Complete breakup of liquids into ultrafine droplets by grid turbulence

Complete breakup of liquids into ultrafine droplets by grid turbulence | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Complete breakup of liquids into ultrafine droplets by grid turbulence Hui Wu, Ziwei Li, Zhiwen Cui, Zekun Cheng, Shanyu Zhao, Ya Huang, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3873446/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Ultrafine droplets play an important role in materials processing and nanotechnology, with crucial applications in nanoparticle preparation, molecular spraying, water evaporation, nanodrug delivery, nano-printing/coating, among numerous others. While the potential of turbulent gas flow to enhance liquid breakup is acknowledged, the construction of turbulence-driven atomizers for generating ultrafine droplets remains a significant challenge. Herein, we report the innovation of grid-turbulence atomization (GTA), which employed a rotating mesh to deliver liquid and an air knife to spray ultrafine droplets. The airflow across the mesh transitions from laminar to grid-turbulence, leading to complete liquid breakup with three-stages: bag formation, stretching, and turbulence-induced breakup. Ultrafine water droplets with a 4.8 µm Sauter mean diameter have been achieved through GTA . The GTA system demonstrates versatility in atomizing various liquids including those with high viscosities of ~ 1000 cP. We further achieved high-quality production of ultrafine powders including milk, coffee, sugar, polymers, and ceramics, based on the combination of GTA and spray-drying. Our strategic methodology establishes pivotal link between turbulence characteristics and materials processing, influencing a wide range of applications and sparking further innovation in the field. Physical sciences/Materials science/Nanoscale materials Physical sciences/Chemistry/Chemical engineering Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Liquid atomization holds fundamental importance as a cornerstone for various scientific and industrial processes. This phenomenon has been extensively studied not only for its direct applications but also for its potential to enhance the efficiency and effectiveness of diverse processes, including fuel combustion 1 , disinfectant and pesticide spraying 2 , 3 , drug delivery 4 – 6 , environmental humidification and purification 7 , 8 , seawater desalination 9 , cooling 10 , and food industry 11 , among many others. Specifically, the significance and importance of liquid atomization are pronounced in the realm of material processing and nanotechnology. Completely breaking up bulk liquid into ultrafine droplets is especially critical in this domain, playing a vital role in the production of nano-medicine, aerosol and nanomaterials using methods such as spray drying 12 , spray pyrolysis 13 , molecular coating 14 , water microdroplet chemistry 15 , and nanoscale printing 16 . In these sophisticated applications, the size of liquid droplets is paramount, and minimizing liquid droplet size has long been recognized as a critical goal. Consequently, given the important role that ultrafine droplets play in diverse materials processing and nanotechnology contexts, effectively breaking up bulk liquid into such ultrafine droplets poses a significant scientific challenge that calls for innovative solution. Current industrial liquid atomization is commonly achieved through the use of high-speed airflow; such process involves complex interactions between gas and liquid flow. The fundamental understanding of this gas-liquid interaction has been a persistent research focus, encompassing both substantial scientific challenges and practical implications that extend across scales ranging from the complexities of the global water cycle to the intricate atomization processes 17 – 22 . A prominent illustration of the gas-liquid interactions is found in the widely applied technique of pneumatic two-fluid nozzle atomization. This method harnesses high-speed airflow to efficiently break up liquids. Owing to its straightforward design, rapid operational speed, and ability to atomize high-temperature liquids, including molten metals, this technology has achieved considerable success in various engineering applications. Its simplicity, combined with versatility and efficiency, especially in handling challenging materials, positions it as a cornerstone technology in these fields 23 – 25 . However, two-fluid nozzle atomization provides limited shear force to break up the bulk liquid and typically yields droplets ranging from tens to hundreds of micrometers 23 , 26 . The spraying of