Viscosity of bimodal and polydisperse colloidal suspensions

Colloidal Physics Modeling Reveals How Per-Ribosome Productivity Increases with Growth Rate in Escherichia coli

Faster-growing cells must synthesize proteins more quickly. Increased ribosome abundance only partly accounts for increases in total protein synthesis rates. The productivity of individual ribosomes must increase too, almost doubling by an unknown mechanism. Prior models point to diffusive transport as a limiting factor but raise a paradox: faster-growing cells are more crowded, yet crowding slows diffusion. We suspected that physical crowding, transport, and stoichiometry, considered together, might reveal a more nuanced explanation. To investigate, we built a first-principles physics-based model of Escherichia coli cytoplasm in which Brownian motion and diffusion arise directly from physical interactions between individual molecules of finite size, density, and physiological abundance. Using our microscopically detailed model, we predicted that physical transport of individual ternary complexes accounts for ~80% of translation elongation latency. We also found that volumetric crowding increases during faster growth even as cytoplasmic mass density remains relatively constant. Despite slowed diffusion, we predicted that improved proximity between ternary complexes and ribosomes wins out, illustrating a simple physics-based mechanism for how individual elongating ribosomes become more productive. We speculate that crowding imposes a physical limit on growth rate and undergirds cellular behavior more broadly. Unfitted colloidal-scale modeling offers systems biology a complementary "physics engine" for exploring how cellular-scale behaviors arise from physical transport and reactions among individual molecules. IMPORTANCE Ribosomes are the factories in cells that synthesize proteins. When cells grow faster, there are not enough ribosomes to keep up with the demand for faster protein synthesis without individual ribosomes becoming more productive. Yet, faster-growing cells are more crowded, seemingly making it harder for each ribosome to do its work. Our computational model of the physics of translation elongation reveals the underlying mechanism for how individual ribosomes become more productive: proximity and stoichiometry of translation molecules overcome crowding. Our model also suggests a universal physical limitation of cell growth rates.

Viscosity Model for Nanoparticulate Suspensions Based on Surface Interactions

In this paper, a widely mechanistic model was developed to depict the rheological behaviour of nanoparticulate suspensions with solids contents up to 20 wt.%, based on the increase in shear stress caused by surface interaction forces among particles. The rheological behaviour is connected to drag forces arising from an altered particle movement with respect to the surrounding fluid. In order to represent this relationship and to model the viscosity, a hybrid modelling approach was followed, in which mechanistic relationships were paired with heuristic expressions. A genetic algorithm was utilized during model development, by enabling the algorithm to choose among several hard-to-assess model options. By the combination of the newly developed model with existing models for the various physical phenomena affecting viscosity, it can be applied to model the viscosity over a broad range of solids contents, shear rates, temperatures and particle sizes. Due to its mechanistic nature, the model even allows an extrapolation beyond the limits of the data points used for calibration, allowing a prediction of the viscosity in this area. Only two parameters are required for this purpose. Experimental data of an epoxy resin filled with boehmite nanoparticles were used for calibration and comparison with modelled values.

Two-step yielding behavior of densely packed microgel mixtures with chemically dissimilar surfaces and largely different sizes

Steady-state flow and elastic behavior is investigated for the moderately concentrated binary suspensions of soft microgels (pastes) with chemically dissimilar surfaces, and various degrees of size- and stiffness disparities. The pastes of poly(N-isopropyl acrylamide) (N) and poly(N-isopropyl methacrylamide) (NM) microgels with different values of yield strain γc (γNc > γNMc) are employed as the components. For the single microgel pastes (φ ≈ 1 where φ is apparent volume fraction), the values of γc are governed by the chemical species of constituent polymer in microgel surface whereas γc is insensitive to cross-link density and particle size. We demonstrate that the binary N/NM pastes with large size disparity (RN/NM = DN/DNM < 0.26 where D is the microgel diameter) at low φN (φN: weight fraction of small N microgels) exhibit the peculiarities in several rheological aspects, i.e., the two-step yielding in steady-state flow, and their values of γc and equilibrium shear modulus (G0) being equivalent to those of the single large NM microgel paste. These peculiarities are attributed to the characteristic packing resulting from large size disparity in which all or almost of the small N microgels tend to be accommodated in the gap between the large NM microgels even in moderately concentrated state. This characteristic packing substantially masks the contribution of the small N microgels at low φN, explaining the φN-independent G0 and γc as well as the first yielding governed solely by the large NM microgels. The second yielding results from the emerged contribution of the small N microgels expelled out from the gap by the positional rearrangements after the first yielding. The binary homo-N/N pastes with the similarly large size disparity at low φsmall also exhibit the φsmall-independent values of G0, but they show one-step yielding, indicating that the two-step yielding requires not only sufficiently large size disparity but also chemical dissimilarity (different values of γc) between the two components.

