Multiscale Modeling of Aqueous Electric Double Layers

Abstract

From the stability of colloidal suspensions to the charging of electrodes, electric double layers play a pivotal role in aqueous systems. The interactions between interfaces, water molecules, ions and other solutes making up the electrical double layer span length scales from Ångstroms to micrometers and are notoriously complex. Therefore, explaining experimental observations in terms of the double layer's molecular structure has been a long-standing challenge in physical chemistry, yet recent advances in simulations techniques and computational power have led to tremendous progress. In particular, the past decades have seen the development of a multiscale theoretical framework based on the combination of quantum density functional theory, force-field based simulations and continuum theory. In this Review, we discuss these theoretical developments and make quantitative comparisons to experimental results from, among other techniques, sum-frequency generation, atomic-force microscopy, and electrokinetics. Starting from the vapor/water interface, we treat a range of qualitatively different types of surfaces, varying from soft to solid, from hydrophilic to hydrophobic, and from charged to uncharged.

NaCl, MgCl2, and AlCl3 Surface Coverages on Fused Silica and Adsorption Free Energies at pH 4 from Nonlinear Optics

“…A modified Poisson–Boltzmann model with hydration repulsion , may provide a better agreement between experiment and theory, especially when further modified with effective ion diameters at charged interfaces, as its good agreement with XPS measurements has been established for silica colloids to account for nonideal behavior (short-range ion correlations, site availability, etc.) of aqueous electrolytes at surfaces. − A related issue is the spatial variation of the (field-dependent) relative permittivity, ε r , which these models neglect, i.e., the solvent is modeled as a uniform continuum, despite large differences in reported ε r . ,,− These considerations point to the possibility that the total potential we employ to compute cation surface coverages from eq should in fact be reduced by about 50%. Figure D shows the resulting surface coverages, recomputed with eq using half of the Φ tot values reported in Figure (n.b., Φ tot,0 was kept unchanged in this calculation).…”

Parameter-Fitting-Free Continuum Modeling of Electric Double Layer in Aqueous Electrolyte

“…It is known that water molecules form a two-dimensional (2D) hydrogen bonding network on electrode surface like platinum that stabilize the water molecules and change their dielectric properties. − Although our model includes the polarization energy that accounts for the stabilization of solvent dipole for the electric field, it does not include the explicit expressions for the two-dimensional hydrogen bonding in the vicinity of the interface. The model will be capable of including these effects by setting the parameters based on further analyses.…”

“…Without specific ion adsorption, the Stern layer does not contain charged species. The dielectric constant in the Stern layer can be much smaller than that of the bulk solvent (∼an order of magnitude) due to impacts of water structure − and field effects − near the interface. Unlike in the Stern layer, ions can redistribute, depending on the electrostatic potential in the diffuse layer.…”

Sodium Triflate Water-in-Salt Electrolytes in Advanced Battery Applications: A First-Principles-Based Molecular Dynamics Study

“…This, in turn, necessitates the implementation of accurate numerical simulations capable of capturing essential details in the system behavior, encompassing local structures, charge transport mechanisms, and chemical reactions at the interfaces with electrodes. While numerous studies have explored computational methods for simulating solvent-in-salt electrolytes and ionic liquids, both in bulk − and at interfaces, − the optimal approach for modeling WiS electrolytes remains uncertain. Despite their high accuracy, first-principles calculations come with extensive computational costs.…”