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Solid particles tend to adhere to fluid interfaces under the action of capillary force. This adsorption process is robust and has been exploited in lots of applications from stabilisation of emulsions to micro fluidic fabrications. The resulting particle laden fluid interfaces can manifest solid-like behaviours. The modifi cation of the surface tension and the emergence of surface shear elasticity of a particle-covered drops are attributed to the particle-induced surface stress. This stress represents at the continuum level the microscopic effect of particle-particle interactions. Understanding the link between the surface stress and the particle arrangement are crucial for creating novel soft materials in the future. A challenge remains when carrying out numerical simulations of particle-laden fluid interfaces: the large separation of scales makes the direct numerical simulations extraordinary expensive. Physical features present in the system come from both the liquid meniscus on the surface of each particle and the fluid interfaces containing thousands of particles. Motivated by the need for a fast simulation method to study problems involving particle-laden fluid interface, this thesis presents a new numerical formulation named Fast Interface Particle Interaction (FIPI) that can be used to simulate a large number of solid particles absorbed on fluid interfaces at a moderate computational cost. The outstanding performance of this new method is attributed to the fact that particle-level phenomena are modelled with analytical or semi-empirical expressions while hydrodynamics and fluid interface morphology at larger scales are fully resolved. Two important studies of particle-covered drops have been carried out with FIPI. In the first one a particle-covered pendant drop is simulated. The result reveals that the FIPI can successfully capture the modulation of surface tension made by absorbed particles. Moreover, the information of anisotropic surface stress is now directly available on the fluid interfaces. This capability has not been achieved previously in both experiments and simulations. The anisotropic stress emerged on the surface of a pendant drop is caused by anisotropic arrangement of the particles on the interface which in turn is induced by stretching of the interface due to gravity. Once the surface tension of the fluid interface is reduced below zero, the Laplace pressure inside the drop becomes negative and the drop can buckle like a thin solid elastic shell under compression. In the second study, the behaviours of a particle covered spherical drop under compression have been explored. The simulation results indicate the possibilities of particle desorption as well as fluid interface buckling. The onset of desorption is highly correlated to small-scale monolayer undulations which can greatly amplify the normal forces pushing particles out of the interface. The behaviours of a particle-covered drop under compression depend on the combination of several parameters related to the properties of the particle and the surface pressure created by the monolayer.

Adsorption-mediated self-assembly of nanoparticles at fluid interfaces, driven by reduction in interfacial energy, leads to stabilization of emulsions and foams and can be used for the bottom-up fabrication of functional nanostructured materials. Improved understanding of the parameters that control the self-assembly, the structure of nanoparticles at the interface, the barrier properties of the assembly and the rate of particle attachment and exchange is needed if such nanoparticle assemblies are to be employed for the design and fabrication of novel materials and devices. Here, I report on the use of dynamic surface tension (DST) measurements to probe the kinetics of irreversible adsorption and self-assembly of hydrophobic ethyl-cellulose (EC) nanoparticles at the air-water interface. Using thermodynamic arguments, I make a direct connection between the DST and the time-dependent surface coverage. I show that adsorption models appropriate for surfactants (e.g., Ward and Tordai model) break down for irreversible adsorption of nanoparticles, when the adsorption energy far exceeds the mean energy of thermal fluctuations (kBT) and surface blocking effects give rise to a steric barrier to adsorption. I show instead that irreversible adsorption kinetics are unequivocally characterized in terms of the adsorption rate constant and the maximum (jamming) coverage, both of which are determined on the basis of DST data using the generalized random sequential adsorption theory (RSA) for the first time. Novel accurate estimates of the adsorption energy of 42 nm and 89 nm EC nanoparticles are also provided. Coverage of the interface to the jamming limit of 91%, corresponding to a triangular lattice in 2D, is experimentally demonstrated. Colloidal solutions of EC nanoparticles are stabilized at neutral pH by electrostatic repulsive forces. Strong adsorption of these particles at an interface of like charge suggests the parallel action of attractive hydrophobic forces.

