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Nanocellulose‐based strain sensor (NBSS) have been a subject of growing interest for wearable electronics. However, these electronic devices are susceptible to damage when they come into contact with water and organic contaminants. Recently, researchers have developed a superhydrophobic NBSS. Unfortunately, it does not treat organic pollutants in water when used in an underwater environment. In this paper, a new solution: a superhydrophobic photocatalytic self‐cleaning NBSS created through scrape coating and dip coating methods is proposed. This new method shows outstanding self‐cleaning capabilities against water and organic contaminants due to the synergistic effects of the superhydrophobicity and photocatalysis of MnO2 nanoparticles. Furthermore, the superhydrophobic photocatalytic self‐cleaning NBSS has an exceptional response time of 0.66 s, a fast recovery time of 0.81 s, a sensitivity ≈66.53 at a strain of 0.5%. It is expect that the superhydrophobic photocatalytic self‐cleaning NBSS can monitor human movements, including finger twists, wrist movements, elbow bends, and knee movements. Not only is the fabrication method cost‐effective and scalable, but the new NBSS holds great promise in a wide range of fields, including human‐machine interactive systems, smart systems, and human‐body monitoring. Overall, the study provides significant guidance for future designs for wearable strain sensors. A superhydrophobic photocatalytic self‐cleaning nanocellulose‐based strain sensors (NBSS) is created through scrape coating and dip coating methods. Not only is this fabrication method cost‐effective and scalable, but the new NBSS holds great promise in a wide range of fields, including human‐machine interactive systems, smart systems. Overall, this research provides significant guidance for future designs for wearable strain sensors.

Evaporating liquid droplets are omnipresent in nature and technology, such as in inkjet printing, coating, deposition of materials, medical diagnostics, agriculture, the food industry, cosmetics, or spills of liquids. Whereas the evaporation of pure liquids, liquids with dispersed particles, or even liquid mixtures has intensively been studied over the past two decades, the evaporation of ternary mixtures of liquids with different volatilities and mutual solubilities has not yet been explored. Here we show that the evaporation of such ternary mixtures can trigger a phase transition and the nucleation of microdroplets of one of the components of the mixture. As a model system, we pick a sessile Ouzo droplet (as known from daily life—a transparent mixture of water, ethanol, and anise oil) and reveal and theoretically explain its four life phases: In phase I, the spherical cap-shaped droplet remains transparent while the more volatile ethanol is evaporating, preferentially at the rim of the drop because of the singularity there. This leads to a local ethanol concentration reduction and correspondingly to oil droplet nucleation there. This is the beginning of phase II, in which oil microdroplets quickly nucleate in the whole drop, leading to its milky color that typifies the so-called “Ouzo effect.” Once all ethanol has evaporated, the drop, which now has a characteristic nonspherical cap shape, has become clear again, with a water drop sitting on an oil ring (phase III), finalizing the phase inversion. Finally, in phase IV, all water has evaporated, leaving behind a tiny spherical cap-shaped oil drop.

In particle image velocimetry (PIV), overexposure is particularly common in regions with high illumination. In particular, strong scattering or background reflection at the liquid–gas interface will make the overexposure phenomenon more obvious, resulting in local pixel saturation, which will significantly reduce the particle image quality, and thus reduce the particle recognition rate and the accuracy of velocity field estimation. This study addresses the overexposure challenges in particle image velocimetry applications, mainly to address the challenge that the velocity field cannot be measured due to the difficulty in effectively detecting particles in the exposed area. In order to address the challenge of overexposure, this paper does not use traditional frame-based high-speed cameras, but instead proposes a particle image velocimetry algorithm based on adaptive integral spike camera data using a neuromorphic vision sensor (NVS). Specifically, by performing target-background segmentation on high-frequency digital spike signals, the method suppresses high illumination background regions and thus effectively mitigates overexposure. Then the spike data are further adaptively integrated based on both regional background illumination characteristics and the spike frequency features of particles with varying velocities, resulting in high signal-to-noise ratio (SNR) reconstructed particle images. Flow field computation is subsequently conducted using the reconstructed particle images, with validation through both simulation and experiment. In simulation, in the overexposed area, the average flow velocity estimation error of frame-based cameras is 8.594 times that of spike-based cameras. In the experiments, the spike camera successfully captured continuous high-density particle trajectories, yielding measurable and continuous velocity fields. Experimental results demonstrate that the proposed particle image velocimetry algorithm based on the adaptive integration of the spike camera effectively addresses overexposure challenges caused by high illumination of the liquid–gas interface in flow field measurements.

