A gas cavity can reduce the hydrodynamic drag on a falling sphere in liquid to near zero by providing perfect slip conditions.

Despite significant recent progress, dense, time-resolved imaging of complex, non-stationary 3D flow velocities remains an elusive goal. In this work we tackle this problem by extending an established 2D method, Particle Imaging Velocimetry, to three dimensions by encoding depth into color. The encoding is achieved by illuminating the flow volume with a continuum of light planes (a "rainbow"), such that each depth corresponds to a specific wavelength of light. A diffractive component in the camera optics ensures that all planes are in focus simultaneously. With this setup, a single color camera is sufficient for tracking 3D trajectories of particles by combining 2D spatial and 1D color information. For reconstruction, we derive an image formation model for recovering stationary 3D particle positions. 3D velocity estimation is achieved with a variant of 3D optical flow that accounts for both physical constraints as well as the rainbow image formation model. We evaluate our method with both simulations and an experimental prototype setup.

In recent years, innovation in wearable health monitors has surged from significant 30 advances in flexible sensory arrays, wireless technologies, and scaled low-power electronics. Such 31 biometric monitoring devices are critical for continuous monitoring of body vitals and health 32 conditions as means of care for advanced personalized healthcare. Still, widespread deployment of 33 such devices are far more remote due to affordability (viz. complex materials and processes induced 34 higher price), low sensitivity, selectivity, recovery and disposability. Therefore, in addition to 35 functionality, accuracy, comfort and convenience, affordability and accessibility are critical need for 36 the wide adaptation of its benefits. Here we show an integration strategy to rationally design an ultra-37 low cost health monitoring device, a "Paper Watch", using recyclable household materials: non-38 functionalized papers. Its unusual simplicity in manufacturing and in daily use, gives it unprecedented 39

We demonstrate the viability of using four low-cost smartphone cameras to perform Tomographic PIV. We use colored shadows to imprint two or three different time-steps on the same image. The backlighting is accomplished with three sets of differently-colored pulsed LEDs. Each set of Red, Green & Blue LEDs is shone on a diffuser screen facing each of the cameras. We thereby record the RGB-colored shadows of opaque suspended particles, rather than the conventionally used scattered light. We subsequently separate the RGB color channels, to represent the separate times, with preprocessing to minimize noise and cross-talk. We use commercially available Tomo-PIV software for the calibration, 3-D particle reconstruction and particle-field correlations, to obtain all three velocity components in a volume. Acceleration estimations can be done thanks to the triple pulse illumination. Our test flow is a vortex ring produced by forcing flow through a circular orifice, using a flexible membrane, which is driven by a pressurized air pulse. Our system is compared to a commercial stereoscopic PIV system for error estimations. We believe this proof of concept experiment will make this technique available for education, industry and scientists for a fraction of the hardware cost needed for traditional Tomo-PIV.Flow visualization and quantitative velocity measurements are the foundations of experimental fluid mechanics. They have, with the other pillars of theory and numerical simulations, built up our understanding of the dynamics of complex or turbulent flows. Since the invention of the CCD sensor the advances in digital cameras and computational power have gone hand-in-hand as their electronic fabrication methods have taken a parallel track. This is particularly true in the recent advances in smartphone technology, where a camera and a computational brain have been integrated into a rapidly developing combined device and the economics of scale have allowed the addition of advanced features into these mass-produced camera-sensors, at minimal cost. Indeed as smartphones have become ubiquitous in the general population, they are equipped with high quality sensors such as gyroscopes, accelerometers, GPS and one or two CMOS camera sensors. These features allow people to communicate, record vast amounts of information and even monitor their health at a fraction of the cost of similar commercial scientific cameras and other sensors used in industry and research, thereby, becoming a valuable tool in everyone's daily life. Herein we demonstrate that the recent very high pixel-count of a few of these camera sensors can be combined together for measuring three-dimensional velocity fields.Particle Image Velocimetry (PIV) is the most powerful modern technique to measure extended velocity fields 1-4 . This relies on seeding the flow-volume with small tracer particles which are illuminated with pulsed light and digital cameras capture images of their displacement with time. The velocity field is subsequently extracted through image correlation...

Novel low-cost 3D-printed plug-and-play microfluidic devices have been developed for droplet generation and applications. By combining a commercial tubing with the printed channel design we can generate well-controlled droplets down to 50 μm.