Thermodynamics of atomistic and coarse-grained models of water on nonpolar surfaces

Computing the Work of Solid-Liquid Adhesion in Systems with Damped Coulomb Interactions via Molecular Dynamics: Approaches and Insights

Recently, the dry-surface method [Langmuir2016, 31, 8335−8345] has been developed to compute the work of adhesion of solid–liquid and other interfaces using molecular dynamics via thermodynamic integration. Unfortunately, when long-range Coulombic interactions are present in the interface, a special treatment is required, such as solving additional Poisson equations, which is usually not implemented in generic molecular dynamics software, or as fixing some groups of atoms in place, which is undesirable most of the time. In this work, we replace the long-range Coulombic interactions with damped Coulomb interactions, and explore several thermal integration paths. We demonstrate that regardless of the integration path, the same work of adhesion values are obtained as long as the path is reversible, but the numerical efficiency differs vastly. Simple scaling of the interactions is most efficient, requiring as little as 8 sampling points, followed by changing the Coulomb damping parameter, while modifying the Coulomb interaction cutoff length performs worst. We also demonstrate that switching long-range Coulombic interactions to damped ones results in a higher work of adhesion by about 10 mJ/m² because of slightly different liquid molecule orientation at the solid–liquid interface, and this value is mostly unchanged for surfaces with substantially different Coulombic interactions at the solid–liquid interface. Finally, even though it is possible to split the work of adhesion into van der Waals and Coulomb components, it is known that the specific per-component values are highly dependent on the integration path. We obtain an extreme case, which demonstrates that caution should be taken even when restricting to qualitative comparison.

Bottom-up coarse-grained models for external fields and interfaces

Bottom-up coarse-grained (CG) models accurately describe the structure of homogeneous systems but sometimes provide limited transferability and a poor description of thermodynamic properties. Consequently, inhomogeneous systems present a severe challenge for bottom-up models. In this work, we examine bottom-up CG models for interfaces and inhomogeneous systems. We first analyze the effect of external fields upon the many-body potential of mean force. We also demonstrate that the multiscale CG (MS-CG) variational principle for modeling the external field corresponds to a generalization of the first Yvon-Born-Green equation. This provides an important connection with liquid state theory, as well as physical insight into the structure of interfaces and the resulting MS-CG models. We then develop and assess MS-CG models for a film of liquid methanol that is adsorbed on an attractive wall and in coexistence with its vapor phase. While pair-additive potentials provide unsatisfactory accuracy and transferability, the inclusion of local-density (LD) potentials dramatically improves the accuracy and transferability of the MS-CG model. The MS-CG model with LD potentials quite accurately describes the wall-liquid interface, the bulk liquid density, and the liquid-vapor interface while simultaneously providing a much improved description of the vapor phase. This model also provides an excellent description of the pair structure and pressure-density equation of state for the bulk liquid. Thus, LD potentials hold considerable promise for transferable bottom-up models that accurately describe the structure and thermodynamic properties of both bulk and interfacial systems.

Role of image charges in ionic liquid confined between metallic interfaces

Atomistic molecular dynamics simulations unveil a minor role of metal polarisation at ionic liquid/gold interface and provide a novel description of the interface where long range effects are seen in dynamical properties up to 10 nm from surface.

Dynamical insights into the mechanism of a droplet detachment from a fiber

Quantifying the detachment behavior of a droplet from a fiber is important in many applications such as fog harvesting, oil-water separation, or water management in fuel cells. When the droplets are forcibly removed from hydrophilic fibers, the ease of detachment strongly depends on droplet volume and the rate of the process controlled by the applied force. Experiments, conducted on a ferrofluid under magnetic force, as well as continuum level calculations from fluid mechanics have so far been unable to resolve the time-dependent dynamics of droplet detachment and, most importantly, to assess the role of the applied force as the key determinant of the volume of the droplet residue remaining on the fiber after detachment. In the present work, we study the mechanism of water droplet detachment and retention of residual water on smooth hydrophilic fibers using nonequilibrium molecular dynamics simulations. We investigate how the applied force affects the breakup of a droplet and how the minimal detaching force per unit mass decreases with droplet size. We extract scaling relations that allow extrapolation of our findings to larger length scales that are not directly accessible by molecular models. We find that the volume of the residue on a fiber varies nonmonotonically with the detaching force, reaching the maximal size at an intermediate force and associated detachment time. The strength of this force decreases with the size of the drop, while the maximal residue increases with the droplet volume, V, sub-linearly, in proportion to the V2/3.

