Droplet最新文献

Front Cover: The cover image is based on the Research Article DropletMask: Leveraging visual data for droplet impact analysis by Zhao et al.

Cover description: Capturing the dynamic movements of droplet impacts is critical in thermal science and applications involving droplets. We propose a framework that leverages machine learning-assisted computer vision tools that quantitatively analyze their impacts. The interconnected network on the image background represents digital droplets, enabling precise measurements of the spatiotemporal data involving droplet movements, sizes, and impact forces on various surfaces. (DOI: 10.1002/dro2.137)

Inside Back Cover: The cover image is based on the Research Article Electro-coalescence of heterogeneous paired-droplets under AC electric field by Tao et al.

Cover description: Electro-coalescence of heterogeneous paired-droplets is achieved within milliseconds under AC electric fields on a lab-on-a-chip platform. The physical mechanisms are examined by parameters such as conductivity, surface tension, non-Newtonian properties. This technique could be applied to the droplet-based chemical reaction at microscale, including the efficient and additive-free fabrication of hydrogel microspheres. (DOI: 10.1002/dro2.145)

Inside Front Cover: The cover image is based on the Research Article A facile method to fabricate cell-laden hydrogel microparticles of tunable sizes using thermal inkjet bioprinting by Suntornnond et al.

Cover description: We demonstrate a novel approach for fabricating hydrogel microparticles (HMPs) using thermal inkjet-based bioprinting. The technique enables precise control over HMP size, porosity, and modularity, with potential applications in tissue engineering and regenerative medicine. Cell-laden HMPs of tunable sizes can be fabricated by adjusting surfactant concentration and jetting volume, highlighting their versatility for advanced biomedical applications. (DOI: 10.1002/dro2.144)

Back Cover: The cover image is based on the Research Article Programmable curvilinear self-propelling of droplets without preset channels by Feng et al.

Cover description: We propose a programmable curvilinear self-propelling strategy for droplets based on the collaboration of curvilinear wetting gradient and the Leidenfrost effect. This design achieves a well-controlled manner in motion trajectory, as well as high velocity and long distance of droplet transport independent on the pre-set channel. (DOI: 10.1002/dro2.138)

Aerodynamic breakup refers to the process where large droplets are fragmented into small droplets by the aerodynamic force in airflow, which plays a vital role in fluid atomization and spray applications. Previous research has primarily concentrated on the aerodynamic breakup of single-component droplets, but investigations into the breakup of emulsion droplets are limited. This study experimentally investigated the aerodynamic breakup of water-in-oil emulsions in airflow, utilizing high-speed photography to observe the breakup process and digital in-line holography to measure fragment sizes. Comparative analyses between emulsion droplets and single-component droplets are conducted to examine the breakup morphology, breakup regime, deformation characteristics, and fragment size distributions. The emulsion droplets exhibit higher apparent viscosity and shorter stretching lengths of the bag film and peripheral rim due to the presence of a dispersed phase. The breakup regime transitions of emulsions are modeled by integrating the viscosity model of emulsions and the transition model of the pure fluid. The fragment sizes of emulsion droplets are larger due to the shorter lengths of the bag film and peripheral rim.

Controllable droplet coalescence exhibits unique advantages and intriguing prospect in chemical synthesis and biological engineering. Current researches focusing on the droplets of the same physics are, however, limited in terms of the interaction between different reactants. In this work, the electro-coalescence of heterogeneous paired-droplets is investigated in a microfluidic chip controlled by an AC electric field. The characteristics of merging dynamics are analyzed under different electric conditions and fluid properties, and an on-chip cross-linking reaction is conducted to enable the instantaneous production of hydrogel microspheres. We find that the coalescence of heterogeneous paired-droplets expands the range of start positions and prolongs the merging time compared to homogeneous paired-droplets. The evolution process of interfaces is accelerated with the increasing voltage, which contributes to the mixing of diverse components. Different electrical conductivities lead to distinct internal mechanisms within droplets. The voltage across the droplet is reduced with the increasing conductivity, while the enhanced attraction between free charges plays a complimentary role in interface instability. Lowering the surface tension reduced the required electric conditions for coalescence. Endowed with the non-Newtonian property, the droplet presents a non-linear relationship in the coalescence region, triggering coalescence with filaments at low voltages and showcasing superior performance at high frequencies. Based on above findings, we successfully produce alginate hydrogel microspheres with a wide range of concentrations in high monodispersity, achieving a clean fabrication of pure hydrogel without any additives and no need for subsequent cleaning. These results reveal the electro-hydrodynamics of heterogeneous paired-droplets, promoting the development of droplet coalescence in chemical and material science.

