Pressure‐induced phase transitions in silicon studied by neural network‐based metadynamics simulations

Abstract We present a combination of the metadynamics method for the investigation of pressure‐induced phase transitions in solids with a neural network representation of high‐dimensional density‐functional theory (DFT) potential‐energy surfaces. In a recent illustration of the method for the complex high‐pressure phase diagram of silicon Behler et al., Phys. Rev. Lett. 100 , 185501 (2008) we have shown that the full sequence of phases can be reconstructed by a series of subsequent simulations. In the present paper we give a detailed account of the underlying methodology and discuss the scope and limitations of the approach, which promises to be a valuable tool for the investigation of a variety of inorganic materials. The method is several orders of magnitude faster than a direct coupling of metadynamics with electronic structure calculations, while the accuracy is essentially maintained, thus providing access to extended simulations of large systems. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)