure are searched for throughout a database. Practical aspects of the proposed approach are illustrated with real‐life examples from the Crystallography Open Database. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Applied Crystallography is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: A crystal structure descriptor ('fingerprint function') based on a normalized radial distribution function is presented. Unlike earlier prototypes developed mainly for use in crystal structure prediction, data mining and machine‐learning workflows, the presented approach is focused on applications in the field of comparative crystal chemistry. Its prospective applications include the classification of large datasets of chemically heterogeneous crystal structures or 'search match' problems, when structures homeotypic to a given structure are searched for throughout a database. Practical aspects of the proposed approach are illustrated with real‐life examples from the Crystallography Open Database. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Applied Crystallography is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1107/S1600576726002797
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      – Code: eng
        Text: English
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        PageCount: 9
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    Subjects:
      – SubjectFull: Crystal structure
        Type: general
      – SubjectFull: Radial distribution function
        Type: general
      – SubjectFull: Crystallography
        Type: general
      – SubjectFull: Mathematical crystallography
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      – TitleFull: Normalized radial distribution as a crystal structure descriptor: applications in comparative crystal chemistry and the 'search match' problem.
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            NameFull: Rashchenko, Sergey
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            – D: 01
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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