Universal fragment descriptors for predicting properties of inorganic crystals
Machine learning methods can be useful for materials discovery; however certain properties remain difficult to predict. Here, the authors present a universal machine learning approach for modelling the properties of inorganic crystals, which is validated for eight electronic and thermomechanical pro...
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| Huvudupphov: | , , , , , |
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| Materialtyp: | Artigo |
| Språk: | Inglês |
| Utgiven: |
Nature Portfolio
2017-06-01
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| Serie: | Nature Communications |
| Länkar: | https://doi.org/10.1038/ncomms15679 |
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