An introduction to inhomogeneous liquids, density functional theory, and the wetting transition

2015

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Citation: HUGHES, A.P., THIELE, U. and ARCHER, A.J., 2015. Liquid drops on a surface: using density functional theory to calculate the binding potential and drop profiles and comparing with results from mesoscopic modelling.Journal of Chemical Physics, 142 (7), 074702.Additional Information:• The contribution to the free energy for a film of liquid of thickness h on a solid surface due to the interactions between the solid-liquid and liquid-gas interfaces is given by the binding potential, g(h). The precise form of g(h) determines whether or not the liquid wets the surface. Note that differentiating g(h) gives the Derjaguin or disjoining pressure. We develop a microscopic density functional theory (DFT) based method for calculating g(h), allowing us to relate the form of g(h) to the nature of the molecular interactions in the system. We present results based on using a simple lattice gas model, to demonstrate the procedure. In order to describe the static and dynamic behaviour of non-uniform liquid films and drops on surfaces, a mesoscopic free energy based on g(h) is often used. We calculate such equilibrium film height profiles and also directly calculate using DFT the corresponding density profiles for liquid drops on surfaces. Comparing quantities such as the contact angle and also the shape of the drops, we find good agreement between the two methods. We also study in detail the effect on g(h) of truncating the range of the dispersion forces, both those between the fluid molecules and those between the fluid and wall. We find that truncating can have a significant effect on g(h) and the associated wetting behaviour of the fluid. C 2015 AIP Publishing LLC.[http://dx

Section: The Binding Potentialmentioning

confidence: 99%

Liquid drops on a surface: Using density functional theory to calculate the binding potential and drop profiles and comparing with results from mesoscopic modelling

Hughes

Thiele

2015

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“…Ref. 21) and calculate the binding potentials for two different values of the wall attraction strength parameter βǫ ω , employing both the fictitious potential method 9 and the NEB method described in the previous section. Fig.…”

Section: Comparison Of Fictitious Potential and Neb Methodsmentioning

confidence: 99%

“…In our case, we consider nearest neighbor (i.e., short-range) interactions as well as particle self-interactions that results from the mapping of the particle pair interactions in the full translation-invariant 2D or 3D system, as described in Ref. 21. In contrast, the wall potential is long-ranged and acts across the entire system, algebraically decaying as…”

Section: Model Systemmentioning

confidence: 99%

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

Buller

Tewes

et al. 2017

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The wetting behavior of a liquid on solid substrates is governed by the nature of the effective interaction between the liquid-gas and the solid-liquid interfaces, which is described by the binding or wetting potential g(h) which is an excess free energy per unit area that depends on the liquid film height h. Given a microscopic theory for the liquid, to determine g(h) one must calculate the free energy for liquid films of any given value of h; i.e. one needs to create and analyse out-of-equilibrium states, since at equilibrium there is a unique value of h, specified by the temperature and chemical potential of the surrounding gas. Here we introduce a Nudged Elastic Band (NEB) approach to calculate g(h) and illustrate the method by applying it in conjunction with a microscopic lattice density functional theory for the liquid. We show too that the NEB results are identical to those obtained with an established method based on using a fictitious additional potential to stabilize the non-equilibrium states. The advantages of the NEB approach are discussed.

“…The mean-field DFT that we use is a generalisation of the theory presented in Ref. 26 (see also references therein for other applications of the theory). The thermodynamic grand potential is approximated by…”

Section: Lattice Dftmentioning

confidence: 99%

“…26 In order to make sure ρ i does not fall outside the interval (0, 1) during the iteration process, we introduce a mixing parameter, α. The idea is that after each iteration, we mix the new density value with the previous one,…”

Section: Lattice Dftmentioning

confidence: 99%

Two-dimensional colloidal fluids exhibiting pattern formation

Chacko

Chalmers

2015

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Hard sphere fluids at a soft repulsive wall: A comparative study using Monte Carlo and density functional methods J. Chem. Phys. 134, 214706 (2011) Fluids with competing short range attraction and long range repulsive interactions between the particles can exhibit a variety of microphase separated structures. We develop a lattice-gas (generalised Ising) model and analyse the phase diagram using Monte Carlo computer simulations and also with density functional theory (DFT). The DFT predictions for the structures formed are in good agreement with the results from the simulations, which occur in the portion of the phase diagram where the theory predicts the uniform fluid to be linearly unstable. However, the mean-field DFT does not correctly describe the transitions between the different morphologies, which the simulations show to be analogous to micelle formation. We determine how the heat capacity varies as the model parameters are changed. There are peaks in the heat capacity at state points where the morphology changes occur. We also map the lattice model onto a continuum DFT that facilitates a simplification of the stability analysis of the uniform fluid. C 2015 AIP Publishing LLC. [http://dx