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Bacteria often exhibit upstream swimming, which can cause the contamination of biomedical devices and the infection of organs including the urethra or lungs. This process, called rheotaxis, has been studied extensively in Newtonian fluids. However, most microorganisms thrive in non-Newtonian fluids that contain suspended polymers such as mucus and biofilms. Here, we investigate the rheotatic behavior of E. coli near walls in non-Newtonian fluids. Our experiments demonstrate that bacterial upstream swimming is enhanced by an order of magnitude in shear-thinning polymeric fluids relative to Newtonian fluids. This result is explained by direct numerical simulations, revealing a torque that promotes the alignment of bacteria against the flow. From this analysis, we develop a theoretical model that accurately describes experimental rheotatic data in both Newtonian and shear-thinning fluids.

Microorganisms are ubiquitous in nature and technology. They inhabit diverse environments ranging from small river tributaries and lakes to oceans, as well as wastewater treatment plants and food manufacturing. In many of these environments, microorganisms coexist with settling particles. Here, we investigate the effects of microbial activity (swimming \textit{E. coli}) on the settling dynamics of passive colloidal particles using particle tracking methods. Our results reveal the existence of two distinct regimes in the correlation length scale ($L_u$) and the effective diffusivity of the colloidal particles ($D_{e\!f\!f}$), with increasing bacterial concentration ($\phi_b$). At low $\phi_b$, the parameters $L_u$ and $D_{e\!f\!f}$ monotonically increases with increasing $\phi_b$. Beyond a critical $\phi_b$, second regime is found in which both $D_{e\!f\!f}$ and $L_u$ are independent of $\phi_b$. We demonstrate that the transition between these regimes is characterized by the emergence of bioconvection. We use experimentally-measured particle-scale quantities ($L_u$, $D_{e\!f\!f}$) to predict the critical bacterial concentration for the diffusion-bioconvection transition.

Soft robots have a myriad of potentials because of their intrinsically compliant bodies, enabling safe interactions with humans and adaptability to unpredictable environments. However, most of them have limited actuation speeds, require complex control systems, and lack sensing capabilities. To address these challenges, here we geometrically design a class of metacaps whose rich nonlinear mechanical behaviors can be harnessed to create soft robots with unprecedented functionalities. Specifically, we demonstrate a sensor-less metacap gripper that can grasp objects in 3.75 ms upon physical contact and a pneumatically actuated gripper with tunable actuation behaviors that have little dependence on the rate of input. Both grippers can be readily integrated into a robotic platform for practical applications. Furthermore, we demonstrate that the metacap enables propelling of a swimming robot, exhibiting amplified swimming speed as well as untethered, electronics-free swimming with tunable speeds. Our metacaps provide new strategies to design the next-generation soft robots that require high transient output energy and are capable of autonomous and electronics-free maneuvering., Comment: 19 pages, 5 figures

We present a solvable model inspired by dimensional analysis for the time-dependent spreading of droplets that partially wet a substrate, where the spreading eventually stops and the contact angle reaches a nonzero equilibrium value. We separately consider small droplets driven by capillarity and large droplets driven by gravity. To explore both regimes, we first measure the equilibrium radius versus a comprehensive range of droplet volumes for four household fluids, and we compare the results with predictions based on minimizing the sum of gravitational and interfacial energies. The agreement is good, and gives a reliable measurement of an equilibrium contact angle that is consistent in both small and large droplet regimes. Next we use energy considerations to develop equations of motion for the time dependence of the spreading, in both regimes, where the driving forces are balanced against viscous drag in the bulk of the droplet and by friction at the moving contact line. Our approach leads to explicit prediction of the functional form of the spreading dynamics. It successfully describes prior data for a small capillary-driven droplet, and it fits well to new data we obtain for large gravity-driven droplets with a wide range of volumes.

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 ($\phi_b$) is increased. As $\phi_b$ is increased further, the sedimentation speed becomes independent of $\phi_b$. 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.

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., Comment: Soft Matter, (2021). arXiv admin note: substantial text overlap with arXiv:1710.04068