Diffusioosmotic and convective flows induced by a nonelectrolyte concentration gradient.

Glucose is an important energy source in our bodies, and its consumption results in gradients over length scales ranging from the subcellular to entire organs. Concentration gradients can drive material transport through both diffusioosmosis and convection. Convection arises because concentration gradients are mass density gradients. Diffusioosmosis is fluid flow induced by the interaction between a solute and a solid surface. A concentration gradient parallel to a surface creates an osmotic pressure gradient near the surface, resulting in flow. Diffusioosmosis is well understood for electrolyte solutes, but is more poorly characterized for nonelectrolytes such as glucose. We measure fluid flow in glucose gradients formed in a millimeter-long thin channel and find that increasing the gradient causes a crossover from diffusioosmosis-dominated to convection-dominated flow. We cannot explain this with established theories of these phenomena which predict that both scale linearly. In our system, the convection speed is linear in the gradient, but the diffusioosmotic speed has a much weaker concentration dependence and is large even for dilute solutions. We develop existing models and show that a strong surface-solute interaction, a heterogeneous surface, and accounting for a concentration-dependent solution viscosity can explain our data. This demonstrates how sensitive nonelectrolyte diffusioosmosis is to surface and solution properties and to surface-solute interactions. A comprehensive understanding of this sensitivity is required to understand transport in biological systems on length scales from micrometers to millimeters where surfaces are invariably complex and heterogeneous.

Quantitative imaging and modeling of colloidal gelation in the coagulant dipping process.

Many common elastomeric products, including nitrile gloves, are manufactured by coagulant dipping. This process involves the destabilization and gelation of a latex dispersion by an ionic coagulant. Despite widespread application, the physical chemistry governing coagulant dipping is poorly understood. It is unclear which properties of an electrolyte determine its efficacy as a coagulant and which phenomena control the growth of the gel. Here, a novel experimental protocol is developed to directly observe coagulant gelation by light microscopy. Gel growth is imaged and quantified for a variety of coagulants and compared to macroscopic dipping experiments mimicking the industrial process. When the coagulant is abundant, gels grow with a t1/2 time dependence, suggesting that this phenomenon is diffusion-dominated. When there is a finite amount of coagulant, gels grow to a limiting thickness. Both these situations are modeled as one-dimensional diffusion problems, reproducing the qualitative features of the experiments including which electrolytes cause rapid growth of thick gels. We propose that the gel thickness is limited by the amount of coagulant available, and the growth is, therefore, unbounded when the coagulant is abundant. The rate of the gel growth is controlled by a combination of a diffusion coefficient and the ratio of the critical coagulation concentration to the amount of coagulant present, which in many situations is set by the coagulant solubility. Other phenomena, including diffusiophoresis, may make a more minor contribution to the rate of gel growth.

Diffusiophoresis in Cells: A General Nonequilibrium, Nonmotor Mechanism for the Metabolism-Dependent Transport of Particles in Cells.

The more we learn about the cytoplasm of cells, the more we realize that the cytoplasm is not uniform but instead is highly inhomogeneous. In any inhomogeneous solution, there are concentration gradients, and particles move either up or down these gradients due to a mechanism called diffusiophoresis. I estimate that inside metabolically active cells, the dynamics of particles can be strongly accelerated by diffusiophoresis, provided that they are at least tens of nanometers across. The dynamics of smaller objects, such as single proteins, are largely unaffected.

Stratification of mixtures in evaporating liquid films occurs only for a range of volume fractions of the smaller component.

I model the drying of a liquid film containing small and big colloid particles. Fortini et al. [Phys. Rev. Lett. 116, 118301 (2016)] studied these films with both computer simulation and experiment. They found that at the end of drying, the mixture had stratified with a layer of the smaller particles on top of the big particles. I develop a simple model for this process. The model has two ingredients: arrest of the diffusion of the particles at high density and diffusiophoretic motion of the big particles due to gradients in the volume fraction of the small particles. The model predicts that stratification only occurs over a range of initial volume fractions of the smaller colloidal species. Above and below this range, the downward diffusiophoretic motion of the big particles is too slow to remove the big particles from the top of the film, and so there is no stratification. In agreement with earlier work, the model also predicts that large Péclet numbers for drying are needed to see stratification.