Atomistic and Coarse-Grained Modeling of the Adsorption of Graphene Nanoflakes at the Oil-Water Interface

The high interfacial tension between two immiscible liquids can provide the necessary driving force for the self-assembly of nanoparticles at the interface. Particularly, the interface between water and oily liquids (hydrocarbon chains) has been exploited to prepare networks of highly interconnected graphene sheets of only a few layers thickness, which are well suited for industrial applications. Studying such complex systems through particle-based simulations could greatly enhance the understanding of the various driving forces in action and could possibly give more control over the self-assembly process. However, the interaction potentials used in particle-based simulations are typically derived by reproducing bulk properties and are therefore not suitable for describing systems dominated by interfaces. To address this issue, we introduce a methodology to derive solid-liquid interaction potentials that yield an accurate representation of the balance between interfacial interactions at atomistic and coarse-grained resolutions. Our approach is validated through its ability to lead to the adsorption of graphene nanoflakes at the interface between water and n-hexane. The development of accurate coarse-grained potentials that our approach enables will allow us to perform large-scale simulations to study the assembly of graphene nanoparticles at the interface between immiscible liquids. Our methodology is illustrated through a simulation of many graphene nanoflakes adsorbing at the interface.

Is Water at the Graphite Interface Vapor-like or Ice-like?

Graphitic surfaces are the main component of soot, a major constituent of atmospheric aerosols. Experiments indicate that soots of different origins display a wide range of abilities to heterogeneously nucleate ice. The ability of pure graphite to nucleate ice in experiments, however, seems to be almost negligible. Nevertheless, molecular simulations with the monatomic water model mW with water-carbon interactions parameterized to reproduce the experimental contact angle of water on graphite predict that pure graphite nucleates ice. According to classical nucleation theory, the ability of a surface to nucleate ice is controlled by the binding free energy between ice immersed in liquid water and the surface. To establish whether the discrepancy in freezing efficiencies of graphite in mW simulations and experiments arises from the coarse resolution of the model or can be fixed by reparameterization, it is important to elucidate the contributions of the water-graphite, water-ice, and ice-water interfaces to the free energy, enthalpy, and entropy of binding for both water and the model. Here we use thermodynamic analysis and free energy calculations to determine these interfacial properties. We demonstrate that liquid water at the graphite interface is not ice-like or vapor-like: it has similar free energy, entropy, and enthalpy as water in the bulk. The thermodynamics of the water-graphite interface is well reproduced by the mW model. We find that the entropy of binding between graphite and ice is positive and dominated, in both experiments and simulations, by the favorable entropy of reducing the ice-water interface. Our analysis indicates that the discrepancy in freezing efficiencies of graphite in experiments and the simulations with mW arises from the inability of the model to simultaneously reproduce the contact angle of liquid water on graphite and the free energy of the ice-graphite interface. This transferability issue is intrinsic to the resolution of the model, and arises from its lack of rotational degrees of freedom.

Communication: Is a coarse-grained model for water sufficient to compute Kapitza conductance on non-polar surfaces?

Coarse-grained models have increasingly been used in large-scale particle-based simulations. However, due to their lack of degrees of freedom, it is a priori unlikely that they straightforwardly represent thermal properties with the same accuracy as their atomistic counterparts. We take a first step in addressing the impact of liquid coarse-graining on interfacial heat conduction by showing that an atomistic and a coarse-grained model of water may yield similar values of the Kapitza conductance on few-layer graphene with interactions ranging from hydrophobic to mildly hydrophilic. By design the water models employed yield similar liquid layer structures on the graphene surfaces. Moreover, they share common vibration properties close to the surfaces and thus couple with the vibrations of graphene in a similar way. These common properties explain why they yield similar Kapitza conductance values despite their bulk thermal conductivity differing by more than a factor of two.