Wettability characterizations are crucial to many disciplines, including dropwise condensation heat transfer, microfluidics, and self-cleaning materials. Droplet goniometry is a standard technique for such characterizations due to its relatively simple setup and execution. However, goniometry is severely limited when analyzing irregular droplets and multi-droplet systems, and alternative methods often require additional equipment, exhaustive scans, or non-physics-based modeling, hindering their effectiveness. In response, we created the reverse catch light method, which constructs physics-informed, three-dimensional digital twins of droplets from a single overhead image. We locate droplet contact lines and point light reflections on a real droplet surface, then iteratively solve the Young‒Laplace equation to generate candidate droplet surfaces whose unique reflections match those observed in our image. We experimentally validated this method with goniometry across varied droplet contact angles, volumes, liquid types, and substrates. Furthermore, we highlight new capabilities that are impractical with classical goniometry, such as constructing digital twins of irregularly shaped droplets or sliding droplets for hysteresis characterization. Finally, we demonstrate the ability to obtain rich, spatiotemporal statistical data from multi-droplet systems that would be impossible with classical goniometry. Our findings suggest that this methodology could be easily deployed for enhanced in situ diagnostics of otherwise difficult-to-analyze, realistic systems.

Flow boiling is an efficient heat transfer mechanism capable of dissipating high heat loads with minimal temperature variation, making it an ideal thermal management method. However, sudden shifts between flow regimes can disrupt thermal performance and system reliability, highlighting the need for accurate and low-latency real-time monitoring. Conventional optical imaging methods are limited by high computational demands and insufficient temporal resolution, making them inadequate for capturing transient flow behavior. To address this, we propose a real-time framework based on signals from neuromorphic sensors for flow regime classification. Neuromorphic sensors detect changes in brightness at individual pixels, which typically correspond to motion at edges, enabling fast and efficient detection without full-frame reconstruction and providing event-based information. We develop five classification models using both traditional image data and event-based data, demonstrating that models leveraging event data outperform frame-based approaches due to their sensitivity to dynamic flow features. Among these models, the event-based long short-term memory model provides the best balance between accuracy and speed, achieving 97.6% classification accuracy with a processing time of 0.28 ms. Our asynchronous processing pipeline supports continuous, low-latency predictions and delivers stable output through a majority voting mechanisms, enabling reliable real-time feedback for experimental control and intelligent thermal management.

Omniphobic surfaces have attracted considerable interest in recent years due to their various applications. Such surfaces conventionally require a fluorine-based surface chemistry with a low surface energy, which is achieved through surface modification using per- and polyfluoroalkyl substances (PFAS). However, PFAS, as emerging contaminants, pose serious health risks to humans and wildlife. The discovery of doubly reentrant texture has paved the way for designing fluorine-free omniphobic surfaces, but current methods for fabricating this unique texture involve complex processes and expensive equipment. In this work, we demonstrate that the simple and inexpensive digital light processing three-dimensional printing can be used to fabricate not only doubly reentrant but also triply reentrant micropillars. Our printed micropillars with doubly reentrant features display repellency towards liquids with a wide range of surface tensions after surface modification using a hydrocarbon silane. Water and ethanol droplets remain in the Cassie–Baxter state during the entire evaporation process, indicating the robust omniphobicity of our surface. Moreover, the printed micropillars with triply reentrant features exhibit omniphobicity even when the micropillars are composed of hydrophilic resin. Our simple method for achieving fluorine-free omniphobicity has the potential of facilitating the development of sustainable liquid-repellent surfaces and the mitigation of PFAS contamination.

Hydrogel particles are attracting increasing interest as tunable microscale platforms that combine precise architectures with diverse chemical, biological, and physical functionalities. Among fabrication strategies, droplet microfluidics has emerged as a powerful technology for producing monodisperse hydrogel particles with controllable size, composition, and internal structure via precise regulation of microscale fluid dynamics. This review first outlines the fundamental principles of droplet microfluidics, including chip fabrication, channel design, droplet generation dynamics, energy input modes, and fluidic compositions, which collectively underpin reliable particle production. We then highlight compatible hydrogel precursor systems, gelation methods, and functionalization strategies for engineering tailored hydrogel particles. The versatility of such particles is further emphasized, supporting applications in cell culture, 3D bioprinting, drug delivery, and diagnostics. Finally, we provide an outlook on future directions, including system parallelization, process automation, and artificial intelligence integration, anticipated to expand the scalability, functionality, and multidisciplinary impact of droplet-microfluidic hydrogel platforms.

The unique one-dimensional structure and outstanding optoelectronic properties of carbon nanotubes (CNTs) have motivated extensive research into their directed assembly. Although the droplet evaporation method offers a straightforward strategy for aligning CNTs, controlling the final deposited structure remains challenging due to the inherently high aspect ratio of CNTs. In this study, we prepared four substrates with distinct wettability and friction properties through surface modification. Time-resolved contact angle analysis was employed to monitor the evolution of the three-phase contact line and the evaporation kinetics of CNT droplets on these substrates. Combined with detailed microstructural characterization, we found that on hydrophobic, highly friction surfaces (NBE-modified silica), strong friction stabilizes the contact line during droplet drying. At the same time, rapid solvent evaporation induces droplet shrinkage, leading to a pronounced circumferential flow along the droplet periphery. This flow promotes the formation of long-range aligned CNT orientation bands with a width of ∼150 μm (orientation degree of 9.2°) after drying. These findings provide insights for the design and modification of substrates used in evaporation-driven oriented assembly of CNTs.

