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

Abstract

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.