Multiple nanoemulsions consist of solutions with droplets on the nanoscale (by convention, < 200 nm in diameter) that are comprised of multiple entrained phases (typically distinct hydrophilic and hydrophobic regions). Although typically unstable and difficult to control in terms of droplet yield and internal structure, multiple nanoemulsions remain of great interest to a number of emerging applications in which nano-sized carrier systems that potentially encapsulate and protect higher quantities of otherwise insoluble materials are desired. Recent advancements in the production of these solutions to create complex, structured nanomaterials have demonstrated remarkable potential to utilize multiple nanoemulsions to template compartmental nanoparticles and nanocapsules. Moreover, these emerging techniques demonstrate the possibility of leveraging co-surfactant design and their resulting interfacial behavior to control and stabilize complex droplet morphologies.

Here, we propose and theoretically validate a general method for promoting and stabilizing multiple nanoemulsion structures by manipulating their interfacial mechanics via co-surfactant selection. Using small angle neutron scattering, we experimentally characterize nanodroplets made using several asymmetric pairs of ethoxylated co-surfactants. We demonstrate that increased co-surfactant asymmetry favors the formation and stabilization of multiple nanoemulsions. Neutron scattering measurements also enable us to probe the equilibrium dynamics of mixed surfactant layers across nanoscale droplets as well as quantify the preferred partitioning of co-surfactants across interfaces in core-shell nanodroplets. The results of these studies suggest mixtures of asymmetric co-surfactant exhibit frustrated interfacial dynamics and nonideal mixing.

Using equilibrium interfacial free energy models, we establish a theoretical basis for the preferred stabilization of multi-phase core-shell nanodroplet structures formed with co-surfactants of opposing spontaneous curvatures and demonstrate these models may be used to predict and quantify conditions under which multiple nanoemulsions may be produced. We experimentally verify the predictions made by these models using small-angle neutron scattering to characterize the droplet morphologies of nanoemulsions made using asymmetric pairs of ethoxylated co-surfactants. We show that the co-surfactant based interfacial strategy allows for some degree of control over the internal droplet morphology and provides a rational means of engineering desirable multi-phase nanodroplets.

Nanoemulsions – nanoscale droplet suspensions – in polymeric solution have been widely used in many fields from consumer products to advanced technology. Due to their nanoscopic dimensions, they exhibit unique physical behavior in terms of their rheology and microstructure, both at rest and under flow. However, mechanisms that give rise the interesting phenomena observed in nanodroplet-polymer mixtures are poorly understood. Thus, the goals of this thesis are to develop a model nanoemulsion-polymer system to impart control over polymer-droplet and droplet-droplet interactions, use it to investigate the mechanisms colloidal behavior of nanodroplets in polymeric solutions, and to determine how these behaviors influence suspension microstructure, dynamics and rheology.

For these purposes, we choose to study thermoresponsive oil-in-water nanoemulsions as a model system. The systems include polydimethylsiloxane (PDMS) oil nanodroplets dispersed in aqueous mixtures of functionalized hydrophilic polymer (polyethylene glycol diacrylate, PEGDA) and ionic surfactant (sodium dodecyl sulfate, SDS). Combining calorimetry, rheology and scattering measurements, we show how molecular self-assembly in the system can be used to control the viscoelasticity of the system, which remarkably follows time-temperature superposition, much like simpler polymer fluids, and suggests that polymer-surfactant complexation forms a transient polymer network between droplets. Systematic changes in the energy scale for complexation allows us to develop a simple model for the modulus and viscoelastic relaxation time. Furthermore, the relaxation time of the network in this model system can be varied by ten orders of magnitudes, providing advantages for fundamental studies.

We exploited the properties of this novel nanoemulsion system to study shear-induced clustering of colloid-polymer mixtures and its impact on fluid rheology. The system allows us to explore several limiting regimes of polymer and suspension dynamics. Combining rheological characterization with three-dimensionally-resolved flow-small angle neutron scattering measurements reveals that an excess of particle fluxes along compressional and vorticity axes of shear are the primary mechanism of clustering, and suggestes that short-range hydrodynamic forces dominate the clustering of Brownian suspensions in viscoelastic fluids.

