Colloidal Interactions Research Articles

Electrostatic-elastic coupling in colloidal crystals

Abstract Electrostatic-elastic coupling in colloidal crystals, composed of a mobile Coulomb gas permeating a fixed background crystalline lattice of charged colloids, is studied on the continuum level in order to analyze the lattice-mediated interactions between mobile charges. The linearized, Debye-H{" u}ckel-like mean-field equations incorporating a minimal coupling between electrostatic and displacement fields imply an additional effective attractive interaction between mobile charges. For small screening lengths, the interactions between like mobile charges exhibit colloid lattice-mediated effective interaction, ranging from weak to strong attraction, while for large screening lengths the lattice mediated interaction is purely attractive. Continuum theory incorporating the standard lattice elasticity and electrostatics of mobile charges, augmented by the minimal electrostatic-elastic coupling terms, can serve as a baseline for more detailed microscopic models.

Brownian colloids in optothermal field: An experimental perspective

Colloidal matter undergoing Brownian motion serves as a model system to study various physical phenomena. Understanding the effect of external perturbation on the assembly and dynamics of “Brownian colloids” has emerged as a relevant research issue in soft matter and biological physics. Optical perturbation in the form of photonic forces and torques has added impetus to this exploration. In recent years, optothermal effects arising due to optical excitation of mesoscale matter have expanded the toolbox of light–colloidal matter interactions. In this perspective, we present an experimental viewpoint on some of the developments related to the assembly and dynamics of Brownian colloids driven by the optothermal field. Furthermore, we discuss some interesting prospects on driven colloidal matter that can have implications on soft matter physics and soft photonics.

Self-stratification and phase separation in drying binary colloidal films

HypothesisFilms that develop compositional heterogeneity during drying offer a promising approach for achieving tailored functionalities. These functionalities can be realized by strategically directing different components during the drying process. One approach to achieve this is through spontaneous size segregation of colloidal particles. Two variants thereof have previously been observed in binary suspensions: layer formation (self-stratification) due to kinetically driven concentration gradients, and micro-domain formation (phase separation) due to thermodynamic depletion interactions between the small and large species. Surprisingly, in the context of binary colloidal films, these phenomena have never been investigated concurrently during evaporation. ExperimentsWe show how we can achieve both self-stratification and domain formation in a single step. Using real-time 3D confocal fluorescence microscopy, we quantitatively unravel the effects of various parameters on the emergence of compositional heterogeneity. FindingsWe reveal that beyond a certain size ratio, micro-phase separation becomes a prominent mechanism dictating the final morphology. The initial volume fraction minimally affects the final domain size but significantly impacts self-stratification. Reducing the evaporation rate increases the domain size while minimizing stratification. Finally, reducing the colloidal electrostatic interaction by a small increase in salt concentration enhances phase separation yet reverses stratification. These findings unveil a strategy for harnessing two distinct size segregation mechanisms in a single film, forming a foundation for customizable self-partitioning coatings.

Optimising the viscoelastic properties of hyaluronic acid hydrogels through colloidal particle interactions: A response surface methodology approach

Enhancing the viscoelastic characteristics of hydrogel systems through strategic colloidal particle interactions is paramount for their functionality in rectal gel applications. This investigation delves into the synergistic interactions between cationic nanoparticles (CNPs), anionic nanoparticles (ANPs), and composite nanoparticles (NPs) within a hyaluronic acid (HA) hydrogel matrix, employing response surface methodology (RSM) for optimisation. Critical parameters, namely the volume fraction of NPs and oscillatory amplitude, were meticulously calibrated to achieve optimal complex viscosity, as determined by advanced rheometric analysis. The findings reveal substantial effects of CNPs, ANPs, and mixed NPs on the viscoelasticity of the HA hydrogel, with complex viscosity measurements of 490.82 ± 10.57, 214.70 ± 8.96, and 328.46 ± 6.67 mPa. s, respectively. The hydrogel system with mixed NPs exhibited a strong concordance with empirical data (R² = 0.9843), validating the predictive precision of the model. Morphological assessments uncovered a highly interconnected network within the HA gel-particle composite, characterised by both densely and sparsely packed porous architectures. This study presents a robust framework for modulating viscoelastic properties in colloidal particle-gel systems, providing pivotal insights for the development of advanced rectal gel formulations.

