Density functional approach to wetting behavior of water on solid surfaces modified by grafting of chains and their mixtures

Pizio, Orest; Sokołowski, Stefan

doi:10.1016/j.molliq.2023.123009

Cited by 2 publications

(2 citation statements)

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“…yields a similar accuracy of the description of vapor-liquid bulk coexistence [39]. The mean-field approximation is particularly useful in describing the adsorption of water on solid surfaces and on even more complex substrates formed by solids with, e.g., grafted chains [40,41].…”

Section: Bulk Fluidmentioning

confidence: 93%

Revisiting the wetting behavior of solid surfaces by water-like models within a density functional theory

Kozina,

Aguilar,

Pizio

et al. 2024

Condens. Matter Phys.

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We perform the analysis of predictions of a classical density functional theory for associating fluids with different association strength concerned with wetting of solid surfaces. The four associating sites water-like models with non-associative square-well attraction parametrized by Clark et al. [Mol. Phys., 2006, 104, 3561] are considered. The fluid-solid potential is assumed to have a 10-4-3 functional form. The growth of water film on the substrate upon changing the chemical potential is described. The wetting and prewetting critical temperatures, as well as the prewetting phase diagram are evaluated for different fluid-solid attraction strength from the analysis of the adsorption isotherms. Moreover, the temperature dependence of the contact angle is obtained from the Young equation. It yields estimates for the wetting temperature as well. Theoretical findings are compared with experimental results and in a few cases with data from computer simulations. The theory is successful and quite accurate in describing the wetting temperature and contact angle changes with temperature for different values of fluid-substrate attraction. Moreover, the method provides an easy tool to study other associating fluids on solids of importance for chemical engineering, in comparison with laboratory experiments and computer simulations.

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Section: Bulk Fluidmentioning

confidence: 93%

Revisiting the wetting behavior of solid surfaces by water-like models within a density functional theory

Kozina,

Aguilar,

Pizio

et al. 2024

Condens. Matter Phys.

Self Cite

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show abstract

“…Equation is analogous to the KS-DFT equation; viz., it predicts the density profile of a noninteracting system under an effective one-body potential. Similar cDFT equations can be written for molecular and polymeric systems. − …”

mentioning

confidence: 99%

Perfecting Liquid-State Theories with Machine Intelligence

Wu,

2023

J. Phys. Chem. Lett.

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Recent years have seen a significant increase in the use of machine intelligence for predicting the electronic structure, molecular force fields, and physicochemical properties of various condensed systems. However, substantial challenges remain in developing a comprehensive framework capable of handling a wide range of atomic compositions and thermodynamic conditions. This perspective discusses potential future developments in liquid-state theories leveraging recent advancements in functional machine learning. By harnessing the strengths of theoretical analysis and machine learning techniques including surrogate models, dimension reduction, and uncertainty quantification, we envision that liquid-state theories will gain significant improvements in accuracy, scalability, and computational efficiency, enabling their broader applications across diverse materials and chemical systems.

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Density functional approach to wetting behavior of water on solid surfaces modified by grafting of chains and their mixtures

Cited by 2 publications

References 64 publications

Revisiting the wetting behavior of solid surfaces by water-like models within a density functional theory

Revisiting the wetting behavior of solid surfaces by water-like models within a density functional theory

Perfecting Liquid-State Theories with Machine Intelligence

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