4.3 Article

Electronic structure prediction via data-mining the empirical pseudopotential method

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WILEY-V C H VERLAG GMBH
DOI: 10.1002/pssb.200945268

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  1. National Science Foundation International Materials Institute [DMR-08-33853]
  2. AFOSR [FA95500610501]
  3. DARPA Center for Interfacial Engineering for MEMS (CIEMS) [1891874036790B]

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We introduce a new approach for accelerating the calculation of the electronic structure of new materials by utilizing the empirical pseudopotential method combined with data mining tools. Combining data mining with the empirical pseudopotential method allows us to convert an empirical approach to a predictive approach. Here we consider tetrahedrally bounded III-V Bi semiconductors, and through the prediction of form factors based on basic elemental properties we can model the band structure and charge density for these semi-conductors, for which limited results exist. This work represents a unique approach to modeling the electronic structure of a material which may be used to identify new promising semi-conductors and is one of the few efforts utilizing data mining at an electronic level. (C) 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

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