Deciphering Dynamics of the Cl + SiH4 → H + SiH3Cl Reaction on a Machine Learning Made Globally Accurate Full-Dimensional Potential Energy Surface

Abstract

Chemical reaction dynamics needs the joint effort from both experiment and theory, and theory is useful to rationalize the experimental results by offering intimate details of chemical reaction dynamics and to explore new reaction pathways. With the aid of machine learning, we develop here an accurate full-dimensional potential energy surface (PES) for the reaction between Cl + SiH4. This PES can describe well the hydrogen abstraction channel to HCl + SiH3. It can also give a good description for the hydrogen substitution channel to H + SiH3Cl, which is the focus of the current study and has never been reported by theory. The dynamics of this substitution channel is revealed in detail by calculating ample quasi-classical trajectories (QCTs) on the new PES. The computed product angular distributions are in good agreement with the only crossed molecular beam experiment. Both theory and experiment suggest that this channel takes place mainly via the typical SN2 inversion mechanism. Theory reveals that there also exists a novel torsion mechanism for the substitution channel. Two dynamic mechanisms are analyzed in detail. The present detailed theoretical dynamics study sheds insightful and novel understanding for this fundamentally important chemical reaction.