Nudged elastic band calculation of the binding potential for liquids at interfaces

Buller, Oleg; Tewes, Walter; Archer, Andrew J.; Heuer, Andreas; Thiele, Uwe; Gurevich, Svetlana V.

doi:10.1063/1.4990702

Cited by 9 publications

(13 citation statements)

References 26 publications

(31 reference statements)

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“…However, alternatively to such combinations of different asymptotic expressions it has recently been shown that one may directly extract wetting energies (and interfacial tensions) from various microscopic models, namely, Molecular Dynamics (MD) simulations [120], lattice Density Functional Theory (DFT) [18,52] and continuous DFT [53] for Lennard-Jones fluids and other simple liquids. Refs.…”

Section: Obtaining Wetting Potentials From Microscopic Modelsmentioning

confidence: 99%

Recent advances in and future challenges for mesoscopic hydrodynamic modelling of complex wetting

Thiele

2018

Colloids and Surfaces A: Physicochemical and Engineering Aspect

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We highlight some recent developments that widen the scope and reach of mesoscopic thin-film (or longwave) hydrodynamic models employed to describe the dynamics of thin films, drops and contact lines of simple and complex liquids on solid substrates. The basis of the discussed developments is the reformulation of various mesoscopic thin-film hydrodynamic models as gradient dynamics on underlying energy functionals. After briefly presenting the general approach, the following sections discuss how to improve these models by amending the energy functional and the mobility function, how to obtain gradient dynamics models for some complex liquids, and how to incorporate processes beyond relaxational dynamics.

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Section: Obtaining Wetting Potentials From Microscopic Modelsmentioning

confidence: 99%

Recent advances in and future challenges for mesoscopic hydrodynamic modelling of complex wetting

Thiele

2018

Colloids and Surfaces A: Physicochemical and Engineering Aspect

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“…Here, we use the approach of Refs. [23,24] (see also [25,26]) that uses classical density functional theory (DFT) [27][28][29] to calculate the binding potential g(h), from which one obtains Π(h) = −∂g(h)/∂h, and also the interfacial tensions. Thin-film equations together with binding potentials from DFT have been used previously to elucidated the influence of the fluid microscopic structure on droplet spreading [30].…”

Section: Introductionmentioning

confidence: 99%

Kinetic Monte Carlo and hydrodynamic modeling of droplet dynamics on surfaces, including evaporation and condensation

2019

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We present a lattice-gas (generalised Ising) model for liquid droplets on solid surfaces. The time evolution in the model involves two processes: (i) Single-particle moves which are determined by a kinetic Monte Carlo algorithm. These incorporate into the model particle diffusion over the surface and within the droplets and also evaporation and condensation, i.e. the exchange of particles between droplets and the surrounding vapour. (ii) Larger-scale collective moves, modelling advective hydrodynamic fluid motion, determined by considering the dynamics predicted by a thin-film equation. The model enables us to relate how macroscopic quantities such as the contact angle and the surface tension depend on the microscopic interaction parameters between the particles and with the solid surface. We present results for droplets joining, spreading, sliding under gravity, dewetting, the effects of evaporation, the interplay of diffusive and advective dynamics, and how all this behaviour depends on the temperature and other parameters. * Electronic address: A.J. Archer@lboro.ac.uk arXiv:1906.08121v1 [cond-mat.soft] 19 Jun 2019 is to use Monte Carlo methods to simulate the dynamic properties of Hamiltonian systems [18]. However, it is not clear to us that one should enforce detailed balance when constructing coarse grained models of such non-equilibrium systems, since droplets on surfaces are highly dissipative systems, due to the evaporation, the strong coupling to the substrate, etc. Of course, at equilibrium, there should be detailed balance in the model.To model collective hydrodynamic motion in our model, we generate large-scale collective particle moves by considering the dynamics that is predicted by a thin-film equation. This is a time evolution equation for the liquid film thickness profile h, i.e. the height of the liquid-vapour interface above the surface [2,[19][20][21][22]. This equation is derived from the Navier-Stokes equations for a film of liquid on a surface by making a long-wave approximation, which greatly simplifies the analysis. When generating these 'thin-film moves', we first determine the liquid film height profile from the configuration of occupied lattice sites, we then evolve the thin-film equation for a short amount of time, and then map back to the lattice. In our model, an important quantity is the parameter λ, defined below in Eq. (13), which is proportional to the ratio of the number of KMC attempted particle moves to the number of thin-film moves. When λ = 0, our model reduces to just evolving the thin-film equation, whilst in the limit λ → ∞, our model is a pure KMC model. Therefore, this parameter λ ∝ D/η, where D is a single-particle diffusion coefficient and η is the viscosity.Key quantities that characterises how a liquid wets a surface are the spreading parameter S = γ sv − (γ sl + γ lv ), where γ sv , γ sl , and γ lv are the solid-vapour, solid-liquid and liquid-vapour interfacial tensions, respectively [2], and also the contact angle θ, which is given by Young's equation [2]:The...

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“…Note that continuation techniques may also be applied to deterministic lattice models or stochastic models [31,34]. This implies that it should in the future also be possible to apply the proposed method to analyse the phase behaviour for lattice DFT and Monte Carlo models as studied, e.g., in [4,7].…”

Section: Discussionmentioning

confidence: 99%

Efficient calculation of phase coexistence and phase diagrams: application to a binary phase-field crystal model

Holl,

Archer,

Thiele

2020

Preprint

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We show that one can employ well-established numerical continuation methods to efficiently calculate the phase diagram for thermodynamic systems. In particular, this involves the determination of lines of phase coexistence related to first order phase transitions and the continuation of triple points. To illustrate the method we apply it to a binary Phase-Field-Crystal model for the crystallisation of a mixture of two types of particles. The resulting phase diagram is determined for one-and two-dimensional domains. In the former case it is compared to the diagram obtained from a one-mode approximation. The various observed liquid and crystalline phases and their stable and metastable coexistence are discussed as well as the temperature-dependence of the phase diagrams. This includes the (dis)appearance of critical points and triple points. We also relate bifurcation diagrams for finite-size systems to the thermodynamics of phase transitions in the infinite-size limit.

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Nudged elastic band calculation of the binding potential for liquids at interfaces

Cited by 9 publications

References 26 publications

Recent advances in and future challenges for mesoscopic hydrodynamic modelling of complex wetting

Recent advances in and future challenges for mesoscopic hydrodynamic modelling of complex wetting

Kinetic Monte Carlo and hydrodynamic modeling of droplet dynamics on surfaces, including evaporation and condensation

Efficient calculation of phase coexistence and phase diagrams: application to a binary phase-field crystal model

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