The Greek aperitif Ouzo is not only famous for its specific anise-flavoured taste, but also for its ability to turn from a transparent miscible liquid to a milky-white coloured emulsion when water is added. Recently, it has been shown that this so-called Ouzo effect, i.e. the spontaneous emulsification of oil microdroplets, can also be triggered by the preferential evaporation of ethanol in an evaporating sessile Ouzo drop, leading to an amazingly rich drying process with multiple phase transitions (Tan et al., Proc. Natl Acad. Sci. USA, vol. 113 (31), 2016, pp. 8642–8647). Due to the enhanced evaporation near the contact line, the nucleation of oil droplets starts at the rim which results in an oil ring encircling the drop. Furthermore, the oil droplets are advected through the Ouzo drop by a fast solutal Marangoni flow. In this article, we investigate the evaporation of mixture droplets in more detail, by successively increasing the mixture complexity from pure water over a binary water–ethanol mixture to the ternary Ouzo mixture (water, ethanol and anise oil). In particular, axisymmetric and full three-dimensional finite element method simulations have been performed on these droplets to discuss thermal effects and the complicated flow in the droplet driven by an interplay of preferential evaporation, evaporative cooling and solutal and thermal Marangoni flow. By using image analysis techniques and micro-particle-image-velocimetry measurements, we are able to compare the numerically predicted volume evolutions and velocity fields with experimental data. The Ouzo droplet is furthermore investigated by confocal microscopy. It is shown that the oil ring predominantly emerges due to coalescence.

Superhydrophobic surfaces offer notable advantages, including markedly low water affinity and reduced ice adhesion strength. Nevertheless, their practical utility is impeded by their limited durability and vulnerability to failure in cold and humid environments. In this study, a novel approach for devising an electro‐photothermal superhydrophobic (EPS) nanocomposite coating is presented. The findings indicate that the EPS nanocomposite coating exhibits both physical and chemical self‐cleaning attributes, showcasing a synergistic interplay of superhydrophobicity, electrothermal, and photothermal characteristics. The superhydrophobic coating delays icing about four times longer than the original coating. At ambient temperatures of −20 °C, the coating stacked with an electro‐ and photo‐thermal performance de‐icing layer reduces the de‐icing time by about 5 times more than the purely photo‐thermal performance de‐icing time, and reduces the de‐icing time by about 4 times more than the purely electro‐thermal de‐icing time. Furthermore, the EPS surface demonstrates the capability to sustain temperatures above 0 °C through the photothermal effect on sunny days, utilizing both the electrothermal and photothermal effects on cloudy days, and relying on the electrothermal effect during cold nights. The research introduces a novel method for fabricating functional materials, pertinent to practical anti‐icing and de‐icing applications. The EPS coating is specifically engineered to execute anti‐icing and de‐icing functions, employing both solar thermal and electrical methodologies. This dual‐pronged functionality underscores the EPS coating's proficiency in utilizing solar energy during the daytime and electrical energy during nighttime hours, all geared towards the objectives of anti‐icing and de‐icing.

3D-printing (3DP) technology has been developing rapidly. However, limited studies on the contribution of 3DP technology, especially multimaterial 3DP technology, to droplet-microfluidics have been reported. In this paper, multimaterial 3D-printed devices for the pneumatic control of emulsion generation have been reported. A 3D coaxial flexible channel with other rigid structures has been designed and printed monolithically. Numerical and experimental studies have demonstrated that this flexible channel can be excited by the air pressure and then deform in a controllable way, which can provide the active control of droplet generation. Furthermore, a novel modular microfluidic device for double emulsion generation has been designed and fabricated, which consists of three modules: function module, T-junction module, and co-flow module. The function module can be replaced by (1) Single-inlet module, (2) Pneumatic Control Unit (PCU) module and (3) Dual-inlet module. Different modules can be easily assembled for different double emulsion production. By using the PCU module, double emulsions with different number of inner droplets have been successfully produced without complicated operation of flow rates of different phases. By using single and dual inlet module, various double emulsions with different number of encapsulated droplets or encapsulated droplets with different compositions have been successfully produced, respectively.

