Machine Learning Photodynamics Unveils a Controlled H$_2$ Loss Channel in Methaniminium Cation

TL;DR

This study uncovers a new UV-induced photochemical pathway in methaniminium cation leading to HCNH$^+$ formation, using advanced quantum calculations and machine learning to control the process.

Contribution

It introduces a novel H$_2$ loss channel in methaniminium cation photochemistry, demonstrated through high-level computations and machine learning-accelerated dynamics.

Findings

Identification of a new S$_1$/S$_0$ conical intersection mediating H$_2$ loss.

Confirmation of direct H$_2$ elimination via trajectory surface hopping.

Machine learning enables mode-specific pre-excitation to control the photochemical pathway.

Abstract

The methaniminium cation, CH$_2$NH$_2^+$, plays an important role in Titan's N$_2$--CH$_4$ atmospheric chemistry. As the simplest protonated Schiff base (PSB), it also serves as a model for studying the nonadiabatic dynamics of retinal PSB, the chromophore central to vertebrate vision. While previous studies have established CN bond cleavage and photoisomerization as the primary pathways in the photochemistry of CH$_2$NH$_2^+$, we now report a new UV-induced photochemical pathway to HCNH$^+$, the dominant ion in Titan's upper atmosphere. Through high-level XMCQDPT2 and CASSCF(12,12) calculations, we identify a novel S$_1$/S$_0$ conical intersection that mediates the concerted double H-atom elimination from the carbon center of CH$_2$NH$_2^+$, yielding carbene CNH$_2^+$ as a direct precursor to HCNH$^+$. On-the-fly trajectory surface hopping dynamics confirm the presence of direct H$_2$ loss following excitation to either the S$_2$ or S$_1$ state. Furthermore, our large-scale, machine learning-accelerated simulations reveal that mode-specific pre-excitation can selectively funnel the dynamics into this new channel via the vibronically allowed S$_1$ state, enabling targeted control of the photochemical outcome.