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    Structure maps for hcp metals from first-principles calculations

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    Date
    2010-05-10
    Authors
    Levy, O
    Hart, GLW
    Curtarolo, S
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    Abstract
    The ability to predict the existence and crystal type of ordered structures of materials from their components is a major challenge of current materials research. Empirical methods use experimental data to construct structure maps and make predictions based on clustering of simple physical parameters. Their usefulness depends on the availability of reliable data over the entire parameter space. Recent development of high-throughput methods opens the possibility to enhance these empirical structure maps by ab initio calculations in regions of the parameter space where the experimental evidence is lacking or not well characterized. In this paper we construct enhanced maps for the binary alloys of hcp metals, where the experimental data leaves large regions of poorly characterized systems believed to be phase separating. In these enhanced maps, the clusters of noncompound-forming systems are much smaller than indicated by the empirical results alone. © 2010 The American Physical Society.
    Type
    Journal article
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    http://hdl.handle.net/10161/3334
    Published Version (Please cite this version)
    10.1103/PhysRevB.81.174106
    Publication Info
    Levy, O; Hart, GLW; & Curtarolo, S (2010). Structure maps for hcp metals from first-principles calculations. Physical Review B - Condensed Matter and Materials Physics, 81(17). pp. 174106. 10.1103/PhysRevB.81.174106. Retrieved from http://hdl.handle.net/10161/3334.
    This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
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    Scholars@Duke

    Curtarolo

    Stefano Curtarolo

    Professor in the Department of Mechanical Engineering and Materials Science
    RESEARCH FIELDS Nanoscale Science of Energy Computational materials science Nanotube growth characterization Alloy theory Superlubricity on quasicrystals Superconductivity in Metal borides Genetic Approaches to QM Predictions of Materials Structures Materials for Nuclear Detection The research is multidisciplinary and makes use of state of the art techniques from fields like materials science, chemis
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