Exploring parameter space effects on structure-property relationships of surfactants at liquid-liquid interfaces

Local Structure of Nonuniform Fluid Mixtures Containing Associating and Chainlike Molecules from a Multilayer Quasichemical Model

In this work, we develop a theory for predicting details of the local structure in nonuniform multicomponent fluids that may contain chainlike and associating components. This theory is an extension─to the fluid interfaces and mesoscopic structures of different geometry─of the multilayer quasichemical model originally proposed by Smirnova to describe liquid solution in the vicinity of a planar solid wall. The basis of the theory is the "cut-and-bond" approach, much in spirit of SAFT, where an infinite attraction between the separated monomeric units of a chainlike molecule mimics the chemical bonds of the chain. We describe the equilibrium structure of the mixture, including the spatial distribution of the monomeric units and the local orientation of the chemical bonds in chainlike molecules, and discuss the contribution of chemical bonds to the local chemical potential in a nonuniform fluid. To test the new theory, we apply it to mixtures containing combinations of model components: a strongly associating solvent, an inert substance of varying chain length, and a chainlike amphiphile. To compare predictions from the multilayer model with the results of continuous description of nonuniform fluids, we also address the square-gradient theory and derive an analytical expression for the influence parameter that takes into account pair correlations in the quasichemical approximation. The multilayer quasichemical model developed in this work predicts formation of aggregates in liquid solution and describes the local structure of the interfaces between the coexisting liquid phases in the mixture. Our theoretical predictions agree on a qualitative level with the accumulated knowledge about the structure of different types of systems studied in this work.

Quantitative investigation of surfactant monolayer bending tendency at an oil-polar solvent interface using DPD modeling and artificial neural networks

The bending tendency of a surfactant monolayer at an interface is critical in determining the type of emulsion formed and the proximity of the emulsion system to its equilibrium state. Despite its importance, the influence of interaction and surfactant structure on the bending tendency has not been quantitatively investigated. In this study, we develop and validate an artificial neural network (ANN) model based on the torque densities from dissipative particle dynamics (DPD) simulations to address this gap. With the validated ANN model, the relationship between surfactant monolayer bending tendency and all the interaction parameters, oil size, and surfactant structure (size and tail branching) was derived, from which the significance of each factor was ranked. With this ANN model, both the relationship and factor analysis can be instantly investigated without further DPD modeling. Furthermore, we expand the study to surfactant-oil-polar solvent (SOP) systems by varying the interaction parameters between polar solvents (PP). Our finding indicates that the interaction between polar solvents plays an important role in determining the bending tendency of surfactant monolayers; weaker intermolecular attraction between polar solvents makes surfactants tend to bend toward the oil phase (tend to form oil in polar solvent emulsion). Factor analysis reveals that increasing the repulsion between head-head (HH) or head-oil (HO) makes the model surfactants more polar-solvophilic, while increasing the repulsion between polar solvent-head (PH), tail-tail (TT) or oil-oil (OO) makes the model surfactants more lipophilic. The ANN model effectively reproduces the dependence of surfactant monolayer bending tendency on oil size, consistent with experimental observations, the larger the oil size, the higher the bending tendency toward the oil phase. The most intriguing insight derived from the ANN model here is that the effect of branching in the lipophilic tail will be enhanced by factors that make surfactants behave more lipophilic in a surfactant-oil-polar solvent (SOP) system, for rather polar-solvophilic surfactants, the effect of tail branching is negligible.

Competitive Sorption of CO2 with Gas Mixtures in Nanoporous Shale for Enhanced Gas Recovery from Density Functional Theory

CO₂ competitive sorption with shale gas under various conditions from simple to complex pore characteristics is studied using a molecular density functional theory (DFT) that reduces to perturbed chain-statistical associating fluid theory in the bulk fluid region. The DFT model is first verified by grand canonical Monte Carlo simulation in graphite slit pores for pure and binary component systems at different temperatures, pressures, pore sizes, and bulk gas compositions for methane/ethane with CO₂. Then, the model is utilized in multicomponent systems that include CH₄, C₂H₆, and C3+ components of different compositions. It is shown that the selectivity of CO₂ decreases with increases in temperature, pressure, nanopore size, and average molecular weight of shale gas. Extending the model to more realistic situations, we consider the impact of water present in the pore and consider the effect of permeation of fluid molecules into the kerogen that forms the pore walls. The water-graphite interaction is calibrated with contact angle from molecular simulation data from the literature. The kerogen pore model prediction of gas absolute sorption is compared with experimental and molecular simulation values in the literature. It is shown that the presence of water reduces the CO₂ adsorption but improves the CO₂ selectivity. The dissolution of gases into the kerogen matrix also leads to the increase in CO₂ selectivity. The effect of kerogen type and maturity on the gas sorption amount and CO₂ selectivity is also studied. The associated mechanisms are discussed to provide fundamental understanding for gas recovery by CO₂.

