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Impedance of nanocapacitors from molecular simulations to understand the dynamics of confined electrolytes

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Pireddu, Giovanni 
Fairchild, Connie 
Niblett, Samuel 
Cox, Stephen 
Rotenberg, Benjamin 


Nanoelectrochemical devices have become a promising candidate technology across various applications, including sensing and energy storage, and provide new plat- forms for studying fundamental properties of electrode/electrolyte interfaces. In this work, we employ constant-potential molecular dynamics simulations to investigate the impedance of gold-aqueous electrolyte nanocapacitors, exploiting a recently-introduced fluctuation-dissipation relation. In particular, we relate the frequency-dependent impedance of these nanocapacitors to the complex conductivity of the bulk electrolyte in differ- ent regimes, and use this connection to design simple but accurate equivalent circuit models. We show that the electrode/electrolyte interfacial contribution is essentially capacitive and that the electrolyte response is bulk-like even when the interelectrode distance is only a few nanometers, provided that the latter is sufficiently large com- pared to the Debye screening length. We extensively compare our simulation results with spectroscopy experiments and predictions from analytical theories. In contrast to experiments, direct access in simulations to the ionic and solvent contributions to the polarization allows us to highlight their significant and persistent anticorrelation and to investigate the microscopic origin of the timescales observed in the impedance spectrum. This work opens avenues for the molecular interpretation of impedance measurements, and offers valuable contributions for future developments of accurate coarse-grained representations of confined electrolytes.



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Proceedings of the National Academy of Sciences of the United States of America

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National Academy of Sciences
Royal Society (URF\R1\211144)
European Commission Horizon 2020 (H2020) Research Infrastructures (RI) (957189)
S.J.C. is a Royal Society University Research Fellow (Grant No. URF\R1\211144) at the University of Cambridge. SPN acknowledges funding from the European Union’s Horizon 2020 Research and Innovation Program under Grant Agreement No. 957189 (BIG-MAP project). G. P. and B. R. acknowledge funding from the European Research Council under the European Union’s Horizon 2020 research and innovation program (project SENSES, grant Agreement No. 863473). G. P. and B. R. acknowledge access to HPC resources from GENCI-IDRIS (grant no. 2022-AD010912966R1).
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