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Electronic structure prediction via data-mining the empirical pseudopotential method

Abstract

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. (Abstract Copyright [2010], Wiley Periodicals, Inc.)
Authors:
Zenasni, H; Aourag, H; [1]  Broderick, S R; Rajan, K [2] 
  1. LEPM, URMER, Departement of Physics, University Abou Bakr Belkaid, Tlemcen 13000 (Algeria)
  2. Department of Materials Science and Engineering, Iowa State University, Ames, Iowa 50011-2230 (United States)
Publication Date:
Jan 15, 2010
Product Type:
Journal Article
Resource Relation:
Journal Name: Physica Status Solidi B (Basic Research); Journal Volume: 247; Journal Issue: 1; Other Information: With 7 figs., 6 tabs., 29 refs.; SICI: 0370-1972(201001)247:1<115::AID-PSSB200945268>3.0.TX;2-N
Subject:
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY; ALUMINIUM ALLOYS; BAND THEORY; BISMUTH ALLOYS; CHARGE DENSITY; COVALENCE; ELECTRONIC STRUCTURE; FORM FACTORS; GALLIUM ALLOYS; INDIUM ALLOYS; LATTICE PARAMETERS; SEMICONDUCTOR MATERIALS; VALENCE
OSTI ID:
21275547
Country of Origin:
Germany
Language:
English
Other Identifying Numbers:
Journal ID: ISSN 0370-1972; PSSBBD; TRN: DE10G1750
Availability:
Available from: http://dx.doi.org/10.1002/pssb.200945268
Submitting Site:
DE
Size:
page(s) 115-121
Announcement Date:
Mar 09, 2010

Citation Formats

Zenasni, H, Aourag, H, Broderick, S R, and Rajan, K. Electronic structure prediction via data-mining the empirical pseudopotential method. Germany: N. p., 2010. Web. doi:10.1002/PSSB.200945268.
Zenasni, H, Aourag, H, Broderick, S R, & Rajan, K. Electronic structure prediction via data-mining the empirical pseudopotential method. Germany. doi:10.1002/PSSB.200945268.
Zenasni, H, Aourag, H, Broderick, S R, and Rajan, K. 2010. "Electronic structure prediction via data-mining the empirical pseudopotential method." Germany. doi:10.1002/PSSB.200945268. https://www.osti.gov/servlets/purl/10.1002/PSSB.200945268.
@misc{etde_21275547,
title = {Electronic structure prediction via data-mining the empirical pseudopotential method}
author = {Zenasni, H, Aourag, H, Broderick, S R, and Rajan, K}
abstractNote = {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. (Abstract Copyright [2010], Wiley Periodicals, Inc.)}
doi = {10.1002/PSSB.200945268}
journal = {Physica Status Solidi B (Basic Research)}
issue = {1}
volume = {247}
place = {Germany}
year = {2010}
month = {Jan}
}