Lastly, we used the thermoresponsive nanoemulsions to investigate the mechanisms of so-called “two-step” or “delayed” yielding in heterogeneous colloidal gels. At high temperatures, the model system forms colloidal gels with heterogeneous microstructure resembling arrested phase separation at elevated temperature caused by polymer-bridging interactions. Analyzing the sequence of mechanical processes during the intracycle yielding processes elucidates the detailed mechanism of frequency and strain amplitude-dependence of nonlinearlity. The nonlinear analysis also allows for characterization of the strain amplitude and rate-dependent yield stress and strain of the material. Furthermore, combining large amplitude oscillatory shear measuremetns with simultaneous small and ultra-small angle neutron scattering reveals that, contrary to previous hypotheses, large-scale microstructural processes play an important, if not dominant, role in the yielding of heterogeneous colloidal gels.

The results of this thesis demonstrate that the rheology and the microstructural processes of nanoemulsions can be controlled through thermoresponsive polymer-surfactant-droplet association, which provides for sophisticated tuning of polymer-colloid and colloid-colloid interactions and dynamics, thus providing new routes and design rules for engineering the colloidal behavior of nanoemulsions.

Polyelectrolyte-based soft materials have been engineered for applications across food science, consumer products, healthcare, and oil recovery. This thesis explores the formation and control of microstructure in two important subclasses of these materials: (1) coacervates (Chapters 2-4), which are sticky Rouse liquids formed by associative phase separation in polyelectrolyte solutions; and (2) chemically-crosslinked hydrogels (Chapter 5), which are permanent, water-swelled networks that form during polymerization.

Coacervates are chiefly understood at equilibrium, but their functionality often depends their non-equilibrium behavior. Herein, we investigate the formation and destabilization of non-equilibrium coacervate structures. We examine the influence of mixing flows on coacervate coarsening in a model chemistry of poly(acrylic acid sodium salt) (PAA) and poly(allylamine hydrochloride) (PAH). Leveraging a combination of microfluidics, microscopy, and image analysis techniques, we find that flow conditions can induce formation of microscale aggregates or “precipitates,” and discover and characterize their interfacial relaxation. Our observations reveal that non-equilibrium structural control in coacervates can be achieved orthogonally to chemical structure design.

Inspired by this concept, we demonstrate spontaneous formation of core-shell droplets in the PAA-PAH system—i.e., with a single coacervate—through careful control of the mixing approach. These all-water, core-shell droplets remain metastable without surfactant. Using image classification machine learning, we discover which compositions, PAA:PAH ratios, and flow conditions favor core-shell formation over generic droplets. Our proposed mechanisms for core-shell formation and stabilization are distinctive within the broader context of multiple emulsions.

Finally, we develop a phase field polymer dynamics model for coacervates. We use it to offer insights into coacervate spinodal decomposition, which has proved challenging to explore experimentally due to the fast dynamics. Taken in concert, our works on coacervates establish the fundamental principles necessary to predict and control their microstructure formation beyond equilibrium.

The final chapter addresses one overarching challenge in hydrogel design: the tradeoffs between optimizing for different performance properties. We explain simultaneous superlubricity and mechanical robustness in a polyacrylamide hydrogel by using a reaction-diffusion model to predict the surface microlayer’s structure. The model is a promising tool for designing gel surface properties, and could readily be modified to other chemistries.

Colloids are used to form processable soft solids that are ubiquitous in everyday materials like foods, industrial building materials, coatings and biomedical products. Despite their prevalence, there are limited experimental methods to probe the underlying colloidal scale interactions in these materials. These underlying interactions give rise to unique structure and properties. By modulating the interaction potential between colloids both equilibrium phase transitions can be triggered and non-equilibrium `arrested states' such as gels and glasses can be formed. However, there is a lack of experimental methods available for faithfully mathematically representing these interactions which prevents a better understanding of the phase behavior and processing of these materials.

To address this problem, we use a model experimental colloidal system to develop a new approach for determining a unique interaction potential that can be used to replicate the systems equilibrium and non-equilibrium phase behavior in particle simulations. The new approach uses a non-equilibrium comparison test between experiments and simulation to down-select candidate potentials (extracted from dilute experimental structural measurements) that differ in shape but share the same equilibrium structure. We demonstrate that the conditions for non-equilibrium arrest by colloidal gelation are sensitive to both the shape of the interaction potential and the thermal quench rate. We exploit this sensitivity to select the potential that best matches the non-equilibrium behavior between simulation and experiments.

