The characterization of the interaction between nano
or sub-nanoparticles
with a support nowadays increasingly relies on computational modeling
by means of the density functional theory calculations. These provide
valuable atomic-detail understanding of the structure and energetics
of supported clusters, but it is still challenging to find (or design)
structural models that are representative of real systems in terms
of size, structure, and composition. In this study, we have applied
an extensive and systematic approach combining global optimization
based on an evolutionary algorithm with atomistic ab initio thermodynamics
for finding stable structures of a relevant material for catalytic
methanol synthesis: Cu(111)-supported Zn
y
O
x
clusters. We identify the ZnO3 motif as the elementary building block of such clusters,
on which we recently have investigated the full catalytic process
for methanol synthesis [Reichenbach, T.; Mondal, K.; Jäger,
M.; Vent-Schmidt, T.; Himmel, D.; Dybbert, V.; Bruix, A.; Krossing,
I.; Walter, M.; Moseler, M. J. Catal., 2018,
360, 168–174]. With the collection of global
minima of Cu(111)-supported Zn
y
O
x
clusters resulting from this large-scale global
optimization effort, we assess the effect of size, gas-phase conditions,
and support interactions on the phase diagrams, reactivity, and structural
properties of the Zn
y
O
x
particles. We find moderate size-effects that are mostly related
to the differences in stable Zn/O ratios of the identified global
minima and to the formation of different sites in larger clusters.
In contrast, large differences in the oxidation state of the clusters
as defined by the gas-phase conditions significantly affect the geometry,
electronic structure, and reactivity of the Zn
y
O
x
particles. This highlights the
importance of thoroughly sampling structures with different stoichiometry
and appropriately assessing their stability using a detailed thermodynamics
analysis.