Stratification and Size Segregation of Ternary and Polydisperse Colloidal Suspensions during Drying.

We investigate the drying process of three-component and polydisperse colloidal suspensions using Brownian dynamics simulations. We have previously reported (Phys. Rev. Lett. 2016, 116, 118301) on the drying of binary mixtures. For binary mixtures, we found that a gradient of colloidal osmotic pressure develops during drying and that this leads to the final film being stratified with a layer of smaller particles on top of a layer of larger particles. Here, we find that stratification by size is very general and also occurs in ternary and polydisperse mixtures. We name the segregation effect colloidal diffusiophoresis. In particular, we show that by changing the composition of a ternary mixture, different stratification morphologies can be achieved and hence the film properties can be tuned. In polydisperse spheres, colloidal diffusiophoresis leads to enrichment in the large particles at the bottom part of the film, whereas the top part is enriched with smaller particles. This segregation means that in the final film, the particle size distribution depends on height. Thus, the properties of the film will then depend on height. We propose a model that predicts a power-law dependence of the phoretic velocity on particle size. Results from the model and simulation show a good agreement.

Long-lived non-equilibrium interstitial solid solutions in binary mixtures.

We perform particle resolved experimental studies on the heterogeneous crystallisation process of two component mixtures of hard spheres. The components have a size ratio of 0.39. We compared these with molecular dynamics simulations of homogenous nucleation. We find for both experiments and simulations that the final assemblies are interstitial solid solutions, where the large particles form crystalline close-packed lattices, whereas the small particles occupy random interstitial sites. This interstitial solution resembles that found at equilibrium when the size ratios are 0.3 [L. Filion et al., Phys. Rev. Lett. 107, 168302 (2011)] and 0.4 [L. Filion, Ph.D. thesis, Utrecht University, 2011]. However, unlike these previous studies, for our system simulations showed that the small particles are trapped in the octahedral holes of the ordered structure formed by the large particles, leading to long-lived non-equilibrium structures in the time scales studied and not the equilibrium interstitial solutions found earlier. Interestingly, the percentage of small particles in the crystal formed by the large ones rapidly reaches a maximum of ∼14% for most of the packing fractions tested, unlike previous predictions where the occupancy of the interstitial sites increases with the system concentration. Finally, no further hopping of the small particles was observed.

Controlling the crystal polymorph by exploiting the time dependence of nucleation rates.

Most substances can crystallise into two or more different crystal lattices called polymorphs. Despite this, there are no systems in which we can quantitatively predict the probability of one competing polymorph forming instead of the other. We address this problem using large scale (hundreds of events) studies of the competing nucleation of the alpha and gamma polymorphs of glycine. In situ Raman spectroscopy is used to identify the polymorph of each crystal. We find that the nucleation kinetics of the two polymorphs is very different. Nucleation of the alpha polymorph starts off slowly but accelerates, while nucleation of the gamma polymorph starts off fast but then slows. We exploit this difference to increase the purity with which we obtain the gamma polymorph by a factor of ten. The statistics of the nucleation of crystals is analogous to that of human mortality, and using a result from medical statistics, we show that conventional nucleation data can say nothing about what, if any, are the correlations between competing nucleation processes. Thus we can show that with data of our form it is impossible to disentangle the competing nucleation processes. We also find that the growth rate and the shape of a crystal depend on it when nucleated. This is new evidence that nucleation and growth are linked.

Erratum: Dynamic Stratification in Drying Films of Colloidal Mixtures [Phys. Rev. Lett. 116, 118301 (2016)].

This corrects the article DOI: 10.1103/PhysRevLett.116.118301.

Publisher's Note: Dynamic Stratification in Drying Films of Colloidal Mixtures [Phys. Rev. Lett. 116, 118301 (2016)].

This corrects the article DOI: 10.1103/PhysRevLett.116.118301.

Dynamic Stratification in Drying Films of Colloidal Mixtures.