AbstractIn this study the effects of the actuation waveforms on the droplet generation in a drop-on-demand inkjet printing are studied systematically by numerical simulations. Two different types of waveforms, namely the unipolar and bipolar actuations, are investigated for three fluids with different physical properties. We focus on two key parameters, which are the dwell time and the velocity amplitude. For the unipolar driving, the ejection velocity and the ejected liquid volume are both increased as the velocity amplitude becomes larger. The dwell time only has minor effects on both the ejection velocity and the ejected liquid volume. The ejection velocity decreases significantly for large liquid viscosity, while the influences of viscosity on the ejected liquid volume are much weaker. Four different droplet morphologies and the corresponding parameter ranges are identified. The droplet radius can be successfully reduced to about 40% of the nozzle exit radius. For the bipolar waveforms, same droplet morphologies are observed but with shifted boundaries in the phase space. The minimal radius of stable droplet produced by the bipolar waveforms is even smaller compared to the unipolar ones.Graphic abstract

To address the increasing demand for miniaturization and integration in artificial satellites, the development of foldable and efficient deployable structures is crucial. This study presents a novel, intelligent variable structure that leverages NiTi shape memory alloy (SMA) to achieve an impressive deployable/foldable ratio exceeding eightfold. The structure’s extension and contraction can be precisely controlled through temperature regulation, providing significant adaptability. A key innovation of this design is the joint-driving mechanism, which uses multiple SMA corrugated plates to convert the material’s strain into rotational movement at the structure’s joints. Through optimization using the Optimal Latin Hypercube and Multi-Island Genetic Algorithm methods, the performance of a single SMA corrugated plate was significantly enhanced, resulting in improved torque output and rotation capability. Incorporating this optimized plate into the joint-driving mechanism enables the intelligent structure to achieve a maximum deployable/foldable ratio of 8.96 and a deployable angle of 20.62°. Furthermore, motion simulations allowed us to optimize the number of SMA corrugated plates, confirming the system’s ability to transmit significant deformation from the driving element to the entire structure. The numerical validation of this intelligent variable structure demonstrates its exceptional deployable/foldable ratio, highlighting its promising potential for various engineering applications.

Particle Image Velocimetry (PIV) is essential in experimental fluid mechanics, providing nonintrusive flow field measurements. Among the recent advances in PIV algorithms, deep-learning-based optical flow estimation is distinguished by its high spatial and temporal resolution, as well as remarkable efficiency, especially RAFT-PIV, which is based on Recurrent All-Pairs Field Transforms (RAFT). However, RAFT-PIV is extremely susceptible to experimental conditions characterized by low signal-to-noise ratios (SNR), leading to unacceptable errors. This study proposes PIV-RAFT-EN, an enhanced RAFT-based algorithm integrating image denoising, enhancement, and optical flow estimation via a Multi-Task Convolutional Neural Network (MTCNN). Evaluations on synthetic and real-world low-SNR data demonstrate its superior accuracy and efficiency. PIV-RAFT-EN offers a reliable solution for precise PIV measurements in challenging environments, including practical applications like vehicle water entry.

Mobile microrobots with shape morphing capability show great advantages for conducting tasks in complex environments. Combination of magnetically driven locomotion and stimuli‐responsive shape morphing is an effective strategy to realize these microrobots. However, most existing microrobots fabricated by the combination strategy are of low locomotion efficiency due to the limited amount of magnetic material loaded. Herein, a novel scheme for coating the magnetic nanoparticles (NPs) on the surface of microrobot is proposed to increase the magnetic material loading amount. Theoretical analyses demonstrate that, below a critical size at microscale, surface coating NPs can load more magnetic material than embedding NPs into the volume due to the high surface area‐to‐volume ratio. Microrobots with both shape morphing and enhanced magnetically driven locomotion are fabricated by coating magnetic NPs on the surface of stimuli‐responsive hydrogel microstructures. It is experimentally demonstrated that surface coating ensures that the microstructure has not only an efficient locomotion but also an excellent deformability. A four‐claw microgripper is fabricated, which is smaller and has higher magnetically driven locomotion speed than the most existing shape morphing microrobots. This microgripper demonstrating carrying and delivery capabilities is of immediate interest to microobject manipulation and minimally invasive surgery. Herein, surface coating structure is proposed to increase the magnetic material loading amount at microscale. Microrobots with both shape morphing and enhanced magnetically driven locomotion are fabricated by coating magnetic nanoparticles on the surface of stimuli‐responsive hydrogel microstructures. The magnetic nanoparticles coating ensures that the microstructure has not only an efficient locomotion but also an excellent deformability.