Droplet最新文献

Droplet impact on solid surfaces is widely involved in diverse applications such as spray cooling, self-cleaning, and hydrovoltaic technology. Maximum solid‒liquid contact area yielded by droplet spreading is one key parameter determining energy conversion between droplets and surfaces. However, for the maximum deformation of impact droplets, the contact length and droplet width are usually mixed indiscriminately, resulting in unignored prediction errors in the maximum contact area. Herein, we investigate and highlight the difference between the maximum contact length and maximum droplet width. The maximum droplet width is never smaller than the maximum contact length, and the difference appears once the contact angle exceeds 90° (which becomes more significant on superhydrophobic surfaces), regardless of impact velocities, liquid viscosities, and system scales (from macroscale to nanoscale). A theoretical model analyzing the structure of the spreading rim is proposed to demonstrate and quantitatively predict the above difference, agreeing well with experimental results. Based on molecular dynamics simulations, the theoretical analysis is further extended to the scenario of nanodroplets impacting on solid surfaces. Reconsideration on the maximum deformation of impact droplets underscores the often-overlooked yet significant difference between maximum values of contact length and droplet width, which is crucial for applications involving droplet‒interface interactions.

Research on cells and organ-like tissues is critical in the fields of molecular biology, genetic analysis, proteomics analysis, tissue engineering, and others. In recent years, advancements in precise cell manipulation technologies have made precise positioning and batch processing of cells feasible. Various methods are used for cell recognition, positioning, manipulation, and assembly, often introducing external fields such as electric, magnetic, acoustic, or optical fields into the liquid environment to interact with cells, applying forces to induce cell movement and rearrangement. Alternatively, three-dimensional (3D) bioprinting technology is employed for precise cell positioning and assembly. This review will comprehensively assess the status, principles, advantages, disadvantages, and prospects of these precise cell manipulation technologies, covering single-cell manipulation, multicellular assembly, and biological 3D printing techniques.

Traditional technologies for manufacturing microfluidic devices often involve the use of molds for polydimethylsiloxane (PDMS) casting generated from photolithography techniques, which are time-consuming, costly, and difficult to use in generating multilayered structure. As an alternative, 3D printing allows rapid and cost-effective prototyping and customization of complex microfluidic structures. However, 3D-printed devices are typically opaque and are challenging to create small channels. Herein, we introduce a novel “programmable optical window bonding” 3D printing method that incorporates the bonding of an optical window during the printing process, facilitating the fabrication of transparent microfluidic devices with high printing fidelity. Our approach allows direct and rapid manufacturing of complex microfluidic structure without the use of molds for PDMS casting. We successfully demonstrated the applications of this method by fabricating a variety of microfluidic devices, including perfusable chips for cell culture, droplet generators for spheroid formation, and high-resolution droplet microfluidic devices involving different channel width and height for rapid antibiotic susceptibility testing. Overall, our 3D printing method demonstrates a rapid and cost-effective approach for manufacturing microfluidic devices, particularly in the biomedical field, where rapid prototyping and high-quality optical analysis are crucial.

The phenomenon of liquid metal “heartbeat” oscillation presents intriguing applications in microfluidic devices, drug delivery, and miniature robotics. However, achieving high vibrational kinetic energy outputs in these systems remains challenging. In this study, we developed a graphite ring electrode with V-shaped inner wall that enables wide-ranging control over the oscillation performance based on droplet size and the height of the V-shape. The mechanism driving the heartbeat is defined as a dynamic process involving the transformation of the oxide layer. Through electrochemical analysis, we confirmed three distinct states of the heartbeat and introduced a novel model to elucidate the role of the V-shaped structure in initiating and halting the oscillations. A comprehensive series of experiments explored how various factors, such as droplet volume, voltage, tilt angle, and V-shape height, affect heartbeat performance, achieving a significant conversion from surface energy to vibrational kinetic energy as high as 4732 J m⁻² s⁻¹. The increase in energy output is attributed to the synergistic effect of the V-shape height and droplet size on the oscillations. These results not only advance our understanding of liquid metal droplet manipulation but also pave the way for designing high-speed microfluidic pumping systems.

Ammonia is a suitable carbon-free alternative fuel for power equipment. Direct combustion of liquid ammonia has the potential to reduce system costs and heat loss of gas turbine (GT). However, its tendency to flash and the high latent heat of vaporization can lead to combustion deterioration. Previous research suggests that stabilizing a liquid ammonia flame requires swirling and preheated air. So far, the influence mechanism of preheated air on liquid ammonia swirl spray remains inadequately explored. To fill this research gap, this study conducted a large eddy simulation (LES) to investigate the effect of preheated air temperature ($�T_a$) on a liquid ammonia flash spray in a swirl combustor. The influence of $�T_a$ on the spray morphology and the axial velocity, diameter, and temperature distributions of the droplets were investigated to understand the spray characteristics. Besides, the effects of $�T_a$ on the evaporation characteristics, the properties, and the possible ignition performance of the mixture were studied. The results show that with the increase of $�T_a$, the heating capacity of air is enhanced, leading to a greater proportion of droplets reaching flash boiling conditions. This greatly optimizes the evaporation process, resulting in more complete evaporation and significantly smaller volume. The bulk air flow velocity is increased, causing the expansion of the inner recirculation zone (IRZ), and the gaseous temperature and mixture concentration distribution are optimized. In addition, the low gaseous ammonia concentration makes ignition difficulty at $�T_a$ = 300 K. The high $��|�$

We experimentally studied the effect of gas flow rate Q on the bubble formation on a superhydrophobic surface (SHS). We varied Q in the range of 0.001 < Q/Q_cr < 0.35, where Q_cr is the critical value for a transition from the quasi-static regime to the dynamic regime. The bubble geometrical parameters and forces acting on the bubble were calculated. We found that as Q increase, the bubble detached volume (V_d) increased. After proper normalization, the relationship between V_d and Q generally agreed with those observed for bubbles detaching from hydrophilic and hydrophobic surfaces. Furthermore, we found that Q had a minor impact on bubble shape and the duration of bubble necking due to the negligible momentum of injected gas compared to surface tension and hydrostatic pressure. Lastly, we explained the primary reason for the larger V_d at higher flow rates, which was increased bubble volume during the necking process. Our results enhanced the fundamental understanding of bubble formation on complex surfaces and could provide potential solutions for controlling bubble generation and extending the application of SHS for drag reduction, anti-fouling, and heat and mass transfer enhancement.

