Although
migration processes on low-coordination surface sites of a magnesium
oxide (MgO) surface are important in technological applications including
catalysis in gas interfaces, they are not well understood. In particular,
hydrated MgO(001) surfaces present charge transfer and ionic transport
phenomena that sometimes do not work properly in technological devices.
On the other hand, low-coordination surface sites are chemically attractive.
Given that defects and adsorbed species can be characterized by the
kinetics of surface processes, in this work, we investigated proton
mobility pathways produced from the dissociative adsorption of water
molecules on different MgO(001) surfaces: a perfect-terrace, with
an anionic vacancy, and with an Al-doped + cationic vacancy. For that
purpose, we employed density-functional theory with periodic boundary
conditions combined with the climbing imaged nudged elastic band method
to compute energy barriers. The dissociative adsorption of water molecules
on the perfect-terrace surface depends on their state of aggregation;
the anionic vacancy was filled with hydroxyl groups, giving rise to
co-adsorbed protons, and the cationic vacancy favored the formation
of hydroxylated centers, in good agreement with experiment. The doping
and vacancies increase the surface dissociation in the absence of
co-adsorbed water molecules by decreasing the barriers of proton and
hydroxyl formation. For the different surfaces, considering perfect-terrace
surface or surface with defects, the water, hydroxyl, and proton species,
are the main sources for changing the proton migration barriers. More
free surface sites of basic residual groups follow favorable kinetic
mobility of protons on MgO and increase the stability of the migration
products, as seen in the surface with an anionic vacancy. Therefore,
we showed that defects on MgO(001) surfaces may be important in surface
proton transport due to the existence of favorable dissociative adsorption
mechanisms of water molecules producing specific residual groups needed
to lead to most stable migration pathways.