Search Results (89)

Under the trend of lightweight and high-efficiency development in industrial equipment, precise regulation of lubrication in gear reducers is a key breakthrough for enhancing transmission system efficiency and reliability. This study establishes a three-dimensional numerical model for high-speed gear jet lubrication using computational fluid dynamics (CFD) and dynamic mesh technology. By implementing the volume of fluid (VOF) multiphase flow model and the standard k-ω turbulence model, the study simulates the dynamic distribution of lubricant in gear meshing zones and analyzes critical parameters such as the oil volume fraction, eddy viscosity, and turbulent kinetic energy. The results show that reducing the oil injection distance significantly enhances lubricant coverage and continuity: as the injection distance increases from 4.8 mm to 24 mm, the lubricant shifts from discrete droplets to a dense wedge-shaped film, mitigating lubrication failure risks from secondary atomization and energy loss. The optimized injection distance also improves the spatial stability of eddy viscosity and suppresses excessive dissipation of turbulent kinetic energy, enhancing both the shear-load capacity and thermal management. Dynamic data from monitoring point P show that reducing the injection distance stabilizes lubricant velocity and promotes more consistent oil film formation and heat transfer. Through multiphysics simulations and parametric analysis, this study elucidates the interaction between geometric parameters and hydrodynamic behaviors in jet lubrication systems. The findings provide quantitative evaluation methods for structural optimization and energy control in gear lubrication systems, offering theoretical insights for thermal management and reliability enhancement in high-speed transmission. These results contribute to the lightweight design and sustainable development of industrial equipment. Full article

This study presents an innovative wedge-shaped inlet weir-type microfluidic chip designed to address common issues of clogging and inefficiency in microfiltration processes. Driven solely by centrifugal force, the chip integrates a crossflow separation mechanism and enables selective droplet sorting based on size, without the need for external pumps. Fabricated from PMMA, the device features a central elliptical chamber, a wedge-shaped inlet, and spiral microchannels. These structures leverage shear stress and Dean vortices under centrifugal fields to achieve high-throughput separation of droplets with different diameters. Using water-in-oil emulsions as a model system, we systematically investigated the effects of geometric parameters and rotational speed on separation performance. A theoretical model was developed to derive the critical droplet size based on force balance, accounting for centrifugal force, viscous drag, pressure differentials, and surface tension. Experimental results demonstrate that the chip can effectively separate droplets ranging from 0 to 400 μm in diameter at 200 rpm, achieving a sorting efficiency of up to 72% and a separation threshold (cutoff accuracy) of 98.2%. Fluorescence analysis confirmed the absence of cross-contamination during single-chip operation. This work offers a structure-guided, efficient, and contamination-free droplet sorting strategy with broad potential applications in biomedical diagnostics and drug screening. Full article

In recent years, the number of transistors on electronic chips has surpassed Moore’s law, resulting in overheating and energy consumption problems in data centers (DCs). Chip-level microchannel cooling is expected to address these challenges. Grooved heat sinks with droplet-shaped fins were introduced to modify the overall capability of the cooling system. The degree of impact of the distribution of grooves and fins was analyzed and optimized using the Taguchi method. Moreover, the coupling effect of flow and temperature fields was explained using the field synergy theory. The key findings are as follows: for thermal resistance, pump power, and overall efficiency, the influence degree is the number of combined units > number of fins in each unit > distribution of the combined units. The optimal configuration of 21 combined units arranged from dense to sparse with one fin in each unit achieves 14.05% lower thermal resistance and 8.5% higher overall efficiency than the initial heat sink. The optimal configuration of five combined units arranged from sparse to dense with one fin in each unit reduces the power energy consumption by 27.61%. After optimization, the synergy angle between the velocity vector and temperature gradient is reduced by 4.29% compared to the smooth heat sink. The coupling effect between flow and heat transport is strengthened. The optimized configuration can better balance heat dissipation and energy consumption, improve the comprehensive capability of cooling system, provide a feasible solution to solve the problems of local overheating and high energy consumption in DCs. Full article

Particles ejected during thermal runaway (TR) of lithium-ion batteries carry a significant fraction of the total TR energy and can cause danger to other components in the battery system. The associated safety hazards should be addressed in the battery pack development process, which requires a deep understanding of TR particle characteristics. In this study, these characteristics are determined by applying several measurement techniques. Among them, dynamic image analysis and large particle image processing are applied to battery abuse particles for the first time, allowing their size and shape to be quantified in detail. Particles are collected from three overheating tests on a prismatic 51 Ah NMC622 cell under vacuum conditions in an autoclave environment. Battery abuse particles cover a wide size range, from micrometers to millimeters, with the largest particle reaching 51.4 mm. They are non-spherical, whereby sphericity, symmetry, and aspect ratio decrease for larger particles. Re-solidified copper droplets and intact separator pieces indicate particle temperatures of ~200–1100 °C at the time of cell ejection. Particles are partially combustible, with an exothermic onset at ~500 °C associated with graphite oxidation. Reactivity is non-linearly size dependent. Implications of these findings for battery system development are discussed. Full article

