Identifying an efficient, thermally robust inorganic phosphor host via machine learning
Identifying an efficient, thermally robust inorganic phosphor host via machine learning
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Publisher
London: Nature Publishing Group UK
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Language
English
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Publisher
London: Nature Publishing Group UK
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Contents
Rare-earth substituted inorganic phosphors are critical for solid state lighting. New phosphors are traditionally identified through chemical intuition or trial and error synthesis, inhibiting the discovery of potential high-performance materials. Here, we merge a support vector machine regression model to predict a phosphor host crystal structure’...
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Full title
Identifying an efficient, thermally robust inorganic phosphor host via machine learning
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TN_cdi_doaj_primary_oai_doaj_org_article_3702a80a2f9b445381a72ddd2dbb5fc9
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_3702a80a2f9b445381a72ddd2dbb5fc9
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ISSN
2041-1723
E-ISSN
2041-1723
DOI
10.1038/s41467-018-06625-z
