Ab initio quality neural-network potential for sodium

Hagai Eshet, Rustam Z. Khaliullin, Thomas D. Kühne, Jörg Behler, and Michele Parrinello
Phys. Rev. B 81, 184107 – Published 14 May 2010

Abstract

An interatomic potential for high-pressure high-temperature (HPHT) crystalline and liquid phases of sodium is created using a neural-network (NN) representation of the ab initio potential-energy surface. It is demonstrated that the NN potential provides an ab initio quality description of multiple properties of liquid sodium and bcc, fcc, and cI16 crystal phases in the PT region up to 120 GPa and 1200 K. The unique combination of computational efficiency of the NN potential and its ability to reproduce quantitatively experimental properties of sodium in the wide PT range enables molecular-dynamics simulations of physicochemical processes in HPHT sodium of unprecedented quality.

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  • Received 15 February 2010

DOI:https://doi.org/10.1103/PhysRevB.81.184107

©2010 American Physical Society

Authors & Affiliations

Hagai Eshet1,*, Rustam Z. Khaliullin1,†, Thomas D. Kühne2,3, Jörg Behler4, and Michele Parrinello1

  • 1Department of Chemistry and Applied Biosciences, ETH Zürich, USI Campus, via G. Buffi 13, 6900 Lugano, Switzerland
  • 2Institute of Physical Chemistry and Center of Computational Sciences, Staudinger Weg 9, D-55128 Mainz, Germany
  • 3Johannes Gutenberg University of Mainz, Staudinger Weg 9, D-55128 Mainz, Germany
  • 4Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum, D-44780 Bochum, Germany

  • *hagai.eshet@gmail.com
  • rustam@khaliullin.com

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Vol. 81, Iss. 18 — 1 May 2010

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