Simulation of bidisperse colloidal centrifugal sedimentation using a mixture viscosity model

Understanding the sedimentation behavior of bidisperse colloidal suspensions is critical in determining their stability and separation. While centrifugation is often used to accelerate separation, the settling of bidisperse colloids and their phase separation under these conditions is complex and difficult to predict explicitly. As an alternative, this work proposes a one-dimensional advection-diffusion model that uses an effective maximum volume fraction with a bidisperse viscosity scheme, which reflects important characteristics of bidisperse sedimentation while remaining computationally efficient. The influence of Derjaguin–Landau–Verwey–Overbeek interactions on packing fraction and dispersion viscosity is also considered. A numerical implementation is described using an adaptive finite-difference solver, which can be used for concentration profile and settling rate prediction of both species under variable acceleration. Validation experiments with silica suspensions in two size ratios (500:800 and 100:500 nm) and various total concentrations are performed using an analytical centrifuge, with results also being compared to Richardson–Zaki empirical predictions. The model is shown to be a very good fit to the data for both size ratio dispersions at three mixing ratios, with differences <10%. Slightly higher levels of variation were detected for the 500:800 nm system, owing to the smaller size ratio and resulting greater effect of uncounted secondary hydrodynamic factors, which enables the limits of the mixture viscosity model to be established. Nevertheless, this work highlights that mixture viscosity modeling combined with effective maximum volume fraction modifications can provide critical insights into the effect of bidisperse suspension dynamics on separation efficiencies

Measuring the predictability of life outcomes with a scientific mass collaboration.

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences

Removal of cesium and strontium ions with enhanced solid-liquid separation by combined ion exchange and BaSO4 co-precipitation

Treatment of cesium and strontium is critical in radioactive liquid waste management, where their ions are difficult to remove in single operations, owing to differences in valence state. Here, the efficacy of composite coagulants synthesised by combining fine clinoptilolite with co-precipitated barite (BaSO₄) were investigated for the simultaneous removal of Cs⁺ and Sr²⁺ ions, producing aggregates with enhanced dewatering properties. Co-precipitated BaSO₄ without clinoptilolite was found to be very effective in the removal of Sr²⁺ (>99 %) while only giving low-level Cs⁺ removal (~14 %) for solutions containing 25 ppm of Cs⁺ and Sr². Conversely, pure clinoptilolite gave high Cs⁺ removal (>98 %) with rapid adsorption (99.9 %), whereas Cs⁺ removal was reduced to 95 % removal. Their physical properties, sedimentation rates, and compressional yield stress were also studied to characterise the aggregates solid-liquid separation behaviour. The combined coagulates obtained settling rates almost twice that of pure BaSO₄, and produced much greater consolidation, owing to increased aggregate density. Also, the combined systems had a higher gel point and lower specific compressive yield stress, suggesting less resistance to compression under centrifugal forces for dewatering. Overall, this study highlights that the use of composite coagulants can improve the removal efficiency of Cs⁺ and Sr²⁺ while also accelerating solid-liquid dewatering