The interplay of solvation and polarization effects on ion pairing in nanoconfined electrolytes

21 February 2024, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


The nature of ion-ion interactions in electrolytes confined to nanoscale pores has important implications for energy storage and separations 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.


Ion pairing
Machine learning potentials
Two dimensional materials
Molecular simulation

Supplementary materials

Supporting information: The interplay of solvation and polarization effects on ion pairing in nanoconfined electrolytes
Details on neural network potential development and validation; simulation methods; details on the potential of mean force calculation; additional results, including finite size effect tests and ion pairing predictions of a classical force field.


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