Berlin 2018 – scientific programme

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O: Fachverband Oberflächenphysik

O 100: Nanostructures at surfaces: Dots, particles, clusters II

O 100.2: Talk

Thursday, March 15, 2018, 15:30–15:45, MA 141

Studying Copper Growth on Zinc Oxide Utilizing a Neural Network Potential — •Martín Leandro Paleico and Jörg Behler — Universität Göttingen, Theoretische Chemie, Tammannstr. 6, 37077 Göttingen, Germany

The catalyst used in the industrial synthesis of methanol is composed of large copper and zinc oxide nanoparticles. Studying this system requires a simulation method capable of handling thousands of atoms with ab initio accuracy, but with computational efficiency comparable to classical force fields. For this purpose, a Neural Network Potential (NNP) has been trained to reproduce the potential energy surface of the system, making use of DFT calculations as reference data.

The current work focuses on the initial results for the ternary copper-zinc oxide system. Specifically, we investigate the growth of copper clusters and films on zinc oxide surfaces using basin hopping Monte Carlo simulations, utilizing a NNP to provide the required energies and forces.