Modeling Equilibration Dynamics of Hyperthermal Products of Surface Reactions Using Scalable Neural Network Potential with First-Principles Accuracy

Equilibration dynamics of hot oxygen atoms followingthe dissociationof O-2 on Pd(100) and Pd(111) surfaces are investigatedby molecular dynamics simulations based on a scalable neural networkpotential enabling first-principles description of the interactionof O-2 and O interacting with variable Pd supercells. Byanalyzing hundreds of trajectories with appropriate initial sampling,the measured distance distribution of equilibrated atom pairs on Pd(111)is well reproduced. However, our results on Pd(100) suggest that theballistic motion of hot atoms predicted previously is a rare eventunder ideal conditions, while initial molecular orientation and surfacethermal fluctuation could significantly affect the overall postdissociationdynamics. On both surfaces, dissociated hyperthermal oxygen atoms primarily locate their nascent positions and experience a similarrandom walk motion nearby.

Automated summary

The equilibration dynamics of hot oxygen atoms following the dissociation of O-2 on Pd(100) and Pd(111) surfaces were investigated using molecular dynamics simulations. The results showed that the initial molecular orientation and surface thermal fluctuation significantly influenced the overall post-dissociation dynamics.