Stratification in binary colloidal mixtures was investigated using implicit-solvent molecular dynamics simulations. For large particle size ratios and film Péclet numbers greater than unity, smaller colloids migrated to the top of the film, while big colloids were pushed to the bottom, creating an "inverted" stratification. This peculiar behavior was observed in recent simulations and experiments conducted by Fortini et al. [ Phys. Rev. Lett. 2016 , 116 , 118301 ]. To rationalize this behavior, particle size ratios and drying rates spanning qualitatively different Péclet number regimes were systematically studied, and the dynamics of the inverted stratification were quantified in detail. The stratified layer of small colloids was found to grow faster and to larger thicknesses for larger size ratios. Interestingly, inverted stratification was observed even at moderate drying rates where the film Péclet numbers were comparable to unity, but the thickness of the stratified layer decreased. A model based on dynamical density functional theory is proposed to explain the observed phenomena.

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We present a machine learning technique to discover and distinguish relevant ordered structures from molecular simulation snapshots or particle tracking data. Unlike other popular methods for structural identification, our technique requires no a priori description of the target structures. Instead, we use nonlinear manifold learning to infer structural relationships between particles according to the topology of their local environment. This graph-based approach yields unbiased structural information which allows us to quantify the crystalline character of particles near defects, grain boundaries, and interfaces. We demonstrate the method by classifying particles in a simulation of colloidal crystallization, and show that our method identifies structural features that are missed by standard techniques.

Drying polymer-polymer and colloid-polymer mixtures were studied using Langevin dynamics computer simulations. Polymer-polymer mixtures vertically stratified into layers, with the shorter polymers enriched near the drying interface and the longer polymers pushed down toward the substrate. Colloid-polymer mixtures stratified into a polymer-on-top structure when the polymer radius of gyration was comparable to or smaller than the colloid diameter, and a colloid-on-top structure otherwise. We also developed a theoretical model for the drying mixtures based on dynamical density functional theory, which gave excellent quantitative agreement with the simulations for the polymer-polymer mixtures and qualitatively predicted the observed polymer-on-top or colloid-on-top structures for the colloid-polymer mixtures.

Low-density "equilibrium" gels that consist of a percolated, kinetically arrested network of colloidal particles and are resilient to aging can be fabricated by restricting the number of effective bonds that form between the colloids. Valence-restricted patchy particles have long served as one archetypal example of such materials, but equilibrium gels can also be realized through a synthetically simpler and scalable strategy that introduces a secondary linker, such as a small ditopic molecule, to mediate the bonds between the colloids. Here, we consider the case where the ditopic linker molecules are low-molecular-weight polymers and demonstrate using a model colloid-polymer mixture how macroscopic properties such as the phase behavior as well as the microstructure of the gel can be designed through the polymer molecular weight and concentration. The low-density window for equilibrium gel formation is favorably expanded using longer linkers, while necessarily increasing the spacing between all colloids. However, we show that blends of linkers with different sizes enable wider variation in microstructure for a given target phase behavior. Our computational study suggests a robust and tunable strategy for the experimental realization of equilibrium colloidal gels.

Functional soft materials, comprising colloidal and molecular building blocks that self-organize into complex structures as a result of their tunable interactions, enable a wide array of technological applications. Inverse methods provide systematic means for navigating their inherently high-dimensional design spaces to create materials with targeted properties. While multiple physically motivated inverse strategies have been successfully implemented in silico, their translation to guiding experimental materials discovery has thus far been limited to a handful of proof-of-concept studies. In this Perspective, we discuss recent advances in inverse methods for design of soft materials that address two challenges: (1) methodological limitations that prevent such approaches from satisfying design constraints and (2) computational challenges that limit the size and complexity of systems that can be addressed. Strategies that leverage machine learning have proven particularly effective, including methods to discover order parameters that characterize complex structural motifs and schemes to efficiently compute macroscopic properties from the underlying structure. We also highlight promising opportunities to improve the experimental realizability of materials designed computationally, including discovery of materials with functionality at multiple thermodynamic states, design of externally directed assembly protocols that are simple to implement in experiments, and strategies to improve the accuracy and computational efficiency of experimentally relevant models. arXiv:2004.00181v1 [cond-mat.soft] 1 Apr 2020

We present an algorithm based on linear bounding volume hierarchies (LBVHs) for computing neighbor (Verlet) lists using graphics processing units (GPUs) for colloidal systems characterized by large size disparities. We compare this to a GPU implementation of the current state-of-the-art CPU algorithm based on stenciled cell lists. We report benchmarks for both neighbor list algorithms in a Lennard-Jones binary mixture with synthetic interaction range disparity and a realistic colloid solution. LBVHs outperformed the stenciled cell lists for systems with moderate or large size disparity and dilute or semidilute fractions of large particles, conditions typical of colloidal systems.

Objective: To describe cardiovascular disease (CVD) risk management in Indigenous primary health care. Design, setting and participants: Review of 1165 randomly selected case records of Indigenous Australian adults, aged ≥ 18 years, regularly attending eight health services in diverse settings in New South Wales, Queensland and Central Australia, October 2007 – May 2008. Main outcome measure: Adherence to CVD risk screening and management guidelines, especially with respect to overall or absolute CVD risk. Results: More than half the people in the sample (53%) were not adequately screened for CVD risk according to national recommendations. Underscreening was significantly associated with younger age, less frequent attendance, and lower uptake of the Medicare Health Assessment. Of the sample, 9% had established CVD, and 29% of those aged ≥ 30 years were classified as high risk according to the 2004 National Heart Foundation of Australia (NHFA) adjusted Framingham equation. Of those with CVD, 40% (95% CI, 30%–50%) were not prescribed a combination of blood pressure (BP) medicines, statins and antiplatelet agents, and 56% (95% CI, 49%–62%) of high‐risk individuals without CVD were not prescribed BP medicines and statins. For high‐risk individuals not prescribed BP medicines or statins, 74% (95% CI, 64%–84%) and 30% (95% CI, 23%–39%) respectively, did not meet 2004 NHFA criteria for prescribing of these medications, and of those already prescribed BP medicines or statins, 41% (95% CI, 36%–47%) and 59% (95% CI, 52%–66%) did not meet respective guideline targets. Conclusions: These management gaps are similar to those found in non‐Indigenous health care settings, suggesting deficiencies across the health system. Prescribing guidelines which exclude many high‐risk individuals contribute to suboptimal management. Guideline reform and improved health service capacity could substantially improve Indigenous vascular health.