In simulations and experiments, we study the drying of films containing mixtures of large and small colloidal particles in water. During drying, the mixture stratifies into a layer of the larger particles at the bottom with a layer of the smaller particles on top. We developed a model to show that a gradient in osmotic pressure, which develops dynamically during drying, is responsible for the segregation mechanism behind stratification.

Controlling bad-actor-artificial intelligence activity at scale across online battlefields.

We consider the looming threat of bad actors using artificial intelligence (AI)/Generative Pretrained Transformer to generate harms across social media globally. Guided by our detailed mapping of the online multiplatform battlefield, we offer answers to the key questions of what bad-actor-AI activity will likely dominate, where, when-and what might be done to control it at scale. Applying a dynamical Red Queen analysis from prior studies of cyber and automated algorithm attacks, predicts an escalation to daily bad-actor-AI activity by mid-2024-just ahead of United States and other global elections. We then use an exactly solvable mathematical model of the observed bad-actor community clustering dynamics, to build a Policy Matrix which quantifies the outcomes and trade-offs between two potentially desirable outcomes: containment of future bad-actor-AI activity vs. its complete removal. We also give explicit plug-and-play formulae for associated risk measures.

Offline events and online hate.

Online hate speech is a critical and worsening problem, with extremists using social media platforms to radicalize recruits and coordinate offline violent events. While much progress has been made in analyzing online hate speech, no study to date has classified multiple types of hate speech across both mainstream and fringe platforms. We conduct a supervised machine learning analysis of 7 types of online hate speech on 6 interconnected online platforms. We find that offline trigger events, such as protests and elections, are often followed by increases in types of online hate speech that bear seemingly little connection to the underlying event. This occurs on both mainstream and fringe platforms, despite moderation efforts, raising new research questions about the relationship between offline events and online speech, as well as implications for online content moderation.

Statistical mechanics of convergent evolution in spatial patterning.

We explore how the genotype-phenotype map determines convergent evolution in a simple model of spatial gene regulation during development. Evolution is simulated via a Monte Carlo scheme that incorporates mutation, selection, and genetic drift, by using a bottom-up model of gene regulation with a fitness function that is optimized by a switch-like response to a morphogen gradient. We find that even for very simple regulation, the genotype-phenotype map gives rise to an emergent fitness landscape of remarkable complexity. This leads to a richness of evolutionary behavior as population size is increased that parallels the thermodynamics of physical systems as temperature decreases. Convergence is controlled by the existence of sufficiently dominant global optima in "free fitness," which is a quantity that is the balance of mutational entropy and fitness. In independent simulations at low population sizes, we find convergence to a phenotype of suboptimal fitness due to the multiplicity or entropy of solutions. This contrasts with convergence to the optimal fitness phenotype at high population size. However, at sufficiently large population sizes, we find convergence in only the phenotypes with greatest effect on fitness, whereas noncritical phenotypes exhibit divergence due to quenched disorder on a locally rough landscape. Our results predict that for large populations, the evolution of even simple gene regulatory circuits may be glassy-like, such that, counter to the commonly accepted view that conservation implies function, many conserved phenotypes are simply frozen accidents of little consequence to the fitness of the organism.

Modeling the filtration efficiency of a woven fabric: The role of multiple lengthscales.

During the COVID-19 pandemic, many millions have worn masks made of woven fabric to reduce the risk of transmission of COVID-19. Masks are essentially air filters worn on the face that should filter out as many of the dangerous particles as possible. Here, the dangerous particles are the droplets containing the virus that are exhaled by an infected person. Woven fabric is unlike the material used in standard air filters. Woven fabric consists of fibers twisted together into yarns that are then woven into fabric. There are, therefore, two lengthscales: the diameters of (i) the fiber and (ii) the yarn. Standard air filters have only (i). To understand how woven fabrics filter, we have used confocal microscopy to take three-dimensional images of woven fabric. We then used the image to perform lattice Boltzmann simulations of the air flow through fabric. With this flow field, we calculated the filtration efficiency for particles a micrometer and larger in diameter. In agreement with experimental measurements by others, we found that for particles in this size range, the filtration efficiency is low. For particles with a diameter of 1.5 µm, our estimated efficiency is in the range 2.5%-10%. The low efficiency is due to most of the air flow being channeled through relatively large (tens of micrometers across) inter-yarn pores. So, we conclude that due to the hierarchical structure of woven fabrics, they are expected to filter poorly.

