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arXiv · 1201.2026

A neural network interatomic potential for the phase change material GeTe

Abstract

GeTe is a prototypical phase change material of high interest for applications in optical and electronic non-volatile 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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Gabriele C. Sosso, Giacomo Miceli, Sebastiano Caravati, Jörg Behler, Marco Bernasconi. 2012-01-10. A neural network interatomic potential for the phase change material GeTe. https://doi.org/10.1103/physrevb.85.174103

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