The nature of ion–ion interactions in electrolytes
confined
to nanoscale pores has important implications for energy storage and
separation technologies. However, the physical effects dictating the
structure of nanoconfined electrolytes remain debated. Here we employ
machine-learning-based molecular dynamics simulations to investigate
ion–ion interactions with density functional theory level accuracy
in a prototypical confined electrolyte, aqueous NaCl within graphene
slit pores. We find that the free energy of ion pairing in highly
confined electrolytes deviates substantially from that in bulk solutions,
observing a decrease in contact ion pairing but an increase in solvent-separated
ion pairing. These changes arise from an interplay of ion solvation
effects and graphene’s electronic structure. Notably, the behavior
observed from our first-principles-level simulations is not reproduced
even qualitatively with the classical force fields conventionally
used to model these systems. The insight provided in this work opens
new avenues for predicting and controlling the structure of nanoconfined
electrolytes.