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Materials Prediction via Classification Learning
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 chem...
Autores principales: | Balachandran, Prasanna V., Theiler, James, Rondinelli, James M., Lookman, Turab |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4548442/ https://www.ncbi.nlm.nih.gov/pubmed/26304800 http://dx.doi.org/10.1038/srep13285 |
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