Thermodynamics, Microstructures, and Solubilization of Block Copolymer Micelles by Density Functional Theory

Block copolymer micelle is one of the most versatile self-assembled structures with applications in drug delivery, cosmetic products, and micellar-enhanced ultrafiltration. The key to design an effective block copolymer to form micelles is to understand how molecular architecture affects critical micelle concentrations, micellar dimensions, and partitioning of solute into the micelle. In this work, we studied micelles from nonionic block copolymers using interfacial statistical associating fluid theory a density functional theory, which explicitly includes block copolymer-water hydrogen bonding and water-water hydrogen bonding. We are able to predict and explain how micellar thermodynamic properties depend on polymer chain architecture. Dimension and aggregation of micelles are investigated for block copolymers with different hyrophobes and hydrophiles. The effects of temperature and pressure on micelle stability are also captured by the theory. The enhanced solubility of hydrophobic substance in water by micelle loading is demonstrated, and predicted solute distribution answers the question about the locus of benzene in micelles from a theoretical perspective.

An accurate density functional theory for the vapor–liquid interface of chain molecules based on the statistical associating fluid theory for potentials of variable range for Mie chainlike fluids

A new Helmholtz free energy density functional is presented to predict the vapor–liquid interface of chainlike molecules.

Modeling micelle formation and interfacial properties with iSAFT classical density functional theory

Surfactants reduce the interfacial tension between phases, making them an important additive in a number of industrial and commercial applications from enhanced oil recovery to personal care products (e.g., shampoo and detergents). To help obtain a better understanding of the dependence of surfactantproperties on molecular structure, a classical density functional theory, also known as interfacial statistical associating fluid theory, has been applied to study the effects of surfactant architecture on micelle formation and interfacial properties for model nonionic surfactant/water/oil systems. In this approach, hydrogen bonding is explicitly included. To minimize the free energy, the system minimizes interactions between hydrophobic components and hydrophilic components with water molecules hydrating the surfactant head group. The theory predicts micellar structure, effects of surfactant architecture on critical micelle concentration, aggregation number, and interfacial tension isotherm of surfactant/water systems in qualitative agreement with experimental data. Furthermore, this model is applied to study swollen micelles and reverse swollen micelles that are necessary to understand the formation of a middle-phase microemulsion.

Adsorption and Phase Behavior of Pure/Mixed Alkanes in Nanoslit Graphite Pores: An iSAFT Application

The prediction of fluid phase behavior in nanoscale pores is critical for shale gas/oil development. In this work, we use a molecular density functional theory (DFT) to study the effect of molecular size and shape on partitioning to graphite nanopores as a model of shale. Here, interfacial statistical associating fluid theory (iSAFT) is applied to model alkane (C₁ - C₈) adsorption/desorption/phase behavior in graphite slit pores for both pure fluids and mixtures. The pure component parameters were fit to the bulk saturated liquid density and vapor pressure data in selected temperature ranges. The potential of interaction between the fluid and graphite is modeled with a Steele 10-4-3 potential that is fit to the potential of mean force from single-molecule simulations. Good agreement is found between theory and molecular simulation for the density distributions of pure components in slit pores. The critical properties of methane, ethane, and their mixtures as well as the shift in bubble point and dew point densities were studied, showing good agreement with simulation. The competitive adsorption of mixtures of normal and branched alkanes in graphite pores was also studied. Heavier components more strongly adsorb up to the point that the entropic penalty due to confinement reduces adsorption.

Competition between Intra- and Intermolecular Association of Chain Molecules with Water-like Solvent

Fluid properties and phase behavior of systems such as glycol ethers, carboxylic acids, and proteins are affected by the competition between intra- and intermolecular hydrogen bonding. Here we study this competition by extending Wertheim's first-order thermodynamic perturbation theory to include intramolecular hydrogen bonding in chain molecules in the presence of an explicit water-like solvent. The theory derived here is found to be in good agreement with molecular simulation. It is shown that intramolecular association is most important for shorter chains at low temperature, low density, and high chain concentration. The theory is also extended into a density functional theory formalism to study the effect of intramolecular association on the structuring of the different segments of the molecules close to a hydrophobic surface. Intramolecular association is found to be enhanced close to the surface, with the total density of the system having the most effect on structuring close to the surface.