Droplet-based microfluidics (DBM) has emerged as a powerful tool for a wide range of biochemical applications, from single-cell analysis and drug screening to diagnostics and tissue engineering. This review provides a comprehensive overview of the latest advancements in droplet generation and trapping techniques, highlighting both passive and active approaches. Passive methods—such as co-flow, cross-flow, and flow-focusing geometries—rely on hydrodynamic instabilities and capillary effects, offering simplicity and integration with compact devices, though often at the cost of tunability. In contrast, active methods exploit external fields—electric, magnetic, thermal, or mechanical—to enable on-demand droplet control, allowing for higher precision and throughput. Furthermore, we explore innovative trapping mechanisms such as hydrodynamic resistance networks, microfabricated U-shaped wells, and anchor-based systems that enable precise spatial immobilization of droplets. In the final section, we also examine active droplet sorting strategies, including electric, magnetic, acoustic, and thermal methods, as essential tools for downstream analysis and high-throughput workflows. These manipulation strategies facilitate in situ chemical and biological analyses, enhance experimental reproducibility, and are increasingly adaptable to industrial-scale applications. Emphasis is placed on the design flexibility, scalability, and biological compatibility of each method, offering critical insights for selecting appropriate techniques based on experimental needs and operational constraints. Full article

The controllable transport of droplets on solid surfaces is crucial for many applications, from water harvesting to bio-analysis. Herein, we propose a novel droplet transport controlling method, reconfigurable orbital electrowetting (ROEW) on inclined slippery liquid-infused porous surfaces (SLIPS), which enables controllable transport and dynamic handling of droplets by non-contact reconfiguration of orbital electrodes. The flexible reconfigurability is attributed to the non-contact wettability modulation and reversibly deformable flexible electrodes. ROEW graphically customizes stable wettability pathways by real-time and non-contact printing of charge-orbit patterns on SLIPS to support the continuous transport of droplets. Benefiting from the fast erase-writability of charges and the movability of non-contact electrodes, ROEW enables reconfiguration of the wetting pathways by designing electrode shapes and dynamically switching electrode configurations, achieving controllable transport of various pathways and dynamic handling of droplet sorting and mixing. ROEW provides a new approach for reconfigurable, electrode-free arrays and reusable microfluidics. Full article

This study introduces a novel method for classifying whole and lactose-free milk and the detection of water adulteration through analyzing dried droplets. The key innovation is the addition of NaCl, which modulates crystallization to enhance structural differentiation and facilitate the classification of milk types and detection of adulteration. Dried droplets of milk containing NaCl concentrations of $0\%$, $2\%$, and $4\%$ were analyzed, revealing distinct morphologies, including amorphous, cross-shaped, and dendritic crystals. These structures were quantitatively characterized using lacunarity to assess their discriminatory power. Two classification approaches were evaluated: one based on lacunarity analysis alone and another incorporating deep learning. Both methods yielded high classification accuracies, with lacunarity achieving $95.04\%\pm 6.66\%$, while deep learning reached $95.22\%\pm 4.47\%$. Notably, the highest performance was obtained with $2\%$ NaCl, where lacunarity reached $97.08\%\pm 2.27\%$ and deep learning $96.88\%\pm 2.8\%$, indicating improved precision and stability. While deep learning demonstrated more consistent performance across test cases, lacunarity alone captured highly discriminative structural features, making it a valuable complementary tool. The integration of NaCl and lacunarity analysis offers a robust and interpretable methodology for ensuring the quality and authenticity of dairy products, particularly in detecting adulteration, where morphological contrast is less evident. Full article

The present work deals with the mixing of two green polymers at several definite ratios that led to the receiving of biodegradable polylactic acid (PLA)/polycaprolactone (PCL) blends possessing well-expressed macromechanical and shape memory properties. Four non-compatibilized polymer compositions were prepared by using a twin-screw melt extrusion technique, allowing for a homogeneous dispersion of the PCL droplets in the PLA matrix and higher interfacial adhesion between the two phases. The mechanical behavior of the specimens was estimated by tensile experiments conducted at three particular crosshead velocities. It was established that the addition of PCL as a soft segment redounded to an increment of the toughness and elongation at ultimate strength of the polymer composite at the expense of the maximum tensile stress and Young’s modulus. These latter two parameters were found to be more sensitive, in terms of reaching high values, to the content of PLA as a hard segment in the polymer blend. Performing thermoresponsive shape memory tests disclosed an overwhelming reversibility between the temporary and permanent states of the composite materials, including significant shape fixation ($R_f$) and shape recovery ($R_r$) rates. SEM analysis of the PLA/PCL compositions revealed a distinct phase-separated microstructure, confirming the immiscibility of the two polymers in the blend. Full article