With a better understanding of the underlying colloidal scale interactions in our experimental system, we then focus on developing new methods to precisely establish locations of non-equilibrium states to generate a comprehensive phase diagram and to elucidate the underlying combination of mechanisms that lead to the emergence of gelation. Our method employs systematically varied quenches of the colloidal fluid over a range of volume fractions to identify minimal conditions for gel solidification. The method is applied to experimental and simulated systems to test its generality toward attraction potentials of varied shape. Using structural and rheological characterization, we show that all gels incorporate elements of percolation, phase separation and glassy arrest, where the quench path sets their interplay and determines the shape of the gelation boundary. We find that the slope of the gelation boundary corresponds to the dominant gelation mechanism, and its location approximately scales with the equilibrium fluid critical point. These results are insensitive to potential shape, suggesting that this interplay of mechanisms is applicable to a wide range of colloidal systems.

Building on our understanding of colloidal phase behavior, we next investigate how programmed quenches to the gelled state can be used to effectively tailor gel structure and mechanics. Specifically, we look at how changing the quench rate from the fluid phase into the gel region can be used to vary the gels elastic modulus by over two orders of magnitude. These results suggest an important parameter for control of the structure and mechanics of gels is the ratio of the timescale of the thermal quench relative to the timescale for phase separation. We also investigate how the structure and mechanics change in time after performing instantaneous quenches to different quench depths in the gel region.

We then used our model colloidal system to develop a new technique for templating porous polymeric materials. These porous materials have a diverse range of applications in materials for water filtration, insulation, biomedical tissue scaffolds and catalyst supports.

Finally we present some future directions on developing time-temperature-transformation (TTT) diagrams to better inform thermokinetic processing of colloidal materials. We also briefly discuss the development of new techniques to locate the attractive glass line inside the phase instability region of the colloidal phase diagram.

The ability to engineer macroscopic properties of colloidal gels through controlled processing of their microscopic substituents presents an opportunity to improve soft material technology in emergent fields such as additive manufacturing and biomaterial production. However, the fundamental underpinnings of colloidal gel formation and behavior are not comprehensively developed to a degree that would facilitate new material design. To build toward such an understanding of colloidal gels, in this dissertation we use a model thermoresponsive colloidal system to investigate (1) the formation of colloidal gels with respect their interparticle potential, phase behavior, and gel arrest kinetics, and (2) the resultant properties of colloidal gels as observed through their structure, viscoelasticity, and yielding.

The system of interest to this work comprises nanoemulsion dispersions with interactions mediated by thermoresponsive polymers. To model the effective interdroplet attractions arising from thermoresponsive behavior, we employ a hard sphere two-Yukawa interaction potential and determine model parameters from experimental scattering measurements. The interaction potential is subsequently used to make mean field predictions of the effective pseudo-one component colloidal phase behavior by means of variational perturbation methods, which are found to agree with measurements from sedimented phase separating gels as well as comparable coarse-grained molecular dynamics simulations. These results are noteworthy because they provide evidence that near-equilibrium behavior can still be recovered underneath the non-equilibrium glassy arrest line.

Additionally, we report qualitatively distinct gelation kinetics between colloidal gels formed at volume fractions below and above the predicted spinodal boundary. To explain gelation kinetics inside the phase coexistence region, we use rheo-microscopy which enables simultaneous characterization of gel linear viscoelasticity and microstructure. Through this characterization, we map out an isothermal transformation diagram to identify the sequential transitions that occur en route to prolonged arrest for varying thermal quenches. From rheological analysis of linear elasticity, we find that conventional nondimensionalization proves insufficient to collapse the quench dependence of gel elasticity, demonstrating a need for further investigation into the appropriate length and energy scales for scaling colloidal gel rheology. From imaging analysis of gel structuration, we find that late-stage coarsening rates exhibit a sigmoidal quench dependence akin to the effective interdroplet attraction strength, which can be predicted from a simple mean-field description of sub-critical viscoelastic phase separation.

Finally, we describe novel experimental techniques and metrics to evaluate colloidal gel structure during the process of yielding during large amplitude oscillatory shear deformation. Combining intracycle and intercycle analyses of microstructure and rheology reveals a three-stage process of network rupture, softening, and alignment that the yielding gel undergoes. Establishing this methodology provides a robust experimental platform for forthcoming studies into the direct influence of gelation and shearing conditions on the complex yielding process.

