Formation enthalpies for automated computational materials design

ORAL

Abstract

The accurate calculation of formation enthalpies is crucial for computational materials design. For compounds chemically similar to their reference phases such as metal alloys, standard semi-local approximations to density functional theory (DFT) lead to accurate results [1]. When the phases are chemically dissimilar as in the case of oxides, DFT suffers from a lack of error cancellation leading to deviations of several hundred meV/atom compared to experimental values [2]. We use the automated computational materials design framework AFLOW [3] to benchmark correction schemes for ab initio formation enthalpies [2, 4]. These empirical methods can improve DFT predictions by a factor of 4 to 7. Zero-point vibrational and thermal contributions to the formation enthalpy are found to largely cancel each other.
[1] S. Curtarolo et al., Calphad 29, 163-211 (2005).
[2] V. Stevanović et al., Phys. Rev. B 85, 115104 (2012).
[3] S. Curtarolo et al., Comput. Mater. Sci. 58, 218 (2012).
[4] L. Wang et al., Phys. Rev. B 73, 195107 (2006).

*We acknowledge support by DOD-ONR (N00014-15-1-2266, N00014-17-1-2090, N00014-16-1-2326, N00014-17-1-2876). R.F. and S.C. acknowledge support from the Alexander von Humboldt foundation. C.O. acknowledges support from the NSF under Grant No. DGF-1106401.

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Presenters

  • Rico Friedrich

    • Department of Mechanical Engineering and Materials Science, Duke University
    • Center for Materials Genomics, Duke University

Authors

  • Rico Friedrich

    • Department of Mechanical Engineering and Materials Science, Duke University
    • Center for Materials Genomics, Duke University

  • Demet Usanmaz

    • Department of Mechanical Engineering and Materials Science, Duke University
    • Center for Materials Genomics, Duke University

  • Corey Oses

    • Department of Mechanical Engineering and Materials Science, Duke University
    • Mechanical Engineering and Materials Science, Duke University
    • Center for Materials Genomics, Duke University
    • Duke University

  • Andrew R Supka

    • Department of Physics and Science of Advanced Materials Program, Central Michigan University
    • Dept. of Physics and Science of Advanced Materials Program, Central Michigan University
    • Department Physics and Science of Advanced Materials Program, Central Michigan University
    • Department of Physics and Science of Advanced Materials Program, Central Michigan University, Mt. Pleasant, MI, USA

  • Marco Fornari

    • Department of Physics and Science of Advanced Materials Program, Central Michigan University
    • Dept. of Physics and Science of Advanced Materials Program, Central Michigan University
    • Department Physics and Science of Advanced Materials Program, Central Michigan University
    • Central Michigan University

  • Marco Buongiorno Nardelli

    • Department of Physics and Department of Chemistry, University of North Texas
    • Department of Physics, University of North Texas, Denton, TX
    • Department of Physics, University of North Texas
    • Physics, University of North Texas, Denton, TX, USA
    • University of North Texas
    • Univ. North Texas

  • Cormac Toher

    • Department of Mechanical Engineering and Materials Science, Duke University
    • Mechanical Engineering and Materials Science, Duke University
    • Center for Materials Genomics, Duke University
    • Duke University

  • Stefano Curtarolo

    • Materials Science, Electrical Engineering, Physics and Chemistry, Duke University
    • Mechanical Engineering and Materials Science, Duke University
    • Materials Science and Engineering, Center for Materials Genomics, Duke University, Durham, NC
    • Center for Materials Genomics, Duke University
    • Duke University
    • Department of Mechanical Engineering and Materials Science, Duke University
    • Materials Science, Electrical Engineering, Physics and Chemistry, Duke University, Durham, NC, USA