Structure and Dynamics of Bimodal Colloidal Dispersions in a Low-Molecular-Weight Polymer Solution

We present an experimental study of the structural and dynamical properties of bimodal, micrometer-sized colloidal dispersions (size ratio ≈ 2) in an aqueous solution of low-molecular-weight polymer (polyethylene glycol 2000) using synchrotron ultra-small angle X-ray scattering (USAXS) and USAXS-based X-ray photon correlation spectroscopy. We fixed the volume fraction of the large particles at 5% and systematically increased the volume fraction of the small particles from 0 to 5% to evaluate their effects on the structure and dynamics. The bimodal dispersions were homogenous through the investigated parameter space. We found that the partial structure factors can be satisfactorily retrieved for the bimodal colloidal dispersions using a Percus-Yevick hard-sphere potential when the size distributions of the particles were taken into account. We also found that the partial structure factor between the large particles did not exhibit a significant variation with increasing volume fraction of the small particles, whereas the isothermal compressibility of the binary mixture was found to decrease with increasing volume fraction of the small particles. The dynamics of single-component large-particle dispersion obey the principles of de Gennes narrowing, where the wave vector dependence of the interparticle diffusion coefficient is inversely proportional to the interparticle structure factor. The dynamics of the bimodal dispersions demonstrate a strong dependence on the fraction of small particles. We also made a comparison between the experimental effective dynamic viscosity of the bimodal dispersion with the theoretical predictions, which suggest that the complex mutual interactions between the large and small particles have a strong effect on the dynamic behaviors of bimodal dispersions.

Impact of aggregate formation on the viscosity of protein solutions

Gaining knowledge on the stability and viscosity of concentrated therapeutic protein solutions is of great relevance to the pharmaceutical industry. In this work, we borrow key concepts from colloid science to rationalize the impact of aggregate formation on the changes in viscosity of a concentrated monoclonal antibody solution. In particular, we monitor the kinetics of aggregate growth under thermal stress by static and dynamic light scattering, and we follow the rise in solution viscosity by measuring the diffusion coefficient of tracer nanoparticles with dynamic light scattering. Moreover, we characterize aggregate morphology in the frame of the fractal geometry. We show that the curves of the increase in viscosity with time monitored at three different protein concentrations collapse on one single master curve when the reaction profiles are normalized based on an effective volume fraction occupied by the aggregates, which depends on the aggregate size, concentration and morphology. Importantly, we find that the viscosity of an aggregate sample is lower than the viscosity of a monomeric sample of a similar occupied volume fraction due to the polydispersity of the aggregate distribution.

Viscosity scaling in concentrated dispersions and its impact on colloidal aggregation

Viscosity scaling in concentrated dispersions is identified using Brownian dynamics simulations, and its impact on colloidal aggregation is quantified.

Viscosity of a concentrated suspension of rigid monosized particles

This paper addresses the relative viscosity of concentrated suspensions loaded with unimodal hard particles. So far, exact equations have only been put forward in the dilute limit, e.g., by Einstein [A. Einstein, Ann. Phys. 19, 289 (1906) (in German); Ann. Phys. 34, 591 (1911) (in German)] for spheres. For larger concentrations, a number of phenomenological models for the relative viscosity was presented, which depend on particle concentration only. Here, an original and exact closed form expression is derived based on geometrical considerations that predicts the viscosity of a concentrated suspension of monosized particles. This master curve for the suspension viscosity is governed by the relative viscosity-concentration gradient in the dilute limit (for spheres the Einstein limit) and by random close packing of the unimodal particles in the concentrated limit. The analytical expression of the relative viscosity is thoroughly compared with experiments and simulations reported in the literature, concerning both dilute and concentrated suspensions of spheres, and good agreement is found.

Energy landscape, antiplasticization, and polydispersity induced crossover of heterogeneity in supercooled polydisperse liquids

Polydispersity is found to have a significant effect on the potential energy landscape; the average inherent structure energy decreases with polydispersity. Increasing polydispersity at a fixed volume fraction decreases the glass transition temperature and the fragility of glass formation analogous to the antiplasticization seen in some polymeric melts. An interesting temperature dependent crossover of heterogeneity with polydispersity is observed at low temperature due to the faster buildup of dynamic heterogeneity at lower polydispersity.

Role of polydispersity in anomalous interactions in electrostatically levitated colloidal systems

In this paper, we investigate the effects of using inverse analyses developed for monodisperse particles to extract particle-particle and particle-surface potentials from simulated interfacial colloidal configurations having finite-size polydispersity. Forward Monte Carlo simulations are used to generate three-dimensional equilibrium configurations of log normal-distributed polydisperse particles confined by gravity near an underlying surface. Particles remain levitated above the substrate and stabilized against aggregation by repulsive electrostatic Derjaguin-Landau-Verwey-Overbeek pair potentials. An inverse Ornstein-Zernike analysis and an inverse Monte Carlo simulation method are used to obtain interactions from simulated distribution functions as a function of polydispersity (sigma), relative range of repulsion (kappa a), and projected interfacial concentration (rho). Both inverse analyses successfully recover input potentials for all monodisperse cases, but fail for polydispersities often encountered in experiments. For different conditions (sigma, kappa a, and rho), our results indicate softened short-range repulsion, anomalous long-range attraction, and apparent particle overlaps, which are similar to commonly reported observations in optical microscopy measurements of quasi-two-dimensional interfacial colloidal ensembles. By demonstrating signatures of, and limitations due to, polydispersity when extracting pair potentials from measured distribution functions, our specific goal is to provide a basis to objectively interpret and resolve the effects of polydispersity in optical microscopy experiments.

A new perspective on the coarse-grained dynamics of fluids

A computational methodology is presented that is designed to model, at a coarse-grained level, the mesoscale dynamics of fluids and potentially other forms of soft matter. Within a molecular dynamics simulation, "ghost" particles of a specific size, corresponding to the fundamental length-scale of coarse-graining, are used as micro-probes designed to respond to local mesoscale fluid flows and stress gradients. A subsequent coarse-grained model is then developed that incorporates both the coarse-grained mesoscale dynamics and isothermal compressibility of the original microscopic system. The method is applied to water and methanol. A contrast with dissipative particle dynamics (DPD) is also presented.