Aligned, isotropic and patterned carbon nanotube substrates that control the growth and alignment of Chinese hamster ovary cells.

Here we culture Chinese hamster ovary cells on isotropic, aligned and patterned substrates based on multiwall carbon nanotubes. The nanotubes provide the substrate with nanoscale topography. The cells adhere to and grow on all substrates, and on the aligned substrate, the cells align strongly with the axis of the bundles of the multiwall nanotubes. This control over cell alignment is required for tissue engineering; almost all tissues consist of oriented cells. The aligned substrates are made using straightforward physical chemistry techniques from forests of multiwall nanotubes; no lithography is required to make inexpensive large-scale substrates with highly aligned nanoscale grooves. Interestingly, although the cells strongly align with the nanoscale grooves, only a few also elongate along this axis: alignment of the cells does not require a pronounced change in morphology of the cell. We also pattern the nanotube bundles over length scales comparable to the cell size and show that the cells follow this pattern.

Sonocrystallisation of ZIF-8 in water with high excess of ligand: Effects of frequency, power and sonication time.

A systematic study on the sonocrystallisation of ZIF-8 (zeolitic imidazolate framework-8) in a water-based system was investigated under different mixing speeds, ultrasound frequencies, calorimetric powers and sonication time. Regardless of the synthesis technique, pure crystals of ZIF-8 with high BET (Brunauer, Emmett and Teller) specific surface area (SSA) can be obtained in water after only 5 s. Furthermore, 5 s sonication produced even smaller crystals (~0.08 µm). The type of technique applied for producing the ZIF-8 crystals did not have any significant impact on crystallinity, purity and yield. Crystal morphology and size were affected by the use of ultrasound and mixing, obtaining nanoparticles with a more spherical shape than in silent condition (no ultrasound and mixing). However, no specific trends were observed with varying frequency, calorimetric power and mixing speed. Ultrasound and mixing may have an effect on the nucleation step, causing the fast production of nucleation centres. Furthermore, the BET SSA increased with increasing mixing speed. With ultrasound, the BET SSA is between the values obtained under silent condition and with mixing. A competition between micromixing and shockwaves has been proposed when sonication is used for ZIF-8 production. The former increases the BET SSA, while the latter could be responsible for porosity damage, causing a decrease of the surface area.

Efficacy of face coverings in reducing transmission of COVID-19: Calculations based on models of droplet capture.

In the COVID-19 pandemic, among the more controversial issues is the use of masks and face coverings. Much of the concern boils down to the question-just how effective are face coverings? One means to address this question is to review our understanding of the physical mechanisms by which masks and coverings operate-steric interception, inertial impaction, diffusion, and electrostatic capture. We enquire as to what extent these can be used to predict the efficacy of coverings. We combine the predictions of the models of these mechanisms which exist in the filtration literature and compare the predictions with recent experiments and lattice Boltzmann simulations, and find reasonable agreement with the former and good agreement with the latter. Building on these results, we explore the parameter space for woven cotton fabrics to show that three-layered cloth masks can be constructed with comparable filtration performance to surgical masks under ideal conditions. Reusable cloth masks thus present an environmentally friendly alternative to surgical masks so long as the face seal is adequate enough to minimize leakage.

Design principles for broad-spectrum protein-crystal nucleants with nanoscale pits.

Growing high-quality crystals is a bottleneck in the determination of protein structures by x-ray diffraction. Experiments find that materials with a disordered pitted surface seed the growth of protein crystals. Here we report computer simulations of rapid crystal nucleation in nanoscale pits. Nucleation is rapid, as the crystal forms in pits that have filled with liquid via capillary condensation. Surprisingly, we find that pits whose surfaces are rough are better than pits with crystalline surfaces; the roughness prevents the growing crystal from trying to conform to the pit surface and becoming strained.