Predicting Colloidal Interaction Parameters from Small-Angle X-ray Scattering Curves Using Artificial Neural Networks and Markov Chain Monte Carlo Sampling.

Small-angle X-ray scattering (SAXS) is a characterization technique that allows for the study of colloidal interactions by fitting the structure factor of the SAXS profile with a selected model and closure relation. However, the applicability of this approach is constrained by the limited number of existing models that can be fitted analytically, as well as the narrow operating range for which the models are valid. In this work, we demonstrate a proof of concept for using an artificial neural network (ANN) trained on SAXS curves obtained from Monte Carlo (MC) simulations to predict values of the effective macroion valency (Z eff) and the Debye length (κ-1) for a given SAXS profile. This ANN, which was trained on 200,000 simulated SAXS curves, was able to predict values of Z eff and κ-1 for a test set containing 25,000 simulated SAXS curves, where most predicted values had errors smaller than 20%. Subsequently, an ANN was used as a surrogate model in a Markov chain Monte Carlo sampling algorithm to obtain maximum a posteriori estimates of Z eff and κ-1, as well as the associated confidence intervals and correlations between Z eff and κ-1 for an experimentally obtained SAXS profile.

Electrophoretic mobility of nanoparticle aggregates: Independence from aggregate size

The zeta potential is a widely used parameter to categorize particle-particle interaction and aggregation. This parameter is often determined by the measurement of electrophoretic mobility. For single particles, various approximations allow a direct correlation between the mobility and the zeta potential. However, for aggregates, which are often found in the environment and in industrial applications, such approximations are less utilized. The relation between the size of aggregates and the resulting electrophoretic mobility has not yet been extensively explored and is often not considered. Here, we control the aggregate size additive-free of two fumed silica types with different primary particle diameters for comprehensive electrophoretic and dynamic light scattering measurements. We evaluate the influence of primary particle diameter and aggregate size on electrophoretic mobility. Our results reveal that the primary particle diameter is the defining factor for the electrophoretic mobility of the aggregates. This finding provides new insights into the electrokinetic behavior of aggregates and emphasizes the importance of primary particle properties in predicting colloidal interactions.

Artificial chemotaxis under electrodiffusiophoresis

HypothesisThrough a large parameter space, electric fields can tune colloidal interactions and forces leading to diverse static and dynamical structures. So far, however, field-driven interactions have been limited to dipole-dipole and hydrodynamic contributions. Nonetheless, in this work, we propose that under the right conditions, electric fields can also induce interactions based on local chemical fields and diffusiophoretic flows. ExperimentsHerein, we present a strategy to generate and measure 3D chemical gradients under electric fields. In this approach, faradaic reactions at electrodes induce global pH gradients that drive long-range transport through electrodiffusiophoresis. Simultaneously, the electric field induces local pH gradients by driving the particle's double layer far from equilibrium. FindingsAs a result, while global pH gradients lead to 2D focusing away from electrodes, local pH gradients induce aggregation in the third dimension. Evidence points to a mechanism of interaction based on diffusiophoresis. Interparticle interactions display a strong dependence on surface chemistry, zeta potential and diameter of particles. Furthermore, pH gradients can be readily tuned by adjusting the voltage and frequency of the electric field. For large Péclet numbers, we observed a collective chemotactic-like collapse of particles. Remarkably, such collapse occurs without reactions at a particle's surface. By mixing particles with different sizes, we also demonstrate, through experiments and Brownian dynamics simulations, the emergence of non-reciprocal interactions, where small particles are more drawn towards large ones.

