Electrolyte solutions and ionic liquids (collectively, “ionic fluids”) are all-important across the biological [1] and physical sciences [2] – they determine effective interactions between solutes, and their nonequilibrium behavior determines the efficiency of energy storage devices. Yet, despite over a century of research, a comprehensive understanding of ionic fluids has remained elusive.

The challenge presented by ionic fluids is that they are inherently multiscale systems. At equilibrium, short-ranged “steric” interactions compete with the long-ranged Coulomb interactions, limiting the accuracy of standard theories such as Debye-Hückel and Poisson-Boltzmann to relatively low concentrations. Away from equilibrium, the gaps in our understanding are even more severe [3]. While molecular simulations in principle encode all relevant physics, they are limited by the accuracy of the interatomic potentials, small system sizes, and adequate statistical sampling. Theoretical techniques such as classical density functional theory (cDFT) [4] and integral equations theories [5] potentially offer an exact description of the statistical mechanics of ionic fluids, yet necessary approximations have largely limited their insights to the qualitative rather than quantitative level. 

Recent advances across many areas of theoretical and computational molecular science, coupled with ever-increasing temporal and spatial resolution of available experimental techniques, suggest that we are closer than ever to attaining an accurate, yet computationally tractable description of ionic fluids. For example, machine learned interatomic potentials (MLIPs) are now commonplace for simple liquids, though accurately incorporating long-ranged electrostatics remains a highly active research area [6]. cDFT approaches have evolved to a point of accurately describing solvation phenomena [7]. Combining cDFT approaches with ML offers an appealing new approach to modelling ionic fluids [8], including electromechanical phenomena, while stochastic DFT methods appear promising for efficiently describing nonequilibrium relaxation [9]. Simulating systems under constant electrochemical bias has also seen rapid development in recent years, including the modelling of impedance [10] and amperometry [11], and accounting for effects of finite screening in metallic electrodes [12] and quantum capacitance [13]. Experimentally, advances in second harmonic scattering revealed underscreening with unprecedented detail [14], although the anomalously long ranged underscreening reported in confined geometry with surface force measurements remains unexplained [15]. Meanwhile, observation of a dense liquid phase as precursor to crystal formation in calcium carbonate solutions hints at delicate ion-specific effects [16]. Vibrational sum frequency experiments have recently been used to probe the dynamics of the electric double layer, allowing for a direct benchmark in terms of time and length scales for molecular simulations [17]. 

In this workshop, we will bring together theoretical, simulation, and experimental researchers working on ionic fluids, with the aim of identifying how these recent advances can be used to collectively tackle the major outstanding issues in this topic.