Adsorption-mediated self-assembly of nanoparticles at fluid interfaces, driven by reduction in interfacial energy, leads to stabilization of emulsions and foams and can be used for the bottom-up fabrication of functional nanostructured materials. Improved understanding of the parameters that control the self-assembly, the structure of nanoparticles at the interface, the barrier properties of the assembly and the rate of particle attachment and exchange is needed if such nanoparticle assemblies are to be employed for the design and fabrication of novel materials and devices. Here, I report on the use of dynamic surface tension (DST) measurements to probe the kinetics of irreversible adsorption and self-assembly of hydrophobic ethyl-cellulose (EC) nanoparticles at the air-water interface. Using thermodynamic arguments, I make a direct connection between the DST and the time-dependent surface coverage. I show that adsorption models appropriate for surfactants (e.g., Ward and Tordai model) break down for irreversible adsorption of nanoparticles, when the adsorption energy far exceeds the mean energy of thermal fluctuations (kBT) and surface blocking effects give rise to a steric barrier to adsorption. I show instead that irreversible adsorption kinetics are unequivocally characterized in terms of the adsorption rate constant and the maximum (jamming) coverage, both of which are determined on the basis of DST data using the generalized random sequential adsorption theory (RSA) for the first time. Novel accurate estimates of the adsorption energy of 42 nm and 89 nm EC nanoparticles are also provided. Coverage of the interface to the jamming limit of 91%, corresponding to a triangular lattice in 2D, is experimentally demonstrated. Colloidal solutions of EC nanoparticles are stabilized at neutral pH by electrostatic repulsive forces. Strong adsorption of these particles at an interface of like charge suggests the parallel action of attractive hydrophobic forces.

Surfactants at fluid-fluid interfaces play a critical role in numerous engineering applications, including enhanced oil recovery and fire suppression by foams. This dissertation explores surfactant-laden fluid-fluid interfaces in two applications using molecular dynamics (MD) simulations and develops deep learning models to predict the interfacial properties of sur factants. The first study investigates slippage modulation at brine–oil interfaces by surfactants, which is relevant to enhanced oil recovery operations. We identified a slip length of 1.2 nm at clean decane-brine interfaces. Introducing surfactants to the interface leads to an initial linear decrease in slippage, with nonylphenol being more effective than phenol. As surfactant concentration increases, the reduction in slip length slows, ultimately plateauing at 1.4 nm and 0.5 nm for nonylphenol and phenol, respectively. The mechanisms underlying these slip modulation behaviors and the effects of surfactant tail length on interfacial slippage are examined by analyzing the molecular structure and transport properties of the interfacial fluids and surfactants. The second study focuses on oil transport across surfactant-laden fluid-fluid interfaces, which is relevant to firefighting foam applications. Despite its importance, the molecular details of this transport are not fully understood. Through MD simulations, the potential of mean force (PMF) and local diffusivity profiles of heptane molecules across surfactant monolayers was computed to evaluate their transport resistance across the interface. It was discovered that a heptane molecule experiences significant resistance when crossing surfactant-covered water−vapor interfaces. This resistance, influenced by high PMF and low diffusion in the surfactant head group region, increases linearly with surfactant density and dramatically spikes as the monolayer reaches saturation, becoming equivalent to the resistance of a 5 nm thick layer of bulk water. These observations provide insights into the design of surfactants aimed at reducing oil transport through water−vapor interfaces. The final part of the dissertation explores the development of a quantitative structure-property relationship (QSPR) model for surfactants using a graph neural network (GNN) based approach. The model was trained on 92 surfactant data points and demonstrated high accuracy (R² = 0.86 on average) in predicting critical micelle concentration, limiting surface tension, and maximum surface excess for various surfactants. The performance of the model in capturing the relationship between molecular design parameters and surfactant properties was critically evaluated. The dataset, model development, and assessments contribute to advancing surfactant QSPR models and their rational design for diverse industrial applications / Doctor of Philosophy / Surfactants are substances that can reduce surface tension, and they play a vital role in many applications, such as recovering oil from petroleum reservoirs and making firefighting foams. This dissertation explores how surfactants behave at the interfaces between different fluids and develops models to predict surfactant properties using machine learning methods. First, how surfactants affect the movement of oil and water at their interface is studied due to their importance in oil recovery. It was discovered that adding surfactants to the interface between oil and brine reduces the "slippage" between them, with some surfactants being more effective than others. This slippage reduction eventually stabilizes as more surfactants are added. Next, the transport of fuel molecules across water-vapor interfaces coated with surfactants is studied due to its relevance to the design of surfactants for firefighting foams. It is revealed that a heptane molecule faces increasing resistance when passing through surfactant-covered interfaces, especially when the surfactant concentration is high. Lastly, a model for predicting surfactant properties from their molecular structure is developed using the artificial intelligence (AI) approach. Using a modest collection of surfactant data, a machine learning model was trained to predict three key properties of surfactants, and the model performance is encouraging. This approach can potentially facilitate the development of new surfactants for a wide range of applications.

