Metadynamics Simulations of the High-Pressure Phases of Silicon Employing a High-Dimensional Neural Network Potential

Jörg Behler, Roman Martoňák, Davide Donadio, and Michele Parrinello
Phys. Rev. Lett. 100, 185501 – Published 5 May 2008

Abstract

We study in a systematic way the complex sequence of the high-pressure phases of silicon obtained upon compression by combining an accurate high-dimensional neural network representation of the density-functional theory potential-energy surface with the metadynamics scheme. Starting from the thermodynamically stable diamond structure at ambient conditions we are able to identify all structural phase transitions up to the highest-pressure fcc phase at about 100 GPa. The results are in excellent agreement with experiment. The method developed promises to be of great value in the study of inorganic solids, including those having metallic phases.

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  • Received 6 December 2007

DOI:https://doi.org/10.1103/PhysRevLett.100.185501

©2008 American Physical Society

Authors & Affiliations

Jörg Behler1,2, Roman Martoňák1,3, Davide Donadio1,4, and Michele Parrinello1

  • 1Department of Chemistry and Applied Biosciences, ETH Zurich, USI-Campus, Via Giuseppe Buffi 13, CH-6900 Lugano, Switzerland
  • 2Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum, D-44780 Bochum, Germany
  • 3Department of Experimental Physics, Faculty of Mathematics, Physics and Informatics, Comenius University, Mlynská dolina F2, 842 48 Bratislava, Slovakia
  • 4Department of Chemistry, University of California Davis, One Shields Avenue, Davis, California 95616, USA

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Issue

Vol. 100, Iss. 18 — 9 May 2008

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