We provide novel random surface density functional theory (RSDFT) formulation in the case of geometric heterogeneous surfaces of solid media which is essential for the description of thermodynamic properties of confined fluids. The major difference of our theoretical approach from the existing ones is a stochastic model of solid surfaces which takes into account the correlation properties of geometry. The main building blocks are effective fluid-solid potentials developed in the work of Khlyupin and Aslyamov [J. Stat. Phys. 167, 1519 (2017)] and geometry-based modification of the Helmholtz free energy for Lennard-Jones fluids. The efficiency of RSDFT is demonstrated in the calculation of argon and nitrogen low temperature adsorption on real heterogeneous surfaces (BP280 carbon black). These results are in good agreement with experimental data published in the literature. Also several models of corrugated materials are developed in the framework of RSDFT. Numerical analysis demonstrates a strong influence of surface roughness characteristics on adsorption isotherms. Thus the developed formalism provides a connection between a rigorous description of the stochastic surface and confined fluid thermodynamics.

Realistic fluid-solid interaction potentials are essential in description of confined fluids especially in the case of geometric heterogeneous surfaces. Correlated random field is considered as a model of random surface with high geometric roughness. We provide the general theory of effective coarsegrained fluid-solid potential by proper averaging of the free energy of fluid molecules which interact with the solid media. This procedure is largely based on the theory of random processes. We apply first passage time probability problem and assume the local Markov properties of random surfaces. General expression of effective fluid-solid potential is obtained. In the case of small surface irregularities analytical approximation for effective potential is proposed. Both amorphous materials with large surface roughness and crystalline solids with several types of fcc lattices are considered. It is shown that the wider the lattice spacing in terms of molecular diameter of the fluid, the more obtained potentials differ from classical ones. A comparison with published Monte-Carlo simulations shows good qualitative agreement with the theory predictions. The work provides a promising approach to explore how the random geometric heterogeneity affects on thermodynamic properties of the fluids.

An optimal combination of power and energy characteristics is beneficial for the further progress of supercapacitors-based technologies. We develop a nanoscale dynamic electrolyte model, which describes both static capacitance and the time-dependent charging process, including the initial square-root dependency and two subsequent exponential trends. The observed charging time corresponds to one of the relaxation times of the exponential regimes and significantly depends on the pore size. Additionally, we find analytical expressions providing relations of the time scales to the electrode’s parameters, applied potential, and the final state of the confined electrolyte. Our numerical results for the charging regimes agree with published computer simulations, and estimations of the charging times coincide with the experimental values.

Adsorption properties of chain fluids are of interest from both fundamental and industrial points of view. Density Functional Theory (DFT) based models are among the most appropriate techniques allowing to describe surface phenomena. At the same time Statistical Associating Fluid Theory (SAFT) successfully describes bulk PVT properties of chain-fluids. In this publication we have developed novel version of SAFT-DFT approach entitled RS-SAFT which is capable to describe adsorption of short hydrocarbons on geometrically rough surface. Major advantage of our theory is application to adsorption on natural roughs surfaces with normal and lateral heterogeneity. For this reason we have proposed workflow where surface of real solid sample is analyzed using theoretical approach developed in our previous work [1] and experimentally by means of low temperature adsorption isotherm measurements for simple fluids. As result RS-SAFT can predict adsorption properties of chain fluids taking into account geometry of the surface sample under the consideration. In order to test our workflow we have investigated hexane adsorption on carbon black with initially unknown geometry. Theoretical predictions for hexane adsorption at 303K and 293K fit corresponding experimental data well.

A graphene nanobubble consists of a graphene sheet, an atomically flat substrate, and a substance enclosed between them. Unlike conventional confinement with rigid walls and a fixed volume, the graphene nanobubble has one stretchable wall, which is the graphene sheet, and its volume can be adjusted by changing the shape. In this study, we developed a model of a graphene nanobubble based on classical density functional theory and the elastic theory of membranes. The proposed model takes into account the inhomogeneity of the enclosed substance, the nonrigidity of the wall, and the alternating volume. As an example application, we utilize the developed model to investigate fluid argon inside graphene nanobubbles at room temperature. We observed a constant height-to-radius ratio over the whole range of radii considered, which is in agreement with the results from experiments and molecular dynamics simulations. The developed model provides a theoretical tool to study both the inner structure of the confined substance and the shape of the graphene nanobubble. The model can be easily extended to other types of nonrigid confinement.

We propose a new theoretical approach to obtain the nanoscale morphology of rough surfaces from low-temperature adsorption experiments. Our method is based on one of the most realistic models of rough surfaces formulated in terms of random correlated processes. In our study, the adsorption on the rough surfaces is theoretically described by random surface density functional theory (RS-DFT), which allows us to take into account both the roughness in the normal direction and the correlation length of the lateral surface. Varying geometrical parameters of RS-DFT, we fit the experimental data in the low-pressure range, where the influence of the surface geometry is the most crucial. From this procedure, we obtained best-fit detailed geometry of rough surfaces, which provides full information for further atomistic modeling. Also, the developed approach allows the calculation of the surface fractal dimension from the experimental isotherms. It demonstrates that the surface fractal dimension observed in many experiments is natural for the correlated random surface model. We investigated the surface geometry of popular silica materials synthesized at different conditions. The obtained roughness parameters and fractal dimensions coincide well with the published experimental data and correctly reflects how the nanoroughness of silica materials depends on the synthesis conditions. Analysis of the best-fit specific surface area reveals the mechanism of adsorption on rough surfaces and provides a new strategy for the search of optimal storage materials.

We study the charging dynamics of a long electrolyte-filled slit pore in response to a suddenly applied potential. In particular, we analytically solve the Poisson-Nernst-Planck (PNP) equations for a pore for which λD H L, with λD the Debye length and H and L the pore's width and length. For small applied potentials, we find the time-dependent potential drop between the pore's surface and its center to be in complete agreement with a prediction of the celebrated transmission line model. For moderate to high applied potentials, prior numerical work showed that charging slows down at late times; Our analytical model reproduces and explains such biexponential charge buildup.

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