A genetic algorithmic approach to structural optimization of supported metal particles.

Bjork Hammer
Aarhus University

We outline an efficient implementation of a genetic search algorithm used in conjunction with total energies evaluated with density functional theory (DFT). The method is applied to describe the adhesion of Au8 to an F center on an MgO support. Despite that this system has been addressed by DFT methods for more than a decade, we show that the use of an unbiased, automated search algorithm provides new structures that are more stable than any other hitherto known ones. The activity of the Au clusters in terms of oxygen bonding is investigated both manually and using the automated search algorithm. Some very stable adsorption configurations of molecular oxygen are identified and discussed in relation to finite size effects versus ensemble effects.

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