Understanding the thixotropic structural build-up of C3S pastes in the presence of polycarboxylate superplasticizers

Due to the physical and chemical effect of polycarboxylate (PCE) ether superplasticizers on the simultaneous hydration of aluminate phase and silicate phase, the structural build-up of cement paste with PCE remains a much-complicated process. In order to reveal the underlying mechanism, this study reports the thixotropic structural build-up of C3S paste with PCE in the early stage (stage I before initial setting, within 1500 s). It should be subdivided into stage I′ (rapid non-linear increase) and stage I″ (slow linear development), since PCE significantly prolongs the duration of stage I′ from ∼10 s to ∼1000 s. Although PCE does not alter the origins of thixotropy (CSH/C3S cohesive forces and colloidal interactions), it can change the magnitude of driving forces, greatly depending on its adsorption in the pseudo-contact region. Consequently, the dominant driving force in stage I′ is C3S cohesive force, while it is colloidal interactions in stage I″. The quantitative models of colloidal percolation characteristic time (tperc) and thixotropic structural build-up rate (Gthix) are developed, both of which are determined by the surface coverage and initial solid volume fraction. Increasing PCE dosage augments tperc and diminishes Gthix, until reaching the maximum adsorption threshold (not full surface coverage), beyond which further PCE increase has a minimal effect on tperc and Gthix.

Spatially Confined Assembly and Immobilization of Hierarchical Nanoparticle Architectures inside Microdroplets in Magnetic Fields.

Magnetic field-directed colloidal interactions offer facile tools for assembly of structures that range from linear chains to multidimensional hierarchical architectures. While the field-driven assembly of colloidal particles has commonly been investigated in unbounded media, a knowledge gap remains concerning such assembly in confined microenvironments. Here, we investigate how confinement of ferromagnetic nanoparticles in microspheres directs their magnetic assembly into hierarchical architectures. Microdroplets from polydimethylsiloxane (PDMS) liquid precursor containing dispersed iron oxide magnetic nanoparticles (MNPs) were placed in a static magnetic field leading to the formation of organized assemblies inside the host droplets. By changing the MNP concentrations, we revealed a sequence of microstructures inside the droplets, ranging from linear chains at a low MNP loading, transitioning to a combination of chains and networked bundles, to solely 3D bundles at high MNP loading. These experimental results were analyzed with the aid of COMSOL simulations where we calculated the potential energy to identify the preferred assembly conformations. The chains at high MNP loading minimized their energy by aggregating laterally to form bundles with their MNP dipoles being out-of-registry. We cured these PDMS droplets to immobilize the assemblies by forming soft microbeads. These microbeads constitute an "interaction toolbox" with different magnetic macroscale responses, which are governed by the structuring of the MNPs and their magnetic polarizability. We show that thanks to their ability to rotate by field-induced torque under a rotating field, these microbeads can be employed in applications such as optical modulators and microrollers.

Inferring effective electrostatic interaction of charge-stabilized colloids from scattering using deep learning

An innovative strategy is presented that incorporates deep auto-encoder networks into a least-squares fitting framework to address the potential inversion problem in small-angle scattering. To evaluate the performance of the proposed approach, a detailed case study focusing on charged colloidal suspensions was carried out. The results clearly indicate that a deep learning solution offers a reliable and quantitative method for studying molecular interactions. The approach surpasses existing deterministic approaches with respect to both numerical accuracy and computational efficiency. Overall, this work demonstrates the potential of deep learning techniques in tackling complex problems in soft-matter structures and beyond.

Structural build-up of cement pastes - Underlying mechanisms considering the particle packing, colloidal interactions and hydration kinetics

This study aims to investigate the decisive mechanisms of structural build-up of cement pastes. The structural build-up can be divided into three stages, with distinct developments in particle packing, colloidal interactions, and CSH bridges at each stage. Our model framework demonstrates that the first stage of structural build-up is influenced by heightened colloidal interactions and enhanced particle packing. The second stage is propelled by the strengthening of CSH bridges, while the third stage involves reinforced CSH bridges and increased particle packing. It should be noted that the impact of particle packing may be limited at low hydration levels. Upon examination, the physical-based structural build-up rates (Athix,f, ACA$H and ACSH) are identified as the results of enhanced colloidal interactions, increased particle packing and augmented CSH bridges, respectively. These parameters are validated as consequences of the initial particle packing parameter and rate factors, which denote the increase rate of van der Waals forces, the hydration rate at the beginning of hydration, and in the subsequent second and third stages.