sub-10-µm droplets, crucial in applications such as aerosol medications due to their high surface area-to-volume ratio as well as superior penetration and dispersion, remains challenging using conventional two-fluid nozzle atomization. Ultrasonic atomization has been applied to generate ultrafine droplets with sizes down to a few micrometers, but it often struggles with atomizing liquids of high viscosity. Moreover, the relatively low flow rate and high operating cost of ultrasonic atomization hinder its broad industrial adoption 27 – 29 . Electrostatic spraying has also been developed to generate mists but is contingent upon the use of liquids that have appropriate conductivity and/or low viscosity, and it tends to provide very limited processing efficiency 29 – 31 . The absence of a versatile method capable of producing high-quality, ultrafine droplets is a notable limitation in both fundamental science and practical applications. Consequently, development of new strategies for high-performance atomization assumes critical importance. This endeavor becomes particularly significant in the context of traditional pneumatic two-fluid atomization. Reforming and enhancing this established method to consistently generate sub-10-µm ultrafine droplets would not only be a remarkable technological breakthrough but also a major leap forward in meeting the advanced needs of various industrial processes. The physics of turbulence and the interactions between turbulent gas and liquid droplets have been intensively studied as one of the most challenging and valuable research topics in both science and engineering 32 . During the global COVID-19 pandemic, scientists conducted urgent research on how coughing and sneezing spread viruses, revealing that the effect strongly depends on the turbulent flow dynamics of human airflows. Bourouiba et al. reported experimental observations and the physical mechanisms of ultrafine droplet formation during sneezing 33 . It was found that sneezes feature turbulent multiphase flows that may contain pathogen-bearing droplets of mucosal fluid (Fig. 1 a). During sneezing, air expelled at high velocity can fragment mucus and saliva into tiny droplets laden with solid or semi-solid particles. These droplets evaporate swiftly in the turbulent setting, quickly morphing into aerosols that can travel considerable distances 33 – 36 . This effect is particularly pronounced when wearing a mask, as the “thin meshes” play a significant role in reducing the size of saliva droplets 37 . Although the “sneezing” itself may not generate ultrafine droplets in a uniform, continuous, and stable manner, this phenomenon provides insightful observations into its scientific mechanisms, suggesting that gas turbulence could be a fundamental factor in facilitating the process of ultrafine atomization. This correlation opens up potential avenues for research, where the dynamics observed in natural processes like sneezing could inform and inspire innovative approaches in atomization technology, particularly in achieving ultrafine droplet production. Herein, we were inspired by “sneezing” and its mechanisms to establish a grid-turbulence atomization (GTA) system for rapid and ultrafine liquid spraying. In general, the breakup of droplets in high-speed airflow is predominantly governed by the Weber number ( We ), which represents the ratio of fluid inertial forces to the surface tension forces of the droplets. The Weber number is defined as \(\:We={\rho\:}_{g}{U}^{2}D/\sigma\:\:,\) where \(\:{\rho\:}_{g}\) is air density, U is the slip velocity between droplet and flow, D is the droplet size and \(\:\sigma\:\) is the interfacial tension. As Weber number increases, the droplets undergo various breakup regimes 38 : deformation and flattening ( We < 12), bag breakup (12 < We 80), stretching and thinning breakup (80 < We 350). Theses regimes depend on the slip velocity and the droplet size. To accelerate the breakup of the droplets into ultrafine size, we designed and constructed a rapid rotating metal mesh to continuously deliver liquid that is sprayed out with a vertically blown grid-turbulence airflow, where the initial droplet size is constrained by the mesh size, resulting in a corresponding Weber number around O(10). The GTA setup initiates a bag formation process near the mesh. As the airflow continues to act on the liquid, the thin hollow bags begin to deform and stretch into elongated liquid threads. Additionally, the grid-induced turbulence further breaks up the droplets larger than the Kolmogorov scale, in accordance with Kolmogorov-Hinze theory 39 , 40 . Due to the high-speed airflow through the mesh