Ab Initio Investigation of O–H Dissociation from the Al–OH2 Complex Using Molecular Dynamics and Neural Network Fitting

Abstract

The dissociation dynamics of the O-H bond in Al-OH2 is investigated on an approximated ab initio potential energy surface (PES). By adopting a dynamic sampling method, we obtain a database of 92 834 configurations. The potential energy for each point is calculated using MP2/6-311G (3df, 2p) calculations; then, a 60-neuron feed-forward neural network is utilized to fit the data to construct an analytic PES. The root-mean-square error (rmse) for the training set is reported as 0.0036 eV, while the rmse for the independent testing set is 0.0034 eV. Such excellent fitting accuracy indeed confirms the reliability of the constructed PES. Subsequently, quasi-classical molecular dynamics (MD) trajectories are performed on the constructed PES at various levels of vibrational excitation in the range of 1.03 to 2.23 eV to investigate the probability of O-H bond dissociation. The results indicate a linear relationship between reaction probability and internal energy, from which we can determine the minimum activation internal energy required for the dissociation as 0.62 eV. Moreover, the O-H bond rupture is shown to be highly correlated with the formation of Al-O bond.