Colloidal interactions between nanochitin and surfactants: Connecting micro- and macroscopic properties by isothermal titration calorimetry and rheology

This study elucidates the intricate interactions between chitin nanocrystals (ChNC) and surfactants of same hydrophobic tail (C12) but different head groups types (anionic, cationic, nonionic): sodium dodecyl sulfate (SDS), dodecyltrimethylammonium bromide (DTAB), and polyoxyethylene(23)lauryl ether (Brij-35). Isothermal Titration Calorimetry (ITC) and rheology are used to study the complex ChNC-surfactant interactions in aqueous media, affected by adsorption, self-assembly and micellization. The ITC results demonstrate that the surfactant head group significantly influences the dynamics and nature of the involved phenomena. Cationic DTAB's reveal minimal interaction with ChNC, non-ionic Brij-25's interact moderately at low concentrations driven by hydrophobic effects while SDS's interacts strongly and show complex interaction patterns that fall across four distinct regimes with SDS addition. We attribute such behavior to initiate through electrostatic attraction and terminate in surfactant micelle formation on ChNC surfaces. ITC also elucidates the impact of ChNC concentration on key parameters including critical aggregation concentration (CAC) and saturation concentration (C2). Dynamic rheological analysis indicates the molecular interactions translate to non-linear variations in the elastic modulus (G') upon SDS addition mirroring that observed in ITC experiments. Such a direct correlation between molecular interactions and macroscopic rheological properties provides insights to aid in the creation of nanocomposites with tailored properties.

Different inhibitory mechanisms of flexible and rigid clay minerals on the transport of microplastics in marine porous media

Colloidal interactions between clay minerals and microplastics (MPs) in high salinity seawater are crucial for determining MP fate in marine environments. Montmorillonite (MMT) forms thin and pliable films that tightly cover MPs, while the thick and rigid lamellae of kaolinite (KLT) have limited contact with MPs, resulting in unstable bonding. However, a small quantity of small-sized KLT can create relatively stable heteroaggregates by embedding into the interstitial spaces of MPs. Both MMT and KLT colloids can decrease the mobility of MPs in seawater-saturated sea sand, but their breakthrough curves (BTCs) show distinct phenomena of "blocking" and "ripening", respectively. The "blocking" phenomenon occurs when flexible MMT adheres to the sand surface, depleting attachment sites quickly and inhibiting the retention of subsequent heteroaggregates of MMT-wrapped MPs. The transport of single MMT also experiences colloid competition for attachment sites, but pre-equilibration experiments reveal no competition between MMT and bare MPs for attachment sites. Instead, the attached MMT provides additional attachment sites for MPs. These results suggest that the wrapping of MPs by MMT plays a dominant role in the "blocking" of cotransport. In contrast, rigid KLT forms a three-dimensional stack on the sand surface, offering more attachment sites for subsequent MPs and heteroaggregates.

Self-Assembled Ring-Based Complex Colloidal Particles by Lock-And-Key Interaction and Their Self-Assembly into Unusual Colloidal Crystals.

