Data-mined similarity function between material compositions
A new method for assessing the similarity of material compositions is described. A similarity measure is important for the classification and clustering of compositions. The similarity of the material compositions is calculated utilizing a data-mined ionic substitutional similarity based upon the pr...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
American Physical Society
2014
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| Online Access: | http://hdl.handle.net/1721.1/88962 |
| _version_ | 1826200112847650816 |
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| author | Yang, Lusann Ceder, Gerbrand |
| author2 | Massachusetts Institute of Technology. Department of Materials Science and Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Materials Science and Engineering Yang, Lusann Ceder, Gerbrand |
| author_sort | Yang, Lusann |
| collection | MIT |
| description | A new method for assessing the similarity of material compositions is described. A similarity measure is important for the classification and clustering of compositions. The similarity of the material compositions is calculated utilizing a data-mined ionic substitutional similarity based upon the probability with which two ions will substitute for each other within the same structure prototype. The method is validated via the prediction of crystal structure prototypes for oxides from the Inorganic Crystal Structure Database, selecting the correct prototype from a list of known prototypes within five guesses 75% of the time. It performs particularly well on the quaternary oxides, selecting the correct prototype from a list of known prototypes on the first guess 65% of the time. |
| first_indexed | 2024-09-23T11:31:23Z |
| format | Article |
| id | mit-1721.1/88962 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T11:31:23Z |
| publishDate | 2014 |
| publisher | American Physical Society |
| record_format | dspace |
| spelling | mit-1721.1/889622022-10-01T04:09:29Z Data-mined similarity function between material compositions Yang, Lusann Ceder, Gerbrand Massachusetts Institute of Technology. Department of Materials Science and Engineering Yang, Lusann Ceder, Gerbrand A new method for assessing the similarity of material compositions is described. A similarity measure is important for the classification and clustering of compositions. The similarity of the material compositions is calculated utilizing a data-mined ionic substitutional similarity based upon the probability with which two ions will substitute for each other within the same structure prototype. The method is validated via the prediction of crystal structure prototypes for oxides from the Inorganic Crystal Structure Database, selecting the correct prototype from a list of known prototypes within five guesses 75% of the time. It performs particularly well on the quaternary oxides, selecting the correct prototype from a list of known prototypes on the first guess 65% of the time. United States. Dept. of Energy (Contract DE-FG02-96ER45571) United States. Office of Naval Research (Contract N00014-11-1-0212) National Science Foundation (U.S.) (Cyber-enabled Discover and Innovation Contract ECCS-0941043) 2014-08-21T18:24:23Z 2014-08-21T18:24:23Z 2013-12 2013-11 Article http://purl.org/eprint/type/JournalArticle 1098-0121 1550-235X http://hdl.handle.net/1721.1/88962 Yang, Lusann, and Gerbrand Ceder. “Data-Mined Similarity Function Between Material Compositions.” Phys. Rev. B 88, no. 22 (December 2013). © 2013 American Physical Society en_US http://dx.doi.org/10.1103/PhysRevB.88.224107 Physical Review B Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf American Physical Society American Physical Society |
| spellingShingle | Yang, Lusann Ceder, Gerbrand Data-mined similarity function between material compositions |
| title | Data-mined similarity function between material compositions |
| title_full | Data-mined similarity function between material compositions |
| title_fullStr | Data-mined similarity function between material compositions |
| title_full_unstemmed | Data-mined similarity function between material compositions |
| title_short | Data-mined similarity function between material compositions |
| title_sort | data mined similarity function between material compositions |
| url | http://hdl.handle.net/1721.1/88962 |
| work_keys_str_mv | AT yanglusann dataminedsimilarityfunctionbetweenmaterialcompositions AT cedergerbrand dataminedsimilarityfunctionbetweenmaterialcompositions |