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 centimetric kirigami structures 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, the kirigami fog 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 m2 collector in an outdoor setting.

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 swimming Escherichia coli in 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.

Numerous natural systems depend on the sedimentation of passive particles in presence of swimming microorganisms. Here, we investigate the dynamics of the sedimentation of spherical colloids at various E. coli concentration 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 decays linearly. The sedimentation speed of passive particles decays at a constant speed and decreases as bacteria concentration is increased. As bacteria concentration is increased further, the sedimentation speed becomes independent of bacteria concentration. The timescales of the bacteria front is 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.

Using holographic particle tracking, we report the three-dimensional flow structure organizing the viscoelastic instability in cross-channel flow.

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 ([Formula: see text]). 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 [Formula: see text], while being almost inelastic and purely thixotropic at high [Formula: see text]. Overall, our results provide a framework for predictive model fitting to elucidate the rheological behaviors of natural materials and other structured fluids.