The lattice Boltzmann (LB) method is a versatile way to model complex fluids with hydrodynamic interactions through solving the Navier-Stokes equations. It is well-known that the role of hydrodynamic interactions is ignorable in studying the Boltzmann equilibrium of colloidal (Brownian) particles. However, full hydrodynamic interactions play an important role in their dynamics. In the LB framework for moving colloids, the “bounce-back on links” method is used to calculate the hydrodynamic forces. In this thesis, three kinds of colloidal complex fluids with full hydrodynamic interactions are simulated by lattice Boltzmann methods: colloids in a binary fluid, magnetic colloids in a single fluid and magnetic colloids in a binary fluid. First, we have done extensive simulations of nanoparticles in a binary fluid, following up previous work[1] which predicted formation of a “bijel” (bicontinuous interfacially jammed emulsion gel) in symmetric fluid quenches. Our work in this thesis focuses on the analysis of the dynamics after nanoparticles become arrested on the fluid-fluid interfaces under conditions varying from a symmetric quench to a strongly asymmetric quench. Although these new simulations extend the time window studied by a factor of two, slow domain growth is still observed. Our new analyses address the mechanics of the slow residual dynamics which involves cooperative motion of the nanoparticles at the fluid-fluid interfaces. The second topic is the LB simulation of colloidal ferrofluids to see the effect of full hydrodynamic interactions among magnetic colloids. The main focus is on how the hydrodynamic interaction affects both the equilibrium dynamics of these dipolar systems and also their transient dynamics to form clusters. Numerically, magnetic colloids are implemented with the long-range dipolar interactions described by Ewald summation. To check the effect of full hydrodynamic interactions, Brownian dynamics without any hydrodynamic interaction has been done for comparison: Monte Carlo results are also reported. We confirm that our LB generates the Boltzmann distribution for static equilibrium properties, by comparison with these methods. However, the equilibrium dynamics is altered: hydrodynamic interactions make the structural relaxations slower in both the short-time and the long-time regime. This slow relaxation rate is also found for transient motions. The third topic addresses magnetic colloids in a binary fluid. In contrast with the preceding two systems which correspond directly to laboratory experiments, this last system is so far only predicted by the LB results in this thesis. To explore this hypothetical new material by the LB method, the basic structures are investigated in terms of both domain growth morphology and the arrangement of magnetic colloids. Under conditions varying from a symmetric quench to an asymmetric quench, a chainlike arrangement is observed for dipoles jammed on the surfaces, but the basic morphology of domains is still maintained regardless of the dipolar strength. In addition, applying external field affects the morphology of domains and the stability of domain structures.

