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  Big data approach for effective ionic radii

Gebhardt, J., & Rappe, A. M. (2019). Big data approach for effective ionic radii. Computer Physics Communications, 237, 238-243. doi:10.1016/j.cpc.2018.11.014.

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10.1016_j.cpc.2018.11.014.pdf (Publisher version), 398KB
 
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 Creators:
Gebhardt, J.1, 2, Author           
Rappe, A. M.1, Author
Affiliations:
1Department of Chemistry, University of Pennsylvania, ou_persistent22              
2Theory Group, Theory Department, Max Planck Institute for the Structure and Dynamics of Matter, Max Planck Society, ou_2266715              

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Free keywords: Ionic radii, Materials project, Data harvesting
 Abstract: Effective ionic radii are a useful tool for researchers in many disciplines. These radii are usually determined from interatomic distances and the values tabulated by Shannon and Prewitt are widely used since 1969. Here, we present a modern approach based on automated queries to materials databases followed by categorization and tabulation. This method is used to augment the available set of effective ionic radii by providing radii for missing anionic oxidation states and coordination numbers. Our approach proves to yield results that are consistent with known values for anions with well-established oxidation states. More exotic cases result in larger uncertainties due to the smaller amount of available structural data. Nevertheless, the provided estimates give reasonable values for cases that are untabulated at present. Furthermore, our approach is designed to continuously improve together with the growth of available databases. Furthermore, small tweaks of the presented application will allow us to also complement or revise ionic radii of cations. Thus, our approach is designed to update the old and useful concept of effective ionic radii, bringing it to modern days.

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Language(s): eng - English
 Dates: 2018-04-302018-01-242018-11-162018-11-302019-04
 Publication Status: Issued
 Pages: 6
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.cpc.2018.11.014
 Degree: -

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Project name : J.G. thanks the German Research Foundation for support from Research Fellowships GE 2827/1-1 and GE 2827/2-1. A.M.R. ac- knowledges support of the National Science Foundation, United States, grant DMR-1719353.
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Title: Computer Physics Communications
  Abbreviation : Comput. Phys. Commun.
Source Genre: Journal
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Publ. Info: Amsterdam : Elsevier B.V.
Pages: 6 Volume / Issue: 237 Sequence Number: - Start / End Page: 238 - 243 Identifier: ISSN: 0010-4655
CoNE: https://pure.mpg.de/cone/journals/resource/954925392326