Droplets slip and bounce on superhydrophobic surfaces, enabling remarkable functions in biology and technology. These surfaces often contain microscopic irregularities in surface texture and chemical composition, which may affect or even govern macroscopic wetting phenomena. However, effective ways to quantify and map microscopic variations of wettability are still missing, because existing contact angle and force-based methods lack sensitivity and spatial resolution. Here, we introduce wetting maps that visualize local variations in wetting through droplet adhesion forces, which correlate with wettability. We develop scanning droplet adhesion microscopy, a technique to obtain wetting maps with spatial resolution down to 10 µm and three orders of magnitude better force sensitivity than current tensiometers. The microscope allows characterization of challenging non-flat surfaces, like the butterfly wing, previously difficult to characterize by contact angle method due to obscured view. Furthermore, the technique reveals wetting heterogeneity of micropillared model surfaces previously assumed to be uniform.

The origin of the idea of moving objects by acoustic vibration can be traced back to 1787, when Ernst Chladni reported the first detailed studies on the aggregation of sand onto nodal lines of a vibrating plate. Since then and to this date, the prevailing view has been that the particle motion out of nodal lines is random, implying uncontrollability. But how random really is the out-of-nodal-lines motion on a Chladni plate? Here we show that the motion is sufficiently regular to be statistically modelled, predicted and controlled. By playing carefully selected musical notes, we can control the position of multiple objects simultaneously and independently using a single acoustic actuator. Our method allows independent trajectory following, pattern transformation and sorting of multiple miniature objects in a wide range of materials, including electronic components, water droplets loaded on solid carriers, plant seeds, candy balls and metal parts.

Castable elastomers have been used to fabricate soft robotic devices and it has been shown that the technique scales well from prototyping to mass manufacturing. However, similarly scalable techniques for integrating strain or curvature sensors into such devices are still lacking. In this paper, we show that screen-printed silver conductors serve well as curvature sensors for soft robotic devices. The sensors are produced onto elastomer substrates in a single printing step and integrated into soft pneumatic actuators. We characterized the resistance-curvature relationship of the sensors, which allows the curvature of the actuators to be estimated from the sensor measurements. Hysteresis was observed, which does limit the absolute accuracy of the sensors. However, temperature characterizations showed that the sensor measurements are not significantly affected by temperature fluctuations during normal operation. Dynamic experiments showed that the bandwidth of the sensors is larger than the bandwidth of the actuators. We experimentally validated that these sensors can be used to detect whether the motion of an actuator has been blocked, clearing the way toward simple-to-fabricate soft robots that react to their surroundings. Finally, we demonstrate a three-fingered soft robotic gripper with integrated sensors. We conclude that screen-printing is a promising way to integrate curvature sensors into soft robots.

In biomedical sciences, there is demand for electronic skins with highly sensitive tactile sensors, having applications in patient monitoring, human–machine interfaces, and on‐body sensors. In clinical applications, it would be especially beneficial if the sensors would be disposable. Here, an all plant‐material‐based biodegradable capacitive tactile pressure sensor for disposable electronic skins is reported. Silver‐nanowire‐coated leaf skeletons are used as breathable and flexible electrodes while freeze‐dried rose petals are used as the dielectric layer. The leaf skeleton electrodes have a rough fractal‐like architecture, which provides good adhesion to the silver nanowires and maintains interconnections between the silver nanowires when the electrodes are bent. The electrodes display low constant resistance up to curvature of 800 m⁻¹. The rose petal dielectric layer has a multiscale 3D cell wall microstructure, which compresses elastically when subjected to pressure. The fabricated sensor can respond to pressures ranging from 0.007 to at least 60 kPa, with a maximum sensitivity of ≈0.08 kPa⁻¹. The signal is stable for at least 5000 pressure cycles, after an initial break‐in period. Owing to the all biomaterial constituents, the sensor is biodegradable under aqueous conditions. The sensor is successfully applied as an e‐skin in touch sensing and gesture monitoring.

This paper reports an in-depth study of a hybrid microassembly technique that combines a robotic micromanipulator and a water droplet self-alignment, which greatly improves the performance of robotic microassembly. The method is experimentally studied on a custom-made microrobotic test platform adapted for the experiments. Four important measures of the microassembly technique are investigated--yield, capability, accuracy, and speed. Yield is studied by a large number of tests with random process parameters and statistical-modeling methods. Accuracy is measured by studying the final assembly results under a scanning electron microscope (SEM). Capability is assessed by testing parts of various sizes and shapes. Using a high-speed camera, the duration and trajectories of droplet self-alignment of the hybrid assembly process are studied. The experimental results indicate that such a hybrid assembly technique has very low requirements on the precision, which is comparable with the dimensions of the micropart, of the handling robot while being able to achieve micrometer precision. Moreover, successful assembly can be easily achieved with part sizes that range from 50 to 300 m. The experiments also show that parts of different sizes can be reliably assembled together using the proposed method.

Grasping is one of the key tasks for robots. Gripping fragile and complex three-dimensional (3D) objects without applying excessive contact forces has been a challenge for traditional rigid robot grippers. To solve this challenge, soft robotic grippers have been recently proposed for applying small forces and for conforming to complex 3D object shapes passively and easily. However, rigid grippers are still able to exert larger forces, necessary for picking heavy objects. Therefore, in this study, we propose a magnetically switchable soft suction gripper (diameter: 20 mm) to be able to apply both small and large forces. The suction gripper is in its soft state during approach and attachment while it is switched to its rigid state during picking. Such stiffness switching is enabled by filling the soft suction cup with a magnetorheological fluid (MR fluid), which is switched between low-viscosity (soft) and high-viscosity (rigid) states using a strong magnetic field. We characterized the gripper by measuring the force required to pull the gripper from a smooth glass surface. The force was up to 90% larger when the magnetic field was applied (7.1 N vs. 3.8 N). We also demonstrated picking of curved, rough, and wet 3D objects, and thin and delicate films. The proposed stiffness-switchable gripper can also carry heavy objects and still be delicate while handling fragile objects, which is very beneficial for future potential industrial part pick-and-place applications.