Machine learning-assisted computer vision represents a state-of-the-art technique for extracting meaningful features from visual data autonomously. This approach facilitates the quantitative analysis of images, enabling object detection and tracking. In this study, we utilize advanced computer vision to precisely identify droplet motions and quantify their impact forces with spatiotemporal resolution at the picoliter or millisecond scale. Droplets, captured by a high-speed camera, are denoised through neuromorphic image processing. These processed images are employed to train convolutional neural networks, allowing the creation of segmented masks and bounding boxes around moving droplets. The trained networks further digitize time-varying multi-dimensional droplet features, such as droplet diameters, spreading and sliding motions, and corresponding impact forces. Our innovative method offers accurate measurement of small impact forces with a resolution of approximately 10 pico-newtons for droplets in the micrometer range across various configurations with the time resolution at hundreds of microseconds.

This study investigates the application of a drop-on-demand (DOD) thermal inkjet (TIJ)-based bioprinting system for the fabrication of cell-laden hydrogel microparticles (HMPs) with tunable sizes. The TIJ bioprinting technique involves the formation of vapor bubbles within the print chamber through thermal energy, expelling small droplets of bio-ink onto a substrate. The study employs a heat-treated saponified gelatin-based bio-ink, HSP-GelMA. This bio-ink is modified through methacrylic anhydride functionalization and undergoes subsequent saponification and heat treatment processes. Various concentrations of SPAN 80 surfactant in mineral oil were evaluated to assess their influence on HMP size and stability. The results indicate a direct correlation, with higher SPAN 80 concentrations resulting in smaller and more stable HMPs. The study further investigates the influence of jetting volume on HMP size distribution, revealing that larger jetting volumes lead to increased HMP sizes, attributed to droplet coalescence. This is supported by our further study via a Monte Carlo simulation, which shows that the mean droplet diameter grows approximately linear with the number of dispensed droplets. In addition, the study demonstrates the capability of the TIJ bioprinting system to achieve multimaterial encapsulation within HMPs, exemplified by staining living cells with distinct cytoplasmic membrane dyes. The presented approach provides insights into the controlled fabrication of cell-laden HMPs, highlighting the versatility of the TIJ bioprinting system for potential applications in tissue engineering and drug delivery.

Even more fascinating than its bulk parent, a water droplet possesses extraordinary catalytic and hydro-voltaic capability, elastic adaptivity, hydrophobicity, sensitivity, thermal stability, etc., but the underlying mechanism is still elusive. We emphasize herewith that the H‒O bond follows the universal bond order‒length‒strength correlation and nonbonding electron polarization regulation and the hydrogen bond cooperativity and polarizability notion regulates the performance of the coupling hydrogen bond (O:H‒O). Computational and spectrometric evidence consistently shows that molecular undercoordination shortens the intramolecular H‒O bond by up to 10% while lengthening the intermolecular O:H nonbond by 20% cooperatively with an association of electron polarization, making the 0.3-nm thick droplet skin of a supersolid phase of self-electrification. The supersolid skin dictates the performance and functionality of the droplet in chemical, dielectric, electrical, mechanical, optical, and thermal properties as well as the transport dynamics of electrons and phonons. The amplification of these findings could deepen our insight into the undercoordinated aqueous systems, including bubbles and molecular clusters, and promote deep engineering of water and ice.

Curvilinear self-propelling of droplets has attracted great interest in the past few decades due to their irreplaceable roles in many areas. Conventional understanding is that a droplet moves only along a preset channel formed by morphology or chemical components. Achieving programmable curvilinear droplet motion independent of a preset channel remains greatly challenging. Here, we report a programmable curvilinear self-propelling of droplets (circle, divergence, and convergence) based on the collaboration of the curvilinear wetting gradient and the Leidenfrost effect. This design achieves motion trajectory in a well-controlled manner as well as high velocity and long distance of droplet transport independent of the preset channel. Moreover, the motion behaviors of droplets could be predicted accurately by theoretic simulation. We envision that our unique design could manifest extensive practical applications in fluidic devices, liquid transport, and heat transfer systems.