Neural network interatomic potential for the phase change material GeTe

Gabriele C. Sosso, Giacomo Miceli, Sebastiano Caravati, Jörg Behler, and Marco Bernasconi
Phys. Rev. B 85, 174103 – Published 4 May 2012

Abstract

GeTe is a prototypical phase change material of high interest for applications in optical and electronic nonvolatile memories. We present an interatomic potential for the bulk phases of GeTe, which is created using a neural network (NN) representation of the potential-energy surface obtained from reference calculations based on density functional theory. It is demonstrated that the NN potential provides a close to ab initio quality description of a number of properties of liquid, crystalline, and amorphous GeTe. The availability of a reliable classical potential allows addressing a number of issues of interest for the technological applications of phase change materials, which are presently beyond the capability of first-principles molecular dynamics simulations.

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  • Received 12 January 2012

DOI:https://doi.org/10.1103/PhysRevB.85.174103

©2012 American Physical Society

Authors & Affiliations

Gabriele C. Sosso1, Giacomo Miceli1,*, Sebastiano Caravati2, Jörg Behler3, and Marco Bernasconi1,†

  • 1Dipartimento di Scienza dei Materiali, Università di Milano-Bicocca, Via R. Cozzi 53, I-20125 Milano, Italy
  • 2Department of Chemistry and Applied Biosciences, ETH Zurich, and Facoltà di Informatica, Istituto di Scienze Computazionali, Università della Svizzera Italiana, Via Giuseppe Buffi 13, 6900 Lugano, Switzerland
  • 3Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum, D-44780 Bochum, Germany

  • *Current address: Institute of Theoretical Physics, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland.
  • marco.bernasconi@unimib.it

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Vol. 85, Iss. 17 — 1 May 2012

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