Machine learning dielectric screening for the simulation of excited state properties of molecules and materials

ORAL

Abstract

Accurate and efficient predictions of absorption spectra of materials and molecules at finite temperature are essential for the understanding and rational design of broad classes of systems. We present an approach to improve the efficiency of first principles calculations of absorption spectra of complex materials at finite temperature, based on the solution of the Bethe-Salpeter Equation in finite-field (FF) [1]. We demonstrate that methods using convolutional neural networks (CNN) may be efficiently used to compute the screened Coulomb interaction and to predict finite-temperature absorption spectra of solids, liquids, nanoparticles, and heterogeneous systems, such as solid/liquid interfaces. In addition, we show that our approach may be used to derive model dielectric functions for complex systems [2].

[1] N. L. Nguyen, H. Ma, M. Govoni, F. Gygi, and G. Galli, Phys. Rev. Lett. 122, 237402 (2019).
[2] S. S. Dong, M. Govoni, and G. Galli, 2020 (preprint).

*The work was supported by MICCoM as part of the Computational Materials Science Program funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences (DOE-BES), and AMEWS Center, an Energy Frontier Research Center funded by DOE-BES.

–

Presenters

  • Sijia Dong

    • Argonne National Laboratory
    • Materials Science Division, Argonne National Laboratory

Authors

  • Sijia Dong

    • Argonne National Laboratory
    • Materials Science Division, Argonne National Laboratory

  • Marco Govoni

    • Materials Science Division and Center for Molecular Engineering, Argonne National Laboratory
    • Argonne National Laboratory
    • Materials Science Division, Argonne National Laboratory

  • Giulia Galli

    • The University of Chicago
    • Pritzker School of Molecular Engineering, The University of Chicago
    • Pritzker School of Molecular Engineering, University of Chicago
    • University of Chicago
    • Department of Chemistry, University of Chicago
    • Materials Science Division and Center for Molecular Engineering, Argonne National Laboratory