[1Dp01-09] Surface Science(SS1) Physical Property

[1Dp04] Machine learning molecular dynamics simulation of vibration driven CO₂ hydrogenation to formate on Cu(111) surface

*Harry Halim¹, Yoshitada Morikawa¹ (1. Graduate School of Engineering, Osaka University)

The hydrogenation of CO₂ to formate (i.e., HCOO*) on Cu(111) is investigated by machine-learning molecular dynamics (MLMD). Benchmark of MLMD simulations to the Ab-initio MD (AIMD) shows the capability of MLMD to predict the energetics of chemical reactions in a good accuracy. The success of the hydrogenation strongly depends on the initial conditions of the incoming gas CO₂ such as vibrational modes, vibrational energy, incident angles, and translational energy. Multi-dimensional tables depicting the correlation of those of initial states to the success rate of hydrogenation will be discussed in the conference. The main outcome of this research is the combinations of initial states of CO₂ that are the most efficient ones to produce HCOO* on the surface.