Critical onset of layering in sedimenting suspensions of nanoparticles

Probing sedimentation non-ideality of particulate systems using analytical centrifugation

Analytical centrifugation is a versatile technique for the quantitative characterization of colloidal systems including colloidal stability. The recent developments in data acquisition and evaluation allow the accurate determination of particle size, shape anisotropy and particle density. High precision analytical centrifugation is in particular suited for the study of particle interactions and concentration-dependent sedimentation coefficients. We present a holistic approach for the quantitative determination of sedimentation non-ideality via analytical centrifugation for polydisperse, plain and amino-functionalized silica particles spanning over one order of magnitude in particle size between 100 nm and 1200 nm. These systems typically behave as neutral hard spheres as predicted by auxiliary lattice Boltzmann simulations. The extent of electrostatic interactions and their impact on sedimentation non-ideality can be quantified by the repulsion range, which is the ratio of the Debye length and the average interparticle distance. Experimental access to the repulsion range is provided through conductivity measurements. With the experimental repulsion range at hand, we estimate the effect of polydispersity on concentration-dependent sedimentation properties through a combination of lattice Boltzmann and Brownian dynamics simulations. Finally, we determine the concentration-dependent sedimentation properties of charge-stabilized, fluorescently-labeled silica particles with a nominal particle size of 30 nm and reduced interparticle distance, hence an elevated repulsion range. Overall, our results demonstrate how the influence of hard-sphere type and electrostatic interactions can be quantified when probing sedimentation non-ideality of particulate systems using analytical centrifugation even for systems exhibiting moderate sample heterogeneity and complex interactions.

Colloidal Swarms Can Settle Faster than Isolated Particles: Enhanced Sedimentation near Phase Separation

By experimenting on model colloids where depletion forces can be carefully tuned and quantified, we show that attractive interactions consistently "promote" particle settling, so much that the sedimentation velocity of a moderately concentrated dispersion can even exceed its single-particle value. At larger particle volume fraction ϕ, however, hydrodynamic hindrance eventually takes over. Hence, v(ϕ) actually displays a nonmonotonic trend that may threaten the stability of the settling front to thermal perturbations. Finally, by discussing a representative case, we show that these results are relevant to the investigation of protein association effects by ultracentrifugation.

New possibilities of accurate particle characterisation by applying direct boundary models to analytical centrifugation

Analytical centrifugation (AC) is a powerful technique for the characterisation of nanoparticles in colloidal systems. As a direct and absolute technique it requires no calibration or measurements of standards. Moreover, it offers simple experimental design and handling, high sample throughput as well as moderate investment costs. However, the full potential of AC for nanoparticle size analysis requires the development of powerful data analysis techniques. In this study we show how the application of direct boundary models to AC data opens up new possibilities in particle characterisation. An accurate analysis method, successfully applied to sedimentation data obtained by analytical ultracentrifugation (AUC) in the past, was used for the first time in analysing AC data. Unlike traditional data evaluation routines for AC using a designated number of radial positions or scans, direct boundary models consider the complete sedimentation boundary, which results in significantly better statistics. We demonstrate that meniscus fitting, as well as the correction of radius and time invariant noise significantly improves the signal-to-noise ratio and prevents the occurrence of false positives due to optical artefacts. Moreover, hydrodynamic non-ideality can be assessed by the residuals obtained from the analysis. The sedimentation coefficient distributions obtained by AC are in excellent agreement with the results from AUC. Brownian dynamics simulations were used to generate numerical sedimentation data to study the influence of diffusion on the obtained distributions. Our approach is further validated using polystyrene and silica nanoparticles. In particular, we demonstrate the strength of AC for analysing multimodal distributions by means of gold nanoparticles.