holes and the intense grid-induced turbulent flows, the droplets experience three typical stages of breakup: bag formation, stretching, and turbulence-induced breakup. Under this three-stage breakup mechanism, we demonstrated that GTA can be applied as a generalized strategy for effective atomization of liquids, achieving water droplets with a Sauter mean diameter (SMD) of 4.8 µm. Beyond water, high-viscosity liquids such as olive oil, lubricating oil, and methyl silicone oil (with a viscosity of 990.0 cP) can be atomized by GTA. This capability holds particular importance in fields such as heavy oil atomization for combustion processes and inkjet printing technology. In these areas, the precision in droplet control is not just a matter of enhanced efficiency but also crucial for maintaining high-quality outcomes. The ability to accurately manage droplet size and distribution is key to optimizing performance in these applications, thereby underscoring the importance of advanced atomization technologies. As a result of the high-quality solution spray through GTA, we successfully manufactured ultrafine and uniform powders including milk, coffee, sugar, polymers and ceramics by spray-drying. The GTA system exemplifies a sophisticated interplay between turbulent gas and liquids, achieving high-quality two-fluid atomization. Design and working mechanisms of GTA Grid turbulence is a specific type of turbulence generated when fluid flows pass through a grid or a mesh-like solid structure (lower Fig. 1 a). It serves as a classic prototype for deepening our understanding of turbulence physics due to its reproducibility and simplicity 41 , 42 . In this study, we designed a GTA system that combines grid turbulence with intensive liquid spraying, utilizing a continuously rotating mesh which carries liquid for rapid atomization (Fig. 1 b, c and Supplementary Videos 1 and 2 ). The system consisted of a mesh fixed to a rotating shaft, a vessel containing liquid, and an air knife set above the mesh to provide high-speed gas blowing vertically. Firstly, a slit in the bottom of the vessel allowed the liquid to flow out of it and be continuously and uniformly separated into the mesh cells as the mesh rotated (Fig. 1 b, c). With such rotating grid system, before effective atomization, bulk liquids were separated and filled into grid cells of the mesh (Fig. 1 d). Secondly, the liquid was subsequently ejected from each mesh cell by a high-speed airflow provided by a vertically oriented air knife, forming a mist of microdroplets that vibrated and moved at exceedingly high speeds and frequencies. A clear and uniform Tyndall phenomenon could be observed during the process, indicating a stable and ultrafine liquid spray (Fig. 1 c and Supplementary Videos 2 and 3 ). To ensure full utilization of the airflow's speed and energy while avoiding significant resistance to the mesh rotation, the air knife was positioned very close to the mesh (typically ~ 1 millimeters) without making direct contact. In the GTA process, the effective separation and filling of bulk liquids into the mesh grid cells are critically dependent on the wettability of the liquid on the mesh. This wettability is influenced by both the type of liquid and the material of the mesh. The meshes employed here were commercially available and economical, typically priced at ~ 3 US dollars per piece (7.5-inch size), showcasing the cost-effectiveness of the GTA system. Additionally, the GTA system offers extensive flexibility in terms of both mesh count and material, including but not limited to nylon, copper, and stainless steel, making the system highly adaptable for handling various liquids with different wetting properties (Fig. 1 e and Supplementary Fig. 1 ). We tested the wettability of different liquids on stainless steel meshes ( Supplementary Fig. 2 ) and the wettability of water on various material substrates ( Supplementary Fig. 3 ). Liquids with good wettability tend to spread more easily on the mesh and infiltrate the mesh pores, which facilitates efficient atomization. For liquids with relatively poor wettability, to ensure rapid and even spreading on the mesh while it is rotating quickly, we placed the vessel containing the liquid adjacent to the mesh (typically ~ 1 millimeters). This setup not only supplied the liquid but also served as a scraper, effectively assisting in the application and distribution of the liquid across the mesh. This versatility, combined with the system's simplicity and financial practicality, underscores its utility in a diverse array of applications. To demonstrate the universality of the GTA strategy, we sprayed various kinds