Regensburg 2019 – wissenschaftliches Programm

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O: Fachverband Oberflächenphysik

O 29: Nanostructures at Surfaces III: Dots, Particles, and Clusters

O 29.10: Vortrag

Dienstag, 2. April 2019, 12:45–13:00, H25

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 results for model ternary copper-zinc oxide system. Specifically, we investigate the growth of copper clusters and films on zinc oxide surfaces using both grid and grid-free basin hopping Monte Carlo simulations, entrenching of clusters at elevated temperatures and under an indentation force, and the behavior of copper and zinc oxide interfaces at high temperatures.