Preferential ion adsorption in mixed electrolytes plays a crucial role in many practical applications, such as ion sensing and separation and in colloid science. Using all-atom molecular dynamics simulations of aqueous NaCl, CaCl₂, and NaCl-CaCl₂ solutions confined by charged amorphous silica, we show that Na⁺ ions can adsorb preferentially over Ca²⁺ ions, depending on the surface structure. We propose that this occurs when the local surface structure sterically hinders the first hydration shell of the Ca²⁺ ion. Introducing a protrusion metric as a function of protrusion of deprotonated silanols, ion-specificity is successfully predicted on isolated, vicinal, and geminal silanols alike, provided that no other deprotonated silanols are found nearby. Furthermore, we introduce a new strategy to analyze the results as a function of distance from the surface. This approach effectively removes surface roughness effects allowing for direct comparison with classical electric double layer theory and distinction of specifically adsorbed ions and electrostatically adsorbed ions.

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Despite being ubiquitous in the fields of chemistry and biology, the ion-specific effects of electrolytes pose major challenges for researchers. A lack of understanding about ion-specific surface interactions has hampered the development and application of materials for (bio-)chemical sensor applications. Here, we show that scaling a silicon nanotransistor sensor down to ~25 nm provides a unique opportunity to understand and exploit ion-specific surface interactions, yielding a surface that is highly sensitive to cations and inert to pH. The unprecedented sensitivity of these devices to Na⁺ and divalent ions can be attributed to an overscreening effect via molecular dynamics. The surface potential of multi-ion solutions is well described by the sum of the electrochemical potentials of each cation, enabling selective measurements of a target ion concentration without requiring a selective organic layer. We use these features to construct a blood serum ionogram for Na⁺, K⁺, Ca²⁺ and Mg²⁺, in an important step towards the development of a versatile, durable and mobile chemical or blood diagnostic tool.

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Surface charge controls many static and dynamic properties of soft matter and micro/nanofluidic systems, but its unambiguous measurement forms a challenge. Standard characterization methods typically probe an effective surface charge, which provides limited insight into the distribution and dynamics of charge across the interface, and which cannot predict consistently all surface-charge-governed properties. New experimental approaches provide local information on both structure and transport, but models are typically required to interpret raw data. Conversely, molecular dynamics simulations have helped showing the limits of standard models and developing more accurate ones, but their reliability is limited by the empirical interaction potentials they are usually based on. This review highlights recent developments and limitations in both experimental and computational research focusing on the liquid-solid interface. Based on recent studies, we make the case that coupling of experiments and simulations is pivotal to mitigate methodological shortcomings and address open problems pertaining to charged interfaces.@en

We present a simulation and modeling study of electro-osmotic flow of an aqueous cesium chloride solution confined in a charged amorphous silica slot. Contrasting traditional models of the electric double layer, molecular dynamics simulations indicate that there is no stagnant layer, no Stern layer conduction, and no outer Helmholtz layer. The description of the interface requires two considerations. First, a distinction has to be made between free and surface-bonded ions. The latter do not form a physical layer but rather a set of ion-surface contact pairs. Second, the mobility of the free ions is reduced relative to their bulk value. This hydrodynamic effect needs to be included. These two concepts, coupled to simple macroscopic equations, are sufficient to describe surface conductivity and electro-osmotic flow in the frame of classical mean-field treatment. We show that surface conduction is negative at high concentration, and the Bikerman formula is only valid at low concentration.

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