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The Interplay of Solvation and Polarization Effects on Ion Pairing in Nanoconfined Electrolytes.

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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.



electrolytes, ion pairing, machine-learning potentials, molecular simulations, nanoconfinement, two-dimensional materials

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Nano Lett

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American Chemical Society (ACS)
European Commission Horizon 2020 (H2020) ERC (835073)
EC Horizon Europe ERC (101071937)
EPSRC (EP/T022159/1)
Schmidt Science Fellows, in partnership with the Rhodes Trust; Trinity College, Cambridge; Gates Cambridge Trust; Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) project number 500244608; European Research Council advanced fellowship (Grant No. 835073); Royal Society Research Professorship; European Research Council project (Grant No. 101071937)