On the development of an original mesoscopic model to predict the capacitive properties of carbon-carbon supercapacitors

TL;DR

This paper introduces a novel mesoscopic lattice model that efficiently predicts the capacitive properties of carbon-carbon supercapacitors, incorporating molecular simulation and experimental data, and analyzing effects of pore size and solvent presence.

Contribution

The paper presents an original, significantly faster mesoscopic model that accurately predicts supercapacitor properties based on structural and dynamical inputs from simulations and experiments.

Findings

Model predicts ion adsorption and capacitance within experimental ranges.

Capacitance depends strongly on pore size and solvent type.

Different trends observed for ionic liquids and organic electrolytes.

Abstract

We report on the development of an original mesoscopic lattice model to predict structural, dynamical and capacitive properties of carbon-carbon supercapacitors. The model uses input from molecular simulations, such as free energy profiles to describe the ion adsorption, and experiments, such as energy barriers for transitions between lattice sites. The model developed is approximately 10,000 times faster than common molecular simulations. We apply this model to a set of carbon structures with well-defined pore sizes and investigate the solvation effect by doing simulations with neat ionic liquids as well as acetonitrile-based electrolytes. We show that our model is able to predict quantities of adsorbed ions and capacitances in a range compatible with experimental values. We show that there is a strong dependency of the calculated properties on the pore size and on the presence or absence of solvent. In particular, for neat ionic liquids, larger capacitances are obtained for smaller pores, while the opposite trend is observed for organic electrolytes.