of liquids, including water (H 2 O), 3 wt% hydrogen peroxide in water (3 wt% H 2 O 2 ), ethanol, isopropanol, kerosene, crude oil, ethylene glycol, peanut oil, olive oil, lubricating oil, and methyl silicone oil (Fig. 1 f and Supplementary Fig. 4 ). The high-speed camera results showed that the atomization process for all liquids was stable. All liquids were ejected from the mesh by the gas flow, forming a mist followed by high-speed oscillations of the microdroplets ( Supplementary Video 4 ). A notable aspect of our study is the broad range of liquid viscosities we successfully atomized, ranging from ~ 1–1000 cP ( Supplementary Table 1 and Supplementary Video 5 ). This demonstrates the applicability of the GTA system in various scenarios, especially in critical areas such as fuel combustion. This versatility stands out, particularly when compared to a conventional ultrasonic atomizer equipped with a 1.7 MHz ultrasonic chip, which struggled with these higher-viscosity liquids ( Supplementary Fig. 5 and Supplementary Table 1 ). Three stages of liquid breakup To better understand the mechanisms involved in liquid fragmentation and facilitate the production of ultrafine droplets, it is first very important to understand the formation of turbulent gas flow in our GTA system. High-fidelity computational fluid dynamics (CFD) simulations (see the “ Computational fluid dynamics (CFD) simulations ” section in the Methods and Supplementary Fig. 6 ) vividly illustrated the evolution of grid-generated turbulence as airflow progresses downstream of a grid. As the gas flow encounters the grid, the flow velocity field is significantly disturbed because of the obstacle of the grid. The flow forms a strong shear layer near the grid and produces shedding vortices immediately downstream of the grid. These vortices interact and break up into smaller scales, inducing a flow transition from laminar to turbulent as it moves downstream and forming homogeneous, isotropic turbulence (Fig. 2 a, Supplementary Fig. 7a and Supplementary Video 6 ). The simulation results were also found to be quantitatively consistent with experimental flow visualization using a smoke-wire system (Fig. 2 b, Supplementary Fig. 7b and Supplementary Video 7 . The details of flow visualization are provided in the “ Flow Visualization ” section in the Methods and Supplementary Fig. 8 ). The smoke streak lines, which visualized the flow process, showed that the original laminar flow began to destabilize after passing through the mesh, forming vortices that then broke down into smaller-scale turbulent eddies. The turbulence intensity along the streamwise direction initially increased, indicating the augmentation of turbulence, and then gradually decayed, reflecting the decay of turbulence (the upper panel of Fig. 2 c and the “ Turbulence Intensity and Anisotropy ” section in the Methods ). As the mesh count increased, the distance from the meshes to the peak of turbulence intensity became shorter, and the turbulence decayed faster. This demonstrates the evolution of grid turbulence produced with different mesh counts. In the vorticity contour map with mesh of 150 counts, the flow field visibly became more chaotic at 0.5 mm distance from the edge of the mesh compared with meshes of 30 and 60 counts, indicating an earlier onset of turbulence (Fig. 2 d and Supplementary Fig. 9 ). Meanwhile, the grid turbulence became isotropic before the turbulence intensity reached the peak (the lower panel of Fig. 2 c and the “ Turbulence Intensity and Anisotropy ” section in the Methods ). The isotropic turbulence has been found to promote heat and mass transfer, increasing the evaporation rate of droplets 43 . As a comparison, the smoke streak lines still maintained uniform and straight indicating the laminar flow, when we removed the mesh from the sieve (Fig. 2 e). With such grid-turbulence flow field, we propose that the liquid underwent a three-stage process to achieve ultrafine atomization during GTA: bag formation, stretching, and turbulence-induced breakup. We used the Volume of Fluid (VOF) method to validate this process (the “ Volume of Fluid (VOF) method ” section in the Methods ). First, during the early development of grid-generated turbulence, the high-speed airflow blew out from the grid, creating a significant velocity difference from the liquid spreading in the mesh cells. Such a velocity difference leads to the formation of thin, hollow liquid bags connected to the edge of the original droplets in the mesh cells (Fig. 3 a). Correspondingly, the formation of these bags was observed experimentally using the high-speed camera (Fig. 3 b and Supplementary