Data for Direct grid-based nonadiabatic dynamics on machine-learned potential energy surfaces : application to spin-forbidden processes

To date, our approach has been demonstrated in the ground-state dynamics and non-adiabatic spin-allowed dynamics of several molecular systems.

Expanding on this successful previous work, this Article demonstrates how our ML-based quantum dynamics scheme can be adapted to model non-adiabatic dynamics for spin-forbidden processes such as inter-system crossing (ISC), opening up new possibilities for modelling chemical dynamic phenomena driven by spin-orbit coupling. After describing modifications to diabatization schemes to enable accurate and robust treatment or electronic states of different spin-multiplicity, we demonstrate our methodology in applications to modelling ISC in SO2 and thioformaldehyde, benchmarking our results against previous trajectory-based calculations.