Electronic structure prediction via data-mining the empirical pseudopotential method

被引:11
作者
Zenasni, H. [1 ]
Aourag, H. [1 ]
Broderick, S. R. [2 ]
Rajan, K. [2 ]
机构
[1] Univ Abou Bakr Belkaid, Dept Phys, LEPM, URMER, Tilimsen 13000, Algeria
[2] Iowa State Univ, Dept Mat Sci & Engn, Ames, IA 50011 USA
来源
PHYSICA STATUS SOLIDI B-BASIC SOLID STATE PHYSICS | 2010年 / 247卷 / 01期
基金
美国国家科学基金会;
关键词
PRINCIPAL COMPONENT ANALYSIS; DESIGN; GAAS;
D O I
10.1002/pssb.200945268
中图分类号
O469 [凝聚态物理学];
学科分类号
070205 ;
摘要
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
引用
收藏
页码:115 / 121
页数:7
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