The brain's computational functions, from information synthesis and memory recall to consciousness, remain largely enigmatic. Despite great scientific effort, the mechanisms behind information storage, computation, and readout within the brain are still not well understood. Because of the warm, crowded nature of biological systems, it has traditionally been thought that quantum states would rapidly decohere and be unsuitable for biological information storage. Recently, the "Quantum Brain theory" has proposed the potential for a quantum information network in the brain that could maintain and process quantum information on timescales relevant to brain function. Within the framework of this theory, quantum information is stored in the collective phosphorus spin states of nanometric calcium phosphate clusters known as Posner molecules. The pair binding of these Posner molecules is postulated to be impacted by the collective phosphorus spin states, allowing for a unique quantum state to biochemical signal transduction mechanism. Given that this theory puts forward a uniquely possible method for quantum information processing in the brain, experimental validation or refutation of the theory would be an important step towards an understanding of brain function. This thesis presents experimental results aimed at testing the possibility of this Quantum Brain theory. We show that Posner molecules are stable in simulated body fluids, and uncover a differential lithium isotope effect on the growth of calcium phosphate. This isotope effect provides a link between nuclear spin states and calcium phosphate binding dynamics, and can be connected to in vivo lithium isotope effects in mitochondria. We also uncover spectroscopically 'dark state' phosphate assemblies after measuring unexpected 31P NMR signals, revealing that phosphate solution behavior and 31P nuclear spin dynamics are much more complex than previously predicted. These results verify key predictions of the Quantum Brain theory, indicating the possibility of quantum information processing in the brain, while also progressing our understanding of the complex solution phase space of calcium phosphate.

Flow-based polymer processing is ubiquitous in the formation of soft materials for applications ranging from healthcare to packaging. Polymer processing strategies have historically been determined empirically, where the maximum flow rate is often established by the onset of visual distortions from uniform flow. Such an approach prohibits predictive flow calculations for arbitrary flow environments and polymeric formulations. Theoretical advances over the past several decades have enabled molecularly informed rheological modeling of entangled polymer liquids; however, most models assume that the fluid composition remains uniform during flow. Several exceptions to this assumption are known for polymer solutions such as shear-enhanced concentration fluctuations and polymer migration across curved streamlines, but these effects are typically not accounted for in models due to the belief that these compositional heterogeneities either occur on a small scale, with an insignificant effect on the bulk flow behavior, or on diffusive timescales, which are much longer than typical processing flows. This belief has been challenged by a recently developed two-fluid theory for entangled polymers, which, under certain conditions, predicts that uniform flow is unstable due to a shear-induced demixing instability that results in shear banding (i.e., two or more regions of distinct shear rates across the fluid under a shear flow); however, there is a lack of experimental measurements to directly compare with this theory.

To fill this gap, this dissertation experimentally explores the coupling of shear-induced compositional changes to bulk flow behavior in entangled polymer liquids. To do this, a combination of novel rheo-optical techniques are developed and used to quantify both fluid velocity and concentration fields. Qualitatively different results are observed depending on the number of entanglements and osmotic susceptibility of the polymer solutions. For entangled polystyrene in dioctyl phthalate, spatial variations of shear-enhanced concentration fluctuations in startup shear are coupled to changes in the bulk flow. In particular, the presence of mesoscopic concentration heterogeneities coincides with a local effective viscosity increase of the fluid. Conversely, entangled polybutadiene in dioctyl phthalate exhibits macroscopic heterogeneities in concentration that coincide with shear banded velocity profiles, consistent with a two-fluid model that couples the flow to polymer concentration. The effect of polydispersity on the flow behavior of entangled polymer liquids was investigated by using chemically homologous, bidisperse polymer blends. Interestingly, differences in the flow behavior were observed for blends of equivalent numbers of entanglements, but different blend compositions. Lastly, the two-fluid model for entangled polymer solutions is used to investigate nonuniform flows that arise from shear-induced demixing in complex flow protocols (i.e., large amplitude oscillatory shear (LAOS)).

The results of this dissertation underscore the possibility for non-local concentration changes in flows of entangled polymeric liquids, and reveal a wide range of flow phenomena that result when it is operative. More generally, the concept of flow-concentration coupling is likely applicable to many other complex fluids and should be accounted for in future models to accurately describe their rheology.