The phenomenon of particle retention in granular materials has a wide range of implications. For agricultural operations, these particles can be contaminants transported through the ground that can eventually reach to aquifers, consequently contaminating the water. In oil reservoirs, these particles can be clays that get detached from the rock and migrate with the flow after a change of pressure, plugging the reservoir with the consequent reduction in permeability. These particles can also be traceable nanoparticles, introduced in the reservoir with the purpose of identifying bypassed oil. For all these reasons it is important to understand the mechanisms that contribute to the transport and retention of these particles. In this dissertation the retention of micro and nano size particles was investigated. In saturated model sediments (sphere packs), we analyzed the retention of particles by the mechanism of straining (size exclusion). The analysis focused on experiments reported in the literature in which particles smaller than the smallest pore throats were retained in the sediment. The analysis yields a mechanistic explanation of these observations, by indentifying the retention sites as gaps between pairs of sediment grains. A predictive model was developed that yields a relationship between the straining rate constant and particle size in agreement with the experimental observations. In unsaturated granular materials, the relative contributions of grain surfaces, interfacial areas and contact lines between phases to the retention of colloidal size particles were investigated. An important part of this analysis was the identification and calculation of the length of the contact lines between phases. This estimation of contact line lengths in porous media is the first of its kind. The algorithm developed to compute contact line length yielded values consistent with observations from beads pack and real rocks, which were obtained independently from analysis of high resolution images. Additionally, the predictions of interfacial areas in granular materials were consistent with an established thermodynamic theory of multiphase flow in porous media. Since there is a close relationship between interfacial areas and contact lines this supports the accuracy of the contact line length estimations. Predictions of contact line length and interfacial area in model sediments, combined with experimental values of retention of colloidal size particles in columns of glass beads suggested that it is plausible for interfacial area and contact line to contribute in the same proportion to the retention of particles. The mechanism of retention of surface treated nanoparticles in sedimentary rocks was also investigated, where it was found that retention is reversible and dominated by attractive van der Waals forces between the particles and the rock’s grain surfaces. The intricate combination of factors that affect retention makes the clear identification of the mechanism responsible for trapping a complex task. The work presented in this dissertation provides significant insight into the retention mechanisms in relevant scenarios. / text

Cette thèse de doctorat présente une étude expérimentale des propriétés rhéologiques d’électrolytes confinés et de la mécanique des doubles couches électrostatiques.Afin d’étudier simultanément les propriétés d’équilibre et de transport d’électrolytes confinés proches de parois électriquement chargées, nous avons développé un appareil à forces de surfaces dynamique. Cette technique combine à la fois des mesures à l’équilibre, à l’instar des appareils à forces de surfaces classiques, et des mesures dynamiques permettant de caractériser les phénomènes de transport.Nous avons tout d’abord étudié le cas d’électrolytes très dilués. Nous avons montré l’existence d’une sur-dissipation induite par les ions issus des électrolytes par rapport à un comportement newtonien classique. De plus, nous avons mis en évidence un comportement élastique des doubles couches électrostatiques dépendant de la fréquence. Une approche théorique vient compléter et expliquer en partie les résultats expérimentaux.Enfin nous nous sommes intéressés à la dynamique d’électrolytes concentrés : les liquides ioniques. Nous avons étudié l’influence, sur la viscosité et les propriétés du liquide à l’interface solide-liquide, d’un champ électrique intense appliqué perpendiculairement à l’écoulement, comme rencontré dans les super-condensateurs. / This thesis presents an experimental study of rheological properties of confined electrolytes and mechanics of electric double layer.In order to study simultaneously equilibrium and transport of confined electrolytes nearby charged surfaces, we developed a dynamic surface force apparatus. This technique enables both steady state measurements, as provided by common surface forces apparatus, and dynamic measurements that allow characterizing the transport phenomenona.First, we showed the existence of an over-dissipative behavior of weak electrolytes compared to a classical newtonian fluid. Furthermore we highlighted a frequency dependence of the EDL elastic behavior. Alongside, a theoretical approach completes and explains partially the experimental observations.Finally we studied the dynamics of ionic liquid, a type of concentrated electrolytes. We looked at the influence of a huge electric field, applied perpendicularly to the surfaces, on the viscosity and the properties of the liquid nearby the surfaces, as found in super-capacitors.

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