Video 8 ). Second, as the airflow continues to act on the liquid, the thin hollow bags begin to deform and stretch into elongated liquid threads. The VOF simulations demonstrated this stretching phase, where the liquid threads are pulled into long, thin filaments by the aerodynamic forces. During this stage, the liquid remains continuous and does not break into droplets (Fig. 3 c). Third, once droplets entered the turbulence region, they underwent turbulence-induced breakup (Fig. 3 d). At this stage, the flow field evolved into turbulence after experiencing instability, resulting in multi-scale vortices. We employed the Q criterion (see the “ Q criterion ” in the Methods ), which reflects the difference between the magnitudes of the fluid vorticity and strain rate to identify the vortices. The contours of pressure fluctuations and Q show that the generation of vortices was accompanied by pressure fluctuations (Fig. 3 e). Lower pressure usually occurred in vorticity-dominant regions (Q > 0), whereas higher pressure typically arose in strain-dominant regions (Q < 0). Liquid droplets tended to concentrate in the strain-dominant regions due to the centrifugal effect ( Supplementary Fig. 10 and Supplementary Video 9 ). These areas exhibited high pressure and strong stretching, leading to the breakup of droplets 44 , 45 . Additionally, as turbulence evolved, large vortex structures disintegrated into finer vortices, with their energy cascading down to smaller scales. This process continued until reaching the dissipation scale, where the kinetic energy was ultimately dissipated (Fig. 3 f) 46 . This process forms multi-scale distribution of vortices from the large scale to the dissipation scale. Previous studies have shown that small droplets are influenced by these multi-scale vortices, resulting in their fragmentation into smaller droplets, following the Kolmogorov-Hinze (KH) theory 47 , 48 . KH theory is the cornerstone of small droplet break up in turbulence, and identifies a Hinze scale to estimate the maximum droplet size for which the surface tension forces of the droplet can resist pressure fluctuations from turbulence 40 , 46 . Based on the KH theory, the Hinze scale decreases with the increasing dissipation rate of turbulence, indicating that turbulence augmentation leads to forming finer droplets ( Supplementary Note 1 ). In a concise overview of the liquid atomization mechanism, the airflow passing through the mesh initiates a high-speed zone, resulting in the formation of thin, hollow liquid bags. The continued interaction with the liquid film causes these hollow bags to deform and stretch into elongated liquid threads. As the airflow progresses, it undergoes a gradual transition into turbulence, giving rise to vortices of varying scales with fluctuations in physical quantities. These turbulent conditions exert stress on the droplet surface, leading to further droplet breakup. Taking advantages of the three-stage breakup mechanism, the GTA method proved highly effective in achieving superior atomization quality. The resulting water spray from the GTA method displayed a uniform particle size distribution, with the Sauter mean diameter (SMD) reaching 4.8 µm (Fig. 3 g, measured using laser diffraction analysis, see the “ Spray particle size measurement ” section in the Methods ). This closely rivals the particle sizes attained by commercial ultrasonic atomization, for which we tested frequencies of 1.7 MHz, 2.4 MHz, and 3.0 MHz, with the smallest droplet size achieved being 6.28 ± 0.25 µm at 3.0 MHz ( Supplementary Fig. 11 ). The GTA method also demonstrated remarkable atomization effectiveness across various liquids, achieving droplet sizes with a SMD of around 3.9 µm for ethanol, kerosene, and isopropanol (Fig. 3 h and Supplementary Fig. 12 ). Additionally, the GTA method showcased its capability for ultrafine atomization of a range of high-viscosity liquids, as demonstrated in the atomization of glycerol and water mixtures with varying ratios (Fig. 3 i). These liquids have similar surface tensions but significantly different viscosities ( Supplementary Table 2 ). The droplet diameters remained consistently fine across different viscosities, which is challenging for ultrasonic atomization 29 . These results underscore that grid turbulence substantially augments gas-liquid interactions, thereby facilitating finer atomization. Ultrafine atomization for applications Liquid atomization, as a method for fluid disintegration, has been widely employed in various industrial applications, including spray drying, coating, incineration, emulsion preparation, and medical devices. Spray drying has been