The process of droplet formation during spraying is influenced by several factors, including the nozzle type and the use of adjuvants. This study aimed to investigate the effect of adding adjuvants to spray solutions using different nozzles, with a focus on droplet spectra, and to examine the impact of the contact angle and the surface tension on this process. The surface tension and contact angle were evaluated using a droplet shape analyzer. The experiment was conducted in a completely randomized design (CRD) using four treatment solutions: water alone and water mixed with three different types of adjuvants, including fatty acid esters (vegetable oil-based), polyether–polymethyl, and polydimethyl-siloxane. The droplet spectra (volume median diameter, relative amplitude, and droplets smaller than 100 µm) were assessed using a particle size analyzer. A CRD with a 4 × 2 factorial scheme was used to assess the effects of the four treatment solutions and two flat-fan nozzles (ULD 120-02 with air induction and LD 110-02 without air induction technology). The polyether–polymethyl considerably reduced the contact angle and surface tension (226% and 180%, respectively, in relation to water). However, it did not homogenize the droplet spectra or reduce the drift risk. The vegetable oil-based adjuvant increased the droplet size when the standard flat-fan nozzle was used. No significant correlation was found between the surface tension and contact angle regarding the droplet spectra parameters. The effect of adjuvants on the droplet spectra was found to be dependent on the nozzle type, which prevents generalizations about the implications of their use. Full article

Laser–arc hybrid welding (LAHW) is an advanced welding technology that integrates both laser and arc heat sources within a single molten pool, achieving synergistic benefits that surpass the sum of their individual contributions. This method enhances the welding speed and depth of the fusion, stabilizes the process, and minimizes welding defects. Numerous studies have investigated the principles, synergistic effects, keyhole dynamics, joint performance, and various factors influencing the parameters of laser–arc hybrid welding. This paper begins with an introduction to the classification of LAHW, followed by a discussion of the characteristics of gas-shielded welding, argon arc welding, and plasma hybrid welding. Subsequently, the welding principles underlying laser–arc hybrid welding will be elucidated. To enhance weld integrity and quality, this paper will analyze keyhole behavior, droplet transfer dynamics, welding quality performance, and the generation and prevention of welding defects that affect laser–arc hybrid welding. Additionally, a detailed analysis of the effects of residual stress on the shape, microstructure, and phase composition of the weld will be provided, along with an exploration of the influences of various welding parameters on post-weld deformation and mechanical properties. Full article

This research investigates the dynamic behavior of flames generated from methyl laurate droplets using advanced deep learning techniques. By analyzing high-resolution image sequences, we aim to extract valuable insights into the flame’s evolution, including its ignition, growth, and extinction phases. YOLOv9, a state-of-the-art object detection model, is employed to automatically segment and track key flame features such as flame shape, size, and intensity. Our results demonstrate a high accuracy of 0.97 and 0.92 mAP for automatic object segmentation of the flame and droplet. Through quantitative analysis of these features, we seek to gain a deeper understanding of the underlying physical processes governing droplet combustion. The results of this study can contribute to the development of more accurate and efficient combustion models, as well as improved fire safety strategies. This study investigates the combustion dynamics of methyl laurate droplets at atmospheric pressure, providing foundational insights into its behavior as a biodiesel fuel. Future research under high-pressure conditions is recommended to better understand its performance in practical engine applications. Full article

Sliding angle (SA) has been widely employed to describe the sliding behaviors of water droplets on substrates. However, it does not work on highly adhesive surfaces since droplets cannot slide along the substrate even at a 90° tilt. In this work, a novel strategy has been developed to characterize the sliding/pinning behaviors based on the collision between a tilted substrate and falling droplets released from a certain height. The critical tilted angle of substrate (i.e., secondary sliding angle, SSA) and the critical releasing height (i.e., H_c) of water droplets have been introduced and measured with the help of commercial equipment (drop shape analysis, DSA). Our results indicate that SSA, H_c and the phase diagram based on the combination of them work well in describing the sliding/pinning behaviors of droplets along highly adhesive substrates. The developed strategy makes it possible to distinguish sliding/pinning behaviors of water droplets along different surfaces as well as different adhesions between them. It can act as an efficient supplement to conventional methods. Full article

