Spatial arrangement of dynamic surface species from solid-state NMR and machine learning-accelerated MD simulations

Abstract

The surface arrangement of motional organic functionalities is explored by experimental dipolar coupling measurements and the prediction of motionally-averaged coupling constant from molecular dynamics simulations. The use of machine learning potentials was key to reaching the timescale required. The distance between dynamic surface species are important in cooperative heterogeneous catalysis.