(320b) Efficiently Accounting for Ion Correlations In Electrokinetic Nanofluidic Devices Using Density Functional Theory

The electrokinetic behavior of nanofluidic devices is dominated by the electrical double layers at the device walls.  Therefore, accurate, predictive models of double layers are essential for device design and optimization.  We demonstrate that density functional theory (DFT) of electrolytes is an accurate and computationally efficient method for computing finite ion size effects and the resulting ion-ion correlations that are neglected in classical double layer theories such as Poisson-Boltzmann.  DFT is designed for nanofluidic systems with small spatial dimensions, high surface charge densities, high ion concentrations, and/or large ions.  These regimes produce nonlinear phenomena such as charge inversion, wherein more counterions adsorb at the wall than is necessary to neutralize its surface charge, leading to a second layer of co-ions.  We show that DFT can predict charge inversion and other nonlinear phenomena.  DFT reproduces experimental results of ion current in single-slit nanofluidic devices and gives insights into the limits of energy conversion via streaming currents and molecular sensing.