Materials Prediction via Classification Learning
Materials Prediction via Classification Learning
About this item
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Publisher
London: Nature Publishing Group UK
Journal title
Language
English
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Publication information
Publisher
London: Nature Publishing Group UK
Subjects
More information
Scope and Contents
Contents
In the paradigm of materials informatics for accelerated materials discovery, the choice of feature set (
i.e.
attributes that capture aspects of structure, chemistry and/or bonding) is critical. Ideally, the feature sets should provide a simple physical basis for extracting major structural and chemical trends and furthermore, enable rapid p...
Alternative Titles
Full title
Materials Prediction via Classification Learning
Authors, Artists and Contributors
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Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4548442
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4548442
Other Identifiers
ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/srep13285
