Defect Segregation, Water Layering, and Proton Transfer at Zirconium Oxynitride/Water Interface Examined Using Neural Network Potential

Zr oxides and oxynitrides are promising candidates to
replace precious
metal cathodes in polymer electrolyte fuel cells. Oxygen reduction
reaction activity in this class of materials has been correlated with
the amount of oxygen vacancies, but a microscopic understanding of
this correlation is still lacking. To address this, we simulate a
defective Zr7O8N4/H2O
interface model and compare it with a pristine ZrO2/H2O interface model. First, ab initio replica exchange Monte
Carlo sampling was performed to determine defect segregation at the
surface in the oxynitride slab model, then molecular dynamics accelerated
by neural network potentials was used to obtain 1000 independent trajectories
of 500 ps-dynamics to attain sufficient statistical accuracy of the
solid/liquid interface structure. The presence of oxygen vacancies
on the surface was found to clearly modify the local adsorption structure:
water molecules were found to adsorb preferentially on Zr atoms surrounding
oxygen vacancies, but not on the oxygen vacancies themselves. The
fact that oxygen vacancy sites are free from poisoning by water molecules
may explain the activity enhancement in defective systems. The layering
of water molecules was also modified considerably, which should influence
the proton and O2 transport near the interfaces which is
another parameter that determines the overall activity. Differences
in the details of proton transfer on the defective and pristine surfaces
are also discussed.