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O: Fachverband Oberflächenphysik

O 41: Poster Session I (Semiconductor Substrates: Epitaxy and growth; Semiconductor Substrates: Adsorbtion; Semiconductor Substrates: Solid-liquid interfaces; Semiconductor Substrates: Clean surfaces; Oxides and insulators: Epitaxy and growth; Oxides and insulators: Adsorption; Oxides and insulators: Clean surfaces; Organic, polymeric and biomolecular films - also with adsorbates; Organic electronics and photovoltaics, Surface chemical reactions; Heterogeneous catalysis; Phase transitions; Particles and clusters; Surface dynamics; Surface or interface magnetism; Electron and spin dynamics; Spin-Orbit Interaction at Surfaces; Electronic structure; Nanotribology; Solid/liquid interfaces; Graphene; Others)

O 41.29: Poster

Dienstag, 23. März 2010, 18:30–21:00, Poster B1

High-Dimensional Neural Network Potentials for Multicomponent Systems: First Applications to Zinc Oxide — •Nongnuch Artrith, Tobias Morawietz, Marcus Maschke, and Jörg Behler — Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum, D-44780 Bochum, Germany

Recently, artificial Neural Networks (NN) trained to first-principles data have shown to provide accurate potential energy surfaces for systems containing a single atomic species. In this work we present an extension of the NN approach to multicomponent systems by introducing physically motivated terms to deal with long-range interactions. This is a necessary condition for studying binary systems and general multicomponent systems with significant charge transfer. The capabilities of the method are demonstrated for crystal structures, amorphous structures, clusters, and surfaces of zinc oxide as a benchmark system. We show that the predicted energies and forces are in excellent agreement with reference density-functional theory calculations.