Big data of materials science: critical role of the descriptor.

نویسندگان

  • Luca M Ghiringhelli
  • Jan Vybiral
  • Sergey V Levchenko
  • Claudia Draxl
  • Matthias Scheffler
چکیده

Statistical learning of materials properties or functions so far starts with a largely silent, nonchallenged step: the choice of the set of descriptive parameters (termed descriptor). However, when the scientific connection between the descriptor and the actuating mechanisms is unclear, the causality of the learned descriptor-property relation is uncertain. Thus, a trustful prediction of new promising materials, identification of anomalies, and scientific advancement are doubtful. We analyze this issue and define requirements for a suitable descriptor. For a classic example, the energy difference of zinc blende or wurtzite and rocksalt semiconductors, we demonstrate how a meaningful descriptor can be found systematically.

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عنوان ژورنال:
  • Physical review letters

دوره 114 10  شماره 

صفحات  -

تاریخ انتشار 2015