Electrocatalytic hydrogen evolution reaction (HER) is crucial for green hydrogen production and the transition toward low-carbon energy systems. However, the issues related to electrochemical gas bubbles, particularly at high current densities, have become a critical bottleneck for HER performance, resulting in active site isolation, increased ohmic resistance, and large concentration overpotential. Addressing these bubble-related limitations is therefore essential for advancing HER efficiency. This review aims to provide a comprehensive understanding of bubble manipulation strategies for enhancing HER by (1) exploring the fundamental principles governing bubble dynamics at electrode interfaces, (2) presenting the strategies to mitigate bubble-related issues at electrode interfaces, that is, passive strategies and active strategies, and (3) offering our insights into the challenges and opportunities for bubble dynamics in HER. By consolidating these projects, this review aims to advance the rational design of bubble management strategies and inspire innovative approaches for efficient hydrogen production.

Magnetic digital microfluidics offers a promising alternative to the dominant electrowetting-based digital microfluidics but faces significant challenges regarding system portability, sample contamination, and limited functionality. Here, we report a magneto-silicobotic system utilizing silicone oil–based ferrofluid droplets as inert microrobots for versatile manipulation of droplets and solid particles. The system combines a cost-effective and portable microcoil array with a millimeter-scale permanent magnet to generate localized magnetic fields for precise actuation. It achieves precise droplet manipulation with an average tracking error of 0.15 mm, stable operation over 360 cycles, and speeds up to 52 mm/s. It can transport droplets 50 times its volume, achieve maximum transport speeds of 35 mm/s, maintain long-term residual-free transport, and handle diverse liquids, including organic solvents and biological samples. We further design a ferrofluid-based pipette to perform droplet splitting and dispensing, thus completing all basic operations of digital microfluidics. Additionally, we extend the robot's capability to include the transport and automated assembly of solid particles using integrated visual feedback. We envision that this portable, additive-free platform will have a significant impact on point-of-care testing, miniaturized biochemical assays, and automated lab-on-a-chip systems.

Cavitation phenomena are widespread in nature and industrial applications. Researchers have conducted in-depth studies on the interaction of cavitation bubbles with a single boundary. However, when cavitation bubbles interact simultaneously with multiple boundaries, for example, a rigid wall and free surface, the process and mechanisms are still unclear. Here, experiments are carried out to study the dynamics of cavitation bubbles within a liquid layer. The results show that due to the combined effect of a rigid wall and free surface, the bubbles exhibit a significant downward migration in the liquid layer. Based on Kelvin impulse theory, we calculate the impulse experienced by the bubble and find a good consistency between the downward migration of the bubble and the impulse it experiences. By varying the initial position of the bubble in the liquid layer, we find that the confinement effect of the rigid wall significantly affects the bubble's collapse morphology, leading to different post-collapse phenomena of free surface motion.

Control of bubble motion is essential for improving efficiency and creating new functionalities in electrochemistry, heat transfer, and biomedical systems. Photoresponsive surfactants enable bubble manipulation by creating surface-tension gradients, inducing a “photo-Marangoni” flow under illumination, without the need for engineered substrates, by leveraging a reversible switch in molecular conformation. Although previous studies have demonstrated bubble manipulation using photo-responsive surfactants, a comprehensive understanding of how fluid behavior is affected by critical parameters, such as bubble size, illumination, photo-switching kinetics, concentration, and adsorption/desorption kinetics, remains elusive. Advances have been limited by the complex multiphysics processes involved, and by the fact that earth-bound experiments couple bubble photo-Marangoni dynamics with interference from buoyancy and photo-thermal convection. We elucidate the factors enabling fast photo-Marangoni-driven bubble motion, by performing microgravity experiments, enabled by a bespoke photo-surfactant, complemented by a detailed modeling framework. We identify an optimal bubble size for migration (radius ~1 mm), since smaller and larger bubbles incur weaker photo-Marangoni stresses and larger drag, respectively. Surfactants that switch rapidly under illumination drive fast migration, provided their reverse switch (in darkness) is 10–100× slower. These foundational results enable the synthesis of next-generation photo-surfactants and photo-Marangoni manipulation across multiphase fluid systems.

Electrowetting-on-dielectric (EWOD) enables electrical modulation of liquid contact angle and is widely used for droplet actuation; however, its reliance on bulky high-voltage power supplies limits portability. Triboelectric nanogenerators (TENGs) provide a lightweight, mechanically driven alternative, yet existing EWOD–TENG systems still rely on electronic controllers or rapid manual actions. Here, we present a hand-powered and mechanically programmable EWOD platform that integrates a contact-separation TENG (CS-TENG) with a mechanically encoded punch-card switch array, both driven by a single hand-crank mechanism. Hand cranking simultaneously generates high voltage for EWOD actuation and advances a punch-card tape to sequentially trigger electrode switching according to predefined punch-hole patterns. Unlike conventional voltage sources, the CS-TENG delivers a constant-charge output per cycle, leading to distinct EWOD behavior. An EWOD–TENG model with trapped charge elucidates key phenomena, including bias-dependent asymmetric EWOD arising from dielectric charge trapping and stepwise voltage attenuation caused by capacitive EWOD loading during sequential switching. The punch-card switch array converts physical hole patterns into time-synchronized electrode activation, enabling programmable droplet manipulation without electronic controllers. The resulting platform executes predefined droplet operations using only a hand crank as the sole energy and control input, achieving autonomous, portable, and robust droplet control for field-deployable microfluidic systems.