Ionic fluids under conductive confinement are central to technologies such as batteries, supercapacitors, and fuel cells. Their interfacial behavior governs energy storage and electrochemical processes. Despite their importance, the thermodynamics of even simple models-such as the charged Lennard-Jones fluid-remain underexplored in this regime. We present an extended Wang-Landau sampling approach to efficiently compute the density of states of charged mixtures with respect to the particle number. The method supports simulations in both bulk and confined geometries. Combined with the constant potential method, it also enables the study of effects due to confining electrodes. We employ this approach to study symmetric, binary mixtures of charged Lennard-Jones particles-the modified restricted primitive model-in bulk, in inert confinement, and in conductive confinement at the potential of zero charge. Our results show that confinement shifts the vapor-liquid critical point to lower temperatures and higher densities compared to bulk, in line with the classical concept of capillary condensation. Importantly, conductive boundaries significantly lower the chemical potential of coexistence relative to inert confinement. For both confinement types, we find a minimal pore size below which no phase transition occurs, corresponding to a super-critical fluid. These findings offer deeper insight into the phase behavior of ionic fluids in energy-relevant porous environments.

Long-range interactions and electric response are essential for accurate modeling of condensed-phase systems, but capturing them efficiently remains a challenge for atomistic machine learning. Traditionally, these two phenomena can be represented by static charges that underlie Coulomb interactions between atoms, and dynamic charges such as atomic polar tensors-aka Born effective charges-describing the response to an external electric field. We critically compare different approaches to learn both types of charges within a single model architecture, taking bulk water and water clusters as paradigmatic examples: (1) learning them independently; (2) coupling static and dynamic charges based on their physical relationship with a single global coupling constant to account for dielectric screening; (3) coupled learning with a local, environment-dependent screening factor. In the coupled case, correcting for dielectric screening is essential, yet the common assumption of homogeneous, isotropic screening breaks down in heterogeneous systems such as water clusters. A learned, environment-dependent screening restores high accuracy for the dynamic charges. However, the accuracy gain over independent dynamic predictions is negligible, while the computational cost increases compared to using separate models for static and dynamic charges. This suggests that, despite the formal connection between the two charge types, modeling them independently is the more practical choice for both condensed-phase and isolated cluster systems.

The dielectric response of nano-confined fluids is crucial across technologies and biological systems, yet its calculation and interpretation from molecular simulations are often muddled by unclear boundary conditions. We re-derive the Green–Kubo relation for the spatially resolved linear dielectric response of fluids in planar confinement, explicitly accounting for boundary conditions and showing that equilibrium-derived profiles agree with those obtained from external fields. We identify common misconceptions in the literature and outline how microscopic dielectric behavior can be coarse-grained to connect with experimental observables. Simulations show that water retains a bulk-like dielectric response down to ∼ 1 nm confinement. The reduced effective dielectric response that governs capacitance arises from the placement of the dielectric interface. Using effective-medium theory, we demonstrate that long-range reductions reported in experiments and theory are consistent with bulk-like behavior beyond about 1 nm from the surface. The effective response naturally maps onto an interfacial capacitance, and the dielectric properties of simulated water are robust across simulation setups and water models, reflecting universal polarization correlations.

The surface charge of an open water surface is crucial for solvation phenomena and interfacial processes in aqueous systems. However, the magnitude of the charge is controversial, and the physical mechanism of charging remains incompletely understood. Here we identify a previously overlooked physical mechanism determining the surface charge of water. Using accurate charge measurements of water microdrops, we demonstrate that the water surface charge originates from the electrostatic effects in the contact line vicinity of three phases, one of which is water. Our experiments, theory, and simulations provide evidence that a junction of two aqueous interfaces (e.g., liquid-solid and liquid-air) develops a pH-dependent contact potential difference Δϕ due to the longitudinal charge redistribution between two contacting interfaces. This universal static charging mechanism may have implications for the origin of electrical potentials in biological, nanofluidic, and electrochemical systems and helps to predict and control the surface charge of water in various experimental environments.

The open water surface is known to be charged. Yet, the magnitude of the charge and the physical mechanism of the charging remain unclear, causing heated debates across the scientific community. Here we directly measure the charge Q of microdrops ejected from hydrophilic and hydrophobic capillaries and show that the water surface can take both positive or negative charge values depending on pH and the capillary type. Our experiments, theory, and simulations provide evidence that a junction of two aqueous interfaces with a different ion adsorption energy (e.g., liquid-solid and liquid-air interfaces) develops a pH-dependent contact potential difference {\Delta}{\phi} up to 52 mV. The longitudinal charge transfer between the interfaces stimulated by {\Delta}{\phi} determines the charge of the open water surface. The suggested static electrification mechanism provides far-reaching insights into the origin of electrical potentials in biological and electrochemical energy systems.

The squirmer is a simple yet instructive model for microswimmers, which employs an effective slip velocity on the surface of a spherical swimmer to describe its self-propulsion. We solve the hydrodynamic flow problem with the lattice Boltzmann (LB) method, which is well-suited for time-dependent problems involving complex boundary conditions. Incorporating the squirmer into LB is relatively straightforward, but requires an unexpectedly fine grid resolution to capture the physical flow fields and behaviors accurately. We demonstrate this using four basic hydrodynamic tests: two for the far-field flow—accuracy of the hydrodynamic moments and squirmer-squirmer interactions—and two that require the near field to be accurately resolved—a squirmer confined to a tube and one scattering off a spherical obstacle—which LB is capable of doing down to the grid resolution. We find good agreement with (numerical) results obtained using other hydrodynamic solvers in the same geometries and identify a minimum required resolution to achieve this reproduction. We discuss our algorithm in the context of other hydrodynamic solvers and present an outlook on its application to multi-squirmer problems.

Self-propelled particles have been experimentally shown to orbit spherical obstacles and move along surfaces. Here, we theoretically and numerically investigate this behavior for a hydrodynamic squirmer interacting with spherical objects and flat walls using three different methods of approximately solving the Stokes equations: The method of reflections, which is accurate in the far field; lubrication theory, which describes the close-to-contact behavior; and a lattice Boltzmann solver that accurately accounts for near-field flows. The method of reflections predicts three distinct behaviors: orbiting/sliding, scattering, and hovering, with orbiting being favored for lower curvature as in the literature. Surprisingly, it also shows backward orbiting/sliding for sufficiently strong pushers, caused by fluid recirculation in the gap between the squirmer and the obstacle leading to strong forces opposing forward motion. Lubrication theory instead suggests that only hovering is a stable point for the dynamics. We therefore employ lattice Boltzmann to resolve this discrepancy and we qualitatively reproduce the richer far-field predictions. Our results thus provide insight into a possible mechanism of mobility reversal mediated solely through hydrodynamic interactions with a surface.