Accurate tight-binding Hamiltonians for two-dimensional and layered materials

Luis A. Agapito, Marco Fornari, Davide Ceresoli, Andrea Ferretti, Stefano Curtarolo, and Marco Buongiorno Nardelli
Phys. Rev. B 93, 125137 – Published 22 March 2016

Abstract

We present a scheme to controllably improve the accuracy of tight-binding Hamiltonian matrices derived by projecting the solutions of plane-wave ab initio calculations on atomic-orbital basis sets. By systematically increasing the completeness of the basis set of atomic orbitals, we are able to optimize the quality of the band-structure interpolation over wide energy ranges including unoccupied states. This methodology is applied to the case of interlayer and image states, which appear several eV above the Fermi level in materials with large interstitial regions or surfaces such as graphite and graphene. Due to their spatial localization in the empty regions inside or outside of the system, these states have been inaccessible to traditional tight-binding models and even to ab initio calculations with atom-centered basis functions.

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  • Received 11 January 2016
  • Revised 4 March 2016

DOI:https://doi.org/10.1103/PhysRevB.93.125137

©2016 American Physical Society

Authors & Affiliations

Luis A. Agapito1,2, Marco Fornari3,4, Davide Ceresoli5, Andrea Ferretti6, Stefano Curtarolo4,7, and Marco Buongiorno Nardelli2,4,*

  • 1Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina 27708, USA
  • 2Department of Physics, University of North Texas, Denton, Texas 76203, USA
  • 3Department of Physics, Central Michigan University, Mount Pleasant, Michigan 48859, USA
  • 4Center for Materials Genomics, Duke University, Durham, North Carolina 27708, USA
  • 5Consiglio Nazionale delle Ricerche, ISTM, Istituto di Scienze e Tecnologie Molecolari, I-20133 Milano, Italy
  • 6Consiglio Nazionale delle Ricerche, NANO S3 Center, Istituto Nanoscienze, I-41125 Modena, Italy
  • 7Materials Science, Electrical Engineering, Physics and Chemistry, Duke University, Durham, North Carolina 27708, USA

  • *mbn@unt.edu

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Vol. 93, Iss. 12 — 15 March 2016

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