Flocculation and percolation in reversible cluster-cluster aggregation

Rigidity-Induced Controlled Aggregation of Binary Colloids

Here, we report the proof-of-concept for controlled aggregation in a binary colloidal system. The binary systems are studied by varying bond flexibility of only one species, while the other species' bonds remain fully flexible. By establishing the underlying relation between gelation and bond rigidity, we demonstrate how the interplay among bond flexibility, critical concentration, and packing volume fraction influenced the aggregation kinetics. Our result shows that rigidity in bonds increases the critical concentration for gels to be formed in the binary mixture. Furthermore, the average number of bonded neighbor analyses reveal the influence of bond rigidity both above and below critical concentrations and show that variation in bond flexibility in only one species alters the kinetics of aggregation of both species. This finding improves our understanding of colloidal aggregation in soft and biological systems.

Enhancement in the diffusivity of Brownian spheroids in the presence of spheres

In the present paper, we have extended the simulation technique Brownian cluster dynamics (BCD) to analyze the dynamics of the binary mixture of hard ellipsoids and spheres. The shape dependent diffusional properties have been incorporated into BCD using Perrin's factor and compared with analytical results of a one-component ellipsoidal system. We have investigated pathways to enhance the diffusivity of spheroids in the binary mixture by manipulating the phase behavior of the system through varying the fraction of spheres in the binary mixture. We show that at low volume fraction the spherical particles have a higher diffusion coefficient than the ellipsoids due to the higher friction coefficient. However, at a higher volume fraction, we show that the diffusion coefficient of the ellipsoids increases irrespective of the aspect ratio due to the anisotropic shape.

Magnetic Control over the Fractal Dimension of Supramolecular Rod Networks

Controlling supramolecular polymerization is of fundamental importance to create advanced materials and devices. Here we show that the thermodynamic equilibrium of Gd³⁺-bearing supramolecular rod networks is shifted reversibly at room temperature in a static magnetic field of up to 2 T. Our approach opens opportunities to control the structure formation of other supramolecular or coordination polymers that contain paramagnetic ions.

Tuning mitochondrial structure and function to criticality by fluctuation-driven mechanotransduction

Cells in vascular walls are exposed to blood pressure variability (BPV)-induced cycle-by-cycle fluctuations in mechanical forces which vary considerably with pathology. For example, BPV is elevated in hypertension but reduced under anesthesia. We hypothesized that the extent of mechanical fluctuations applied to vascular smooth muscle cells (VSMCs) regulates mitochondrial network structure near the percolation transition, which also influences ATP and reactive oxygen species (ROS) production. We stretched VSMCs in culture with cycle-by-cycle variability in area strain ranging from no variability (0%), as in standard laboratory conditions, through abnormally small (6%) and physiological (25%) to pathologically high (50%) variability mimicking hypertension, superimposed on 0.1 mean area strain. To explore how oxidative stress and ATP-dependent metabolism affect mitochondria, experiments were repeated in the presence of hydrogen peroxide and AMP-PNP, an ATP analog and competitive inhibitor of ATPases. Physiological 25% variability maintained activated mitochondrial cluster structure at percolation with a power law distribution and exponent matching the theoretical value in 2 dimensions. The 25% variability also maximized ATP and minimized cellular and mitochondrial ROS production via selective control of fission and fusion proteins (mitofusins, OPA1 and DRP1) as well as through stretch-sensitive regulation of the ATP synthase and VDAC1, the channel that releases ATP into the cytosol. Furthermore, pathologically low or high variability moved mitochondria away from percolation which reduced the effectiveness of the electron transport chain by lowering ATP and increasing ROS productions. We conclude that normal BPV is required for maintaining optimal mitochondrial structure and function in VSMCs.

Aggregation kinetics of irreversible patches coupled with reversible isotropic interaction leading to chains, bundles and globules

In the present study we are performing simulation of simple model of two patch colloidal particles undergoing irreversible diffusion limited cluster aggregation using patchy Brownian cluster dynamics. In addition to the irreversible aggregation of patches, the spheres are coupled with isotropic reversible aggregation through the Kern–Frenkel potential. Due to the presence of anisotropic and isotropic potential we have also defined three different kinds of clusters formed due to anisotropic potential and isotropic potential only as well as both the potentials together. We have investigated the effect of patch size on self-assembly under different solvent qualities for various volume fractions. We will show that at low volume fractions during aggregation process, we end up in a chain conformation for smaller patch size while in a globular conformation for bigger patch size. We also observed a chain to bundle transformation depending on the attractive interaction strength between the chains or in other words depending on the quality of the solvent. We will also show that bundling process is very similar to nucleation and growth phenomena observed in colloidal system with short range attraction. We have also studied the bond angle distribution for this system, where for small patches only two angles are more probable indicating chain formation, while for bundling at very low volume fraction a tail is developed in the distribution. While for the case of higher patch angle this distribution is broad compared to the case of low patch angles showing we have a more globular conformation. We are also proposing a model for the formation of bundles which are similar to amyloid fibers using two patch colloidal particles.