Creating hierarchical crystalline materials using simple colloids or nanoparticles is very challenging, as it is usually impossible to achieve hierarchical structures without nonhierarchical colloidal interactions. Here, we present a hierarchical self-assembly (SA) route that employs colloidal rings and anisotropic colloidal particles to form complex colloids and uses them as building blocks to form unusual colloidal columnar liquid crystals or crystals. This route is realized by designing hierarchical SA driving forces that is controlled by the colloidal shape and shape-dependent depletion attraction. Depletion-induced lock-and-key interaction is the first driving force, which ensures a high efficiency (>90%) to load colloidal particles of other shapes such as spheres, spherocylinders, and oblate ellipsoids into rings, providing high-quality building blocks. Their SA into ordered superstructures has to require a second driving force such as higher volume fraction and/or stronger depletion attraction. As a result, unusual hierarchical colloidal (liquid) crystals, which have previously been difficult to fabricate by simple binary assembly, can be achieved. This work presents a significant advancement in the field of hierarchical SA, demonstrating a promising strategy for constructing many unprecedented crystalline materials by the SA route.

Simulating the rheology of dense suspensions using pairwise formulation of contact, lubrication and Brownian forces

Dense suspensions of solid particles in viscous liquid are ubiquitous in both industry and nature, and there is a clear need for efficient numerical routines to simulate their rheology and microstructure. Particles of micron size present a particular challenge: at low shear rates, colloidal interactions control their dynamics while at high rates, granular-like contacts dominate. While there are established particle-based simulation schemes for large-scale non-Brownian suspensions using only pairwise lubrication and contact forces, common schemes for colloidal suspensions generally are more computationally costly and thus restricted to relatively small system sizes. Here, we present a minimal particle-based numerical model for dense colloidal suspensions that incorporates Brownian forces in pairwise form alongside contact and lubrication forces. We show that this scheme reproduces key features of dense suspension rheology near the colloidal-to-granular transition, including both shear thinning due to entropic forces at low rates and shear thickening at high rates due to contact formation. This scheme is implemented in LAMMPS, a widely used open source code for parallelised particle-based simulations, with a runtime that scales linearly with the number of particles, making it amenable for large-scale simulations.

Colloidal interaction of fly ash and soil clay

The combustion of coal worldwide creates a large quantity of fly ash (FA), and the application of FA to agricultural soils is being encouraged as a resource utilization strategy. While most of our attention has focused on positive aspects such as nutrient supplementation and pollution mitigation, the negative impacts of FA have likely been overlooked. In this study, we examined the colloidal properties of FA and soil clay, aiming to demonstrate the ability of FA to increase the dispersibility and transportability of soil clay. Dynamic light scattering technique was coupled with the test tube method to track the kinetics and pH-dependent changes in the zeta potential, hydrodynamic size and colloidal stability of FA, soil clay and their mixtures. We found that FA occurred in solution as “negatively charged balls”, and its negative surface charges increased with increasing pH. FA itself showed a low dispersibility; however, FA became more dispersive when it was introduced to clay suspensions. The mechanism is that the introduction of FA supplied more negative charges to the clay suspension, inducing electrostatic repulsion with soil clay, from which both FA and soil clay were favoured to disperse. Therefore, it can be inferred that off-site transport of FA is possible. More importantly, excessive application of FA can inadvertently intensify clay dispersibility, eventually resulting in soil clays together with FA being more vulnerable to leaching and/or surface run-off erosion. This suggests that the application of FA needs more careful consideration, and the development of more suitable techniques for the sustainable application of FA is still needed.

Pair Interactions of Self-Propelled SiO2-Pt Janus Colloids: Chemically Mediated Encounters.

Driven by the necessity to achieve a thorough comprehension of the bottom-up fabrication process of functional materials, this experimental study investigates the pairwise interactions or collisions between chemically active SiO2-Pt Janus colloids. These collisions are categorized based on the Janus colloids' orientations before and after they make physical contact. In addition to the hydrodynamic interactions, the Janus colloids are also known to affect each other's chemical field, resulting in chemophoretic interactions, which depend on the degree of surface anisotropy in reactivity of Janus colloid and the solute-surface interaction at play. Our study reveals that these interactions lead to a noticeable decrease in particle speed and changes in orientation that correlate with the contact duration and yield different collision types. Distinct configurations of contact during collisions were found, whose mechanisms and likelihood are found to be dependent primarily on the chemical interactions. Such estimates of collision and their characterization in dilute suspensions shall have a key impact in determining the arrangement and time scales of dynamical structures and assemblies of denser suspensions and potentially the functional materials of the future.

