The drift-diffusion equation is first solved analytically for the dissociation rate and lifetime of a biomolecular or colloidal dimer bonded by realistic intermolecular potentials, under shear flow. Then we show using rigidity percolation concepts that the lifetime of a generic cluster formed under shear is controlled by the typical lifetime of a single bond in its interior. The latter, however, is also affected by collective stress transmission from other bonds in the aggregate, which we account for by introducing a semiempirical, analytical stress transmission efficiency 0 1 calibrated on several simulation data sets. We show that aggregate breakup is a thermally activated process in which the activation energy is controlled by the interplay between intermolecular forces and the shear drift. The collective contribution to the overall shear drift term is dominant for large enough fractal aggregates, while surface erosion prevails for small and compact aggregates. The crossover between the two regimes occurs when N 2, where both the number of particles in the cluster N and the stress transmission efficiency depend on the aggregate structure through the fractal dimension d f . The analytical framework for the aggregate breakup rate is in quantitative agreement with experiments and can be used in future studies in the population balance modeling of colloidal and protein aggregation.
Interactions between colloidal particles are strongly affected by the particle surface chemistry and composition of the liquid phase. Further complexity is introduced when particles are exposed to shear flow, often leading to broad variation of the final properties of formed clusters. Here we discover a new dynamical effect arising in shear-induced aggregation where repeated aggregation and breakup events cause the particle surface roughness to irreversibly increase with time, thus decreasing the bond adhesive energy and the resistance of the aggregates to breakup. This leads to a pronounced overshoot in the time evolution of the aggregate size, which can only be explained with the proposed mechanism. This is demonstrated by good agreement between time evolution of measured light-scattering data and those calculated with a population-balance model taking into account the increase in the primary particle nanoroughness caused by repeated breakup events resulting in the decrease of bond adhesive energy as a function of time. Thus, the proposed model is able to reproduce the overshoot phenomenon by taking into account the physicochemical parameters, such as pH, till now not considered in the literature. Overall, this new effect could be exploited in the future to achieve better control over the flow-induced assembly of nanoparticles.
The gelation kinetics of silica nanoparticles is a central process in physical chemistry, yet not fully understood. Gelation times are measured to increase by over four orders of magnitude, simply changing the monovalent salt species from CsCl to LiCl. This striking effect has no microscopic explanation within current paradigms. The trend is consistent with the Hofmeister series, pointing to short-ranged solvation effects not included in the standard colloidal (DLVO) interaction potential. By implementing a simple form for short-range repulsion within a model that relates the gelation time-scale to the colloidal interaction forces, we are able to explain the many orders of magnitude difference in the gelation times at fixed salt concentration. The model allows to estimate the magnitude of the non-DLVO hydration forces, which dominate the interparticle interactions at the length-scale of the hydrated ion diameter. This opens the possibility of finely tuning the gelation time-scale of nanoparticles by just adjusting the background electrolyte species.
We combine the analytical theory of nonaffine deformations of noncrystalline solids with numerical Stokesian dynamical simulations to obtain analytical closed-form expressions for the shear modulus of fractal aggregates in shear flows. The proposed framework also provides analytical predictions for the evolution of the fractal dimension d f of the aggregate during the aggregation process. This leads to a lower bound on d f below which aggregates are mechanically unstable (they possess floppy modes) and cannot survive without restructuring into more compact, higher-d f configurations. In the limit of large aggregates, the predicted lower bound is d f = 2.407. This result provides the long-sought explanation as to why all experimental and simulation studies in the past consistently reported d f ≳ 2.4 for shear-induced colloidal aggregation. The analytical expressions derived here can be used within population balance calculations of colloidal aggregation in shear flows whereby until now the fractal dimension evolution was treated as a free parameter. These results may open up the possibility of developing new microscopic mechanical manipulation techniques to control nanoparticle and colloidal aggregates at the nanoscale.
Many surfactant-based formulations are utilised in industry as they produce desirable visco-elastic properties at low-concentrations. These properties are due to the presence of worm-like micelles (WLM) and, as a result, understanding the processes that
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