Sol-Gel Titanium Dioxide Nanoparticles: Preparation and Structural Characterization

Titanium dioxide (TiO2) nanoparticle was achieved in an alternative sol-gel route, as involved in 1 M acidic solution: HCl-tetrahydrofuran (HCl-THF), HNO3-tetrahydrofuran (HNO3-THF), and ClHNO2-tetrahydrofuran (ClHNO2-THF) solution. Resultant TiO2 nanoparticle was further investigated in a systematic analytical approach. Nanoscale TiO2 structure was observed at a moderate hydrolysis ratio (8≤RH≤16). Particle size range was much narrower in an aprotic HNO3-THF medium, as compared to a differential HCl-THF medium. Biphasic TiO2 structure was detected at a certain hydrolysis ratio (RH≥16). Even so, relative anatase content was rather insignificant in an aprotic HCl-THF medium, as compared to a differential HNO3-THF medium. Tetragonal TiO2 structure was observed in the entire hydrolysis ratio (4≤RH≤32). Interstitial lattice defect was evident in an aprotic HNO3-THF medium but absent in a differential ClHNO2-THF medium.

Combined deterministic-stochastic framework for modeling the agglomeration of colloidal particles

We present a multiscale model, based on molecular dynamics (MD) and kinetic Monte Carlo (kMC), to study the aggregation driven growth of colloidal particles. Coarse-grained molecular dynamics (CGMD) simulations are employed to detect key agglomeration events and calculate the corresponding rate constants. The kMC simulations employ these rate constants in a stochastic framework to track the growth of the agglomerates over longer time scales and length scales. One of the hallmarks of the model is a unique methodology to detect and characterize agglomeration events. The model accounts for individual cluster-scale effects such as change in size due to aggregation as well as local molecular-scale effects such as changes in the number of neighbors of each molecule in a colloidal cluster. Such definition of agglomeration events allows us to grow the cluster to sizes that are inaccessible to molecular simulations as well as track the shape of the growing cluster. A well-studied system, comprising fullerenes in NaCl electrolyte solution, was simulated to validate the model. Under the simulated conditions, the agglomeration process evolves from a diffusion limited cluster aggregation (DLCA) regime to percolating cluster in transition and finally to a gelation regime. Overall the data from the multiscale numerical model shows good agreement with existing theory of colloidal particle growth. Although in the present study we validated our model by specifically simulating fullerene agglomeration in electrolyte solution, the model is versatile and can be applied to a wide range of colloidal systems.

Structure and rheology of colloidal particle gels: insight from computer simulation

A particle gel is a network of aggregated colloidal particles with soft solid-like mechanical properties. Its structural and rheological properties, and the kinetics of its formation, are dependent on the sizes and shapes of the constituent particles, the volume fraction of the particles, and the nature of the interactions between the particles before, during and after gelation. Particle gels may be permanent or transient depending on whether the colloidal forces between the aggregating particles lead to irreversible bonding or weak reversible interactions. With short-range reversible interactions, network formation is typically associated with phase separation or kinetic arrest due to particle crowding. Much existing knowledge has been derived from computer simulations of idealized model systems containing spherical particles interacting with well-defined pair potentials. The status of current progress is reviewed here by summarizing the underlying methodology and key findings from a range of simulation approaches: Monte Carlo, molecular dynamics, Brownian dynamics, Stokesian dynamics, dissipative particle dynamics, multiparticle collision dynamics, and fluid particle dynamics. Then it is described how the technique of Brownian dynamics simulation, in particular, has provided detailed insight into how different kinds of bonding and weak reversible interactions can affect the aggregate fractal structure, the percolation behaviour, and the small-deformation rheological properties of network-forming colloidal systems. A significant ongoing development has been the establishment and testing of efficient algorithms that are able to capture the subtle dynamic structuring effects that arise from effects of interparticle hydrodynamic interactions. This has led to an appreciation recently of the potentially important role of these particle-particle hydrodynamic effects in controlling the evolving morphology of simulated colloidal aggregates and in defining the location of the sol-gel phase boundary.