This paper presents the results of an optimization analysis of two types of thermal fluid channels. The selected geometries were evaluated according to the criterion of the Entropy Generation Minimization method as suggested by Adrian Bejan, with reference to a smooth pipe of the same diameter. The aim of this research was to assess the effectiveness of two channels that intensify heat transfer in different ways: with an insert (disrupting the flow in the pipe core) and with internal fins (disrupting the flow at the pipe wall), and to compare the results using the same criterion: the EGM method. The tested insert consisted of spaced streamline-shaped flow turbulizing the elements fixed in the axis of the pipe and spaced at equal distances from each other. The second channel was formed by making a right-angled triangle (rib profile) on the deformation of the pipe wall perimeter. Using computer modeling, the effect of the two geometric parameters of the above-mentioned channels on the flux of entropy generated was studied. These are (a) the diameter of the disturbing element (“droplet”) and the distance between these elements for a channel with a turbulent insert, and (b) the height of the rib and the longitudinal distance between them for a finned channel. The novelty resulting from the research is the discovery that the turbulization of the flow in the pipe wall boundary layer generates significantly less irreversible entropy than the disturbance of the flow in the pipe axis by the insert. Full article

Sambucus sibirica, a deciduous shrub from the Adoxaceae family, is a traditional Kazakh medicine used in Xinjiang, China. Its branches, leaves, and fruits are used to treat fractures, rheumatoid arthritis, and nephritis. To advance research on S. sibirica, we conducted studies on its microscopic identification, chemical composition, and biological activity. The cross-sectional features of the branches, leaves, and fruits were observed under a microscope, revealing different types of ducts, cork cells, non-glandular hairs, oil droplets, stone cells, scale hairs, and star-shaped hairs in the S. sibirica powders. Fourier transform infrared spectroscopy (FTIR) was used to characterize the presence of specific chemical groups, revealing similarities and differences between different parts. Thin-layer chromatography (TLC) confirmed that chlorogenic acid was present in the branches, leaves, and fruits, whereas rutin was more prominent in the leaves. The total flavonoid contents were determined by a photocolorimetric approach and resulted in values of 7419.80, 5193.10, and 3629.10 μg·g⁻¹ (dry weight) for the leaves, branches, and fruits, respectively. Further qualitative and quantitative analyses via ultra-performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry (UPLC-QqQ-MS/MS) identified rutin, chlorogenic acid, quercetin, isoquercetin, and astragalin, with contents ranging from 1.00 to 4535.60 μg·g⁻¹ (dry weight). Antioxidant tests revealed that the branches, leaves, and fruits of S. sibirica presented antioxidant properties, with the leaves demonstrating the highest activity, followed by the branches and fruits. These results align with the results of the quantitative analysis. This study provides valuable insights into the microscopic features, chemical composition, and antioxidant activity of S. sibirica, laying the foundation for its pharmacognosy research and quality standards and offering a reference for its future development and utilization. Full article

Droplet quality in drop-on-demand (DoD) Electrohydrodynamic (EHD) inkjet printing plays a crucial role in influencing the overall performance and manufacturing quality of the operation. The current approach to droplet printing analysis involves manually outlining/labeling the printed dots on the substrate under a microscope and then using microscope software to estimate the dot sizes by assuming the dots have a standard circular shape. Therefore, it is prone to errors. Moreover, the dot spacing information is missing, which is also important for EHD DoD printing processes, such as manufacturing micro-arrays. In order to address these issues, the paper explores the application of feature extraction methods aimed at identifying characteristics of the printed droplets to enhance the detection, evaluation, and delineation of significant structures and edges in printed images. The proposed method involves three main stages: (1) image pre-processing, where edge detection techniques such as Canny filtering are applied for printed dot boundary detection; (2) contour detection, which is used to accurately quantify the dot sizes (such as dot perimeter and area); and (3) centroid detection and distance calculation, where the spacing between neighboring dots is quantified as the Euclidean distance of the dot geometric centers. These stages collectively improve the precision and efficiency of EHD DoD printing analysis in terms of dot size and spacing. Edge and contour detection strategies are implemented to minimize edge discrepancies and accurately delineate droplet perimeters for quality analysis, enhancing measurement precision. The proposed image processing approach was first tested using simulated EHD printed droplet arrays with specified dot sizes and spacing, and the achieved quantification accuracy was over 98% in analyzing dot size and spacing, highlighting the high precision of the proposed approach. This approach was further demonstrated through dot analysis of experimentally EHD-printed droplets, showing its superiority over conventional microscope-based measurements. Full article