This paper demonstrates the use of deep learning, specifically the U-Net model, to recognize the menisci of droplets in an electrowetting-on-dielectric (EWOD) digital microfluidic (DMF) device. Accurate recognition of droplet menisci would enable precise control over the movement of droplets to improve the performance and reliability of an EWOD DMF system. Furthermore, important information such as fluid properties, droplet characteristics, spatial position, dynamic behavior, and reaction kinetics of droplets during DMF manipulation can be understood by recognizing the menisci. Through a convolutional neural network utilizing the U-Net architecture, precise identification of droplet menisci is achieved. A diverse dataset is prepared and used to train and test the model. As a showcase, details of training and the optimization of hyperparameters are described. Experimental validation demonstrated that the trained model achieves a 98% accuracy rate and a 0.92 Dice score, which confirms the model's high performance. After the successful recognition of droplet menisci, post-processing techniques are applied to extract essential information such as the droplet and bubble size and volume. This study shows that the trained U-Net model is capable of discerning droplet menisci even in the presence of background image interference and low-quality images. The model can detect not only simple droplets, but also compound droplets of two immiscible liquids, droplets containing gas bubbles, and multiple droplets of varying sizes. Finally, the model is shown to detect satellite droplets as small as 2% of the size of the primary droplet, which are byproducts of droplet splitting.

Ladybirds (Coccinella septempunctata) are adept at living in humid conditions as their elytra can effectively shield their bodies from raindrops. However, due to technical difficulties in examining the delicate structure, the understanding of the water-proofing mechanism of the coupling structure and its impact on the dome-like elytra response to the raindrops remain elusive. In this combined experimental and theoretical study, we showed that the coupling structure on the ladybird elytra can ward off the raindrops traveling at a velocity of 6 m/s, which generates an impact force equivalent to 600 times the body weight. The waterproofing mechanism relies on the deformability of the elytra and their microstructures, which collectively impedes the formation of microchannels for liquids. The enhanced water-proofing capabilities enabled by the coupling structures are validated through experimental testing on comparative 3D-printed models, showing the effectiveness of these structures in improving water resistance. Subsequently, we showcased a water-proofing device, which substantially improved the efficiency of solar panels in converting solar energy. This multidisciplinary study not only advances our understanding of the biomechanics of coupling systems in insects but also inspires the design of water-proofing deployable structures.

Given recent interest in laboratory automation and miniaturization, the microdroplet research space has expanded across research disciplines and sectors. In turn, the microdroplet field is continually evolving and seeking new methods to generate microdroplets, especially in ways that can be integrated into diverse (microfluidic) workflows. Herein, we present a convenient, low-cost, and re-usable microdroplet generation device, termed as the “NanoWand,” which enables microdroplet formation in the nanoliter volume range through modulated surface energy and roughness, that is, an open surface energy trap (oSET), using commercially available and readily assembled coating and substrate materials. A wand-like shape is excised from a microscope glass cover slip via laser-micromachining and rendered hydrophobic; a circle is then cut-out from the hydrophobically modified wand's tip using laser-micromachining to create the oSET. By adjusting the size of the oSET with laser-micromachining, the volume of the microdroplet can be similarly controlled. Using liquid microjunction–surface sampling probe–mass spectrometry (LMJ-SSP-MS), specific NanoWand droplet capture volumes were estimated to be 117 ± 23.6 nL, 198 ± 30.3 nL, and 277 ± 37.1 nL, corresponding to oSET diameters of 0.75, 1.00, and 1.25 mm, respectively. This simple approach provides a user-friendly way to form and transfer microdroplets that could be integrated into different liquid handling applications, especially when combined with the LMJ-SSP and ambient ionization MS as a powerful and rapid analytical tool.

Evaporation of saline droplets significantly impacts industrial processes such as water and gas treatment. Simulations, with advantages in describing temperature, concentration, and velocity distribution inside the droplet, receive increasing attentions. This paper summarized research on numerical simulations of droplet evaporation at micro-, meso-, and macroscales, emphasizing saline or multicomponent droplets. Accurate description of physics at phase interfaces and within proves to be critical for modeling. While recent studies have investigated on interface motion and temperature distribution, the coupling effect of internal concentration and flow distribution is still rarely considered. Among numerical methods, the lattice Boltzmann method is suitable for droplet scale due to its ability to handle non-continuum behavior. Bridging multiscale models remains a challenge, particularly in describing Marangoni and capillary flows. Experimental approaches to the effects of external physical fields (electric, magnetic, convection, and laser) and substrate properties on evaporation were also reviewed. Visualizing evaporation under various conditions can validate macroscopic models, while experiments with different substrates can validate molecular scale simulations, as substrate properties primarily affect evaporation by affecting capillary flow at the droplet bottom. This paper comprehensively reviewed numerical research on droplet evaporation, and analyzed the advantages, limitations, and development directions of various numerical methods.