Self-assembly of soft nanoparticles with tunable patchiness

Details of the forces between nanoparticles determine the ways in which the nanoparticles can self-assemble into larger structures. The use of directed interactions has led to new concepts in self-assembly such as asymmetric dendrons, Janus particles, patchy colloids and colloidal molecules. Recent models that include attractive regions or 'patches' on the surface of the nanoparticles predict a wealth of intricate modes of assembly. Interactions between such particles are also important in a range of phenomena including protein aggregation and crystallization, re-entrant phase transitions, assembly of nanoemulsions and the organization of nanoparticles into nanowires. Here, we report the synthesis of 6-nm nanoparticles with dynamic hydrophobic patches and show that they can form reversible self-assembled structures in aqueous solution that become topologically more connected upon dilution. The organization is based on guest-host supramolecular chemistry with the nanoparticles composed of a hydrophobic dendrimer host molecule and water-soluble hydrophilic guest molecules. The work demonstrates that subtle changes in hierarchal composition and/or concentration can dramatically change mesoscopic ordering.

Kinetic arrest in polyion-induced inhomogeneously charged colloidal particle aggregation

Polymer chains adsorbed onto oppositely charged colloidal particles can significantly modify the particle-particle interactions. For sufficient amounts of added polymers, the original electrostatic repulsion can even turn into an effective attraction and relatively large aggregates can form. The attractive interaction contribution between two particles arises from the correlated adsorption of polyions at the oppositely charged particle surfaces, resulting in a non-homogeneous surface charge distribution. Here, we investigate the aggregation kinetics of polyion-induced colloidal complexes through Monte Carlo simulation, in which the effect of charge anisotropy is taken into account by a DLVO-like inter-particle potential, as recently proposed by Velegol and Thwar (Langmuir 17, 7687 (2001)). The results reveal that the aggregation process slows down due to the progressive increase of the potential barrier height upon clustering. Within this framework, the experimentally observed cluster phases in polyelectrolyte-liposome solutions can be interpreted as a kinetic arrested state.

Self-diffusion of reversibly aggregating spheres

Reversible diffusion limited cluster aggregation of hard spheres with rigid bonds was simulated and the self-diffusion coefficient was determined for equilibrated systems. The effect of increasing attraction strength was determined for systems at different volume fractions and different interaction ranges. It was found that the slowing down of the diffusion coefficient due to crowding is decoupled from that due to cluster formation. The diffusion coefficient could be calculated from the cluster size distribution and became zero only at infinite attraction strength when permanent gels are formed. It is concluded that so-called attractive glasses are not formed at finite interaction strength.

Linking Phase Behavior and Reversible Colloidal Aggregation at Low Concentrations: Simulations and Stochastic Mean Field Theory

We have studied the link between the kinetics of clustering and the phase behavior of dilute colloids with short range attractions of moderate strength. This was done by means of computer simulations and a theoretical kinetic model originally developed to deal with reversible colloidal aggregation. Three different regions of the phase diagram were accessed. For weak attractions, a gas phase of small clusters in equilibrium forms in the system. For intermediate attractions, the system undergoes liquid-gas separation, which is signatured by the formation of a few large droplike aggregates, a gas phase of small clusters, and an overall kinetics where a few seeds succeed in explosively growing at long times, after a lag time. Finally, for very strong attractions, fractal unbreakable clusters form and grow following DLCA-like (diffusion limited cluster aggregation) kinetics; liquid-gas separation is prevented by the strength of the bonds, which do not allow restructuration. Good qualitative and quantitative agreement is found between the dynamic simulations and the kinetic model in all the three regions.

Phase separation and percolation of reversibly aggregating spheres with a square-well attraction potential

Reversible aggregation of spheres is simulated using a novel method in which clusters of bound spheres diffuse collectively with a diffusion coefficient proportional to their radius. It is shown that the equilibrium state is the same as with other simulation techniques, but with the present method more realistic kinetics are obtained. The behavior as a function of volume fraction and interaction strength was tested for two different attraction ranges. The binodal and the percolation threshold were determined. The cluster structure and size distribution close to the percolation threshold were found to be consistent with the percolation model. Close to the binodal phase separation occurred through the growth of spherical dense domains, while for deep quenches a system spanning network is formed that coarsens with a rate that decreases with increasing attraction. We found no indication for arrest of the coarsening.