Control of the Colloidal and Adsorption Behaviors of Chitin Nanocrystals and an Oppositely Charged Surfactant at Solid, Liquid, and Gas Interfaces.

Chitin has a unique hierarchical structure, spanning the macro- and nanoscales, and presents chemical characteristics that make it a suitable component of multiphase systems. Herein, we elucidate the colloidal interactions between partially deacetylated chitin nanocrystals (cationic ChNC) and an anionic surfactant, sodium dodecyl sulfate (SDS). We investigate charge neutralization and association (electrophoretic mobility, surface tensiometry, and quartz crystal microgravimetry) and their role in the stabilization of Pickering emulsions. We find SDS adsorption and association with ChNC under distinctive regimes: At low SDS concentration, submonolayer assemblies form on ChNC, driven by the hydrophobic effect and electrostatic interactions. With the increased SDS concentration, bilayers or patchy bilayers form, followed by adsorbed hemimicelles and micelles. We further suggested the role of hydrophobic effects in the observed colloidal transitions and complex conformations. At the highest SDS concentration tested, charge neutralization and SDS/ChNC flocculation take place. Remarkably, at given concentrations, adsorbed SDS endows the chitin nanoparticles with an effective hydrophobicity that opens the opportunity to achieve tailorable Pickering stabilization. Hence, a facile route is proposed by in situ modification by SDS physisorption, which extends the potential of renewable nanoparticles in the formulation of complex fluids, for instance, those relevant to household and healthcare products.

Biophysical and biochemical characterization of a recombinant Lyme disease vaccine antigen, CspZ-YA

Lyme disease, caused by Lyme Borrelia spirochetes, is the most common vector-borne illness in the United States. Despite its global significance, with an estimated 14.5 % seroprevalence, there is currently no licensed vaccine. Previously, we demonstrated that CspZ-YA protein conferred protection against Lyme Borrelia infection, making it a promising vaccine candidate. However, such a protein was tagged with hexahistidine, and thus not preferred for vaccine development; furthermore, the formulation to stabilize the protein was understudied. In this work, we developed a two-step purification process for tag-free E. coli-expressed recombinant CspZ-YA. We further utilized various bioassays to analyze the protein and determine the suitable buffer system for long-term storage and formulation as a vaccine immunogen. The results indicated that a buffer with a pH between 6.5 and 8.5 stabilized CspZ-YA by reducing its surface hydrophobicity and colloidal interactions. Additionally, low pH values induced a change in local spatial conformation and resulted in a decrease in α-helix content. Lastly, an optimal salinity of 22–400 mM at pH 7.5 was found to be important for its stability. Collectively, this study provides a fundamental biochemical and biophysical understanding and insights into the ideal stabilizing conditions to produce CspZ-YA recombinant protein for use in vaccine formulation and development.

Direct measurements & simplified models of colloidal interactions & diffusion with adsorbed macromolecules.

We report total internal reflection microscopy measurements of 3D trajectories of ensembles of micron sized colloidal particles near interfaces with and without adsorbed macromolecules. Evanescent wave scattering reveals nanometer scale motion normal to planar surfaces and sub-diffraction limit lateral motion is resolved via image analysis. Equilibrium and non-equilibrium analyses of particle trajectories reveal self-consistent position dependent energies (energy landscapes) and position dependent diffusivities (diffusivity landscapes) both perpendicular and parallel to interfaces. For bare colloids and surfaces, electrostatic and hydrodynamic interactions are accurately quantified with established analytical theories. For colloids and surfaces with adsorbed macromolecules, conservative forces are accurately quantified with models for interactions between brush layers, whereas directly measured position dependent diffusivities require novel models of spatially varying permeability within adsorbed layers. Agreement between spatially resolved interactions and diffusivities and rigorous simplified models provide a basis to consistently interpret, predict, and design colloidal transport in the presence of adsorbed macromolecules for diverse applications.