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We explore the relationship between a machine-learned structural quantity (softness) and excess entropy in simulations of supercooled liquids. Excess entropy is known to scale well the dynamical properties of liquids, but this quasi-universal scaling is known to breakdown in supercooled and glassy regimes. Using numerical simulations, we test whether a local form of the excess entropy can lead to predictions similar to those made by softness, such as the strong correlation with particles’ tendency to rearrange. In addition, we explore leveraging softness to compute excess entropy in the traditional fashion over softness groupings. Our results show that the excess entropy computed over softness-binned groupings is correlated with activation barriers to rearrangement.

 

Flow pathlengths non-monotonically control swimmer dispersion and provide optimal transport strategies in time-periodic flows. 

In the midst of the COVID-19 pandemic, many live musical activities had to be postponed and even canceled to protect musicians and the audience. Orchestral ensembles face a particular challenge of contamination, because they are personally heavy and instrumentally diverse. A chief concern is whether wind instruments are vectors of contamination through aerosol dispersion. This study, made possible by the participation of members of The Philadelphia Orchestra, brings insight into the modes of production and early life of aerosols of human origin emitted by wind instruments. We find that these instruments produce aerosol levels that are comparable to normal speech in quantity and size distribution. However, the exit jet flow speeds are much lower than violent expiratory events (coughing and sneezing). For most wind instruments, the flow decays to background indoor-air levels at approximately 2 m away from the instrument's opening. Long range aerosol dispersion is, thus, via ambient air currents. 

Mud is a suspension of fine-grained particles (sand, silt, and clay) in water. The interaction of clay minerals in mud gives rise to complex rheological behaviors, such as yield stress, thixotropy, and viscoelasticity. Here, we experimentally examine the flow behaviors of kaolinite clay suspensions, a model mud, using steady shear rheometry. The flow curves exhibit both yield stress and rheological hysteresis behaviors for various kaolinite volume fractions (ϕk). Further understanding of these behaviors requires fitting to existing constitutive models, which is challenging due to numerous fitting parameters. To this end, we employ a Bayesian inference method, Markov chain Monte Carlo, to fit the experimental flow curves to a microstructural viscoelastic model. The method allows us to estimate the rheological properties of the clay suspensions, such as viscosity, yield stress, and relaxation time scales. The comparison of the inherent relaxation time scales suggests that kaolinite clay suspensions are strongly viscoelastic and weakly thixotropic at relatively low ϕk, while being almost inelastic and purely thixotropic at high ϕk. Overall, our results provide a framework for predictive model fitting to elucidate the rheological behaviors of natural materials and other structured fluids.

 

Numerous natural systems depend on the sedimentation of passive particles in the presence of swimming microorganisms. Here, we investigate the dynamics of the sedimentation of spherical colloids at various E. coli concentrations within the dilute regime. Results show the appearance of two sedimentation fronts: a spherical particle front and the bacteria front. We find that the bacteria front behave diffusive at short times, whereas at long times it decays linearly. The sedimentation speed of passive particles decays at a constant speed and decreases as bacteria concentration (ϕb) is increased. As ϕb is increased further, the sedimentation speed becomes independent of ϕb. The timescales of the bacteria front are associated with the particle settling speeds. Remarkably, all experiments collapse onto a single master line by using the bacteria front timescale. A phenomenological model is proposed that captures the sedimentation of passive particles in active fluids.

 

Understanding mixing and transport of passive scalars in active fluids is important to many natural (e.g., algal blooms) and industrial (e.g., biofuel, vaccine production) processes. Here, we study the mixing of a passive scalar (dye) in dilute suspensions of swimmingEscherichia coliin experiments using a two-dimensional (2D) time-periodic flow and in a simple simulation. Results show that the presence of bacteria hinders large-scale transport and reduces overall mixing rate. Stretching fields, calculated from experimentally measured velocity fields, show that bacterial activity attenuates fluid stretching and lowers flow chaoticity. Simulations suggest that this attenuation may be attributed to a transient accumulation of bacteria along regions of high stretching. Spatial power spectra and correlation functions of dye-concentration fields show that the transport of scalar variance across scales is also hindered by bacterial activity, resulting in an increase in average size and lifetime of structures. On the other hand, at small scales, activity seems to enhance local mixing. One piece of evidence is that the probability distribution of the spatial concentration gradients is nearly symmetric with a vanishing skewness. Overall, our results show that the coupling between activity and flow can lead to nontrivial effects on mixing and transport.

 

To address the global water shortage crisis, one of the promising solutions is to collect freshwater from the environmental resources such as fog. However, the efficiency of conventional fog collectors remains low due to the viscous drag of fog-laden wind deflected around the collecting surface. Here, we show that the three-dimensional and centimetrickirigamistructures can control the wind flow, forming quasi-stable counter-rotating vortices. The vortices regulate the trajectories of incoming fog clusters and eject extensive droplets to the substrate. As the characteristic structural length is increased to the size of vortices, we greatly reduce the dependence of fog collection on the structural delicacy. Together with gravity-directed gathering by the folds, thekirigamifog collector yields a collection efficiency of 16.1% at a low wind speed of 0.8 m/s and is robust against surface characteristics. The collection efficiency is maintained even on a 1 m²collector in an outdoor setting.

 

Sedimentation in active fluids has come into focus due to the ubiquity of swimming micro-organisms in natural and industrial processes. Here, we investigate sedimentation dynamics of passive particles in a fluid as a function of bacteria E. coli concentration. Results show that the presence of swimming bacteria significantly reduces the speed of the sedimentation front even in the dilute regime, in which the sedimentation speed is expected to be independent of particle concentration. Furthermore, bacteria increase the dispersion of the passive particles, which determines the width of the sedimentation front. For short times, particle sedimentation speed has a linear dependence on bacterial concentration. Mean square displacement data shows, however, that bacterial activity decays over long experimental (sedimentation) times. An advection-diffusion equation coupled to bacteria population dynamics seems to capture concentration profiles relatively well. A single parameter, the ratio of single particle speed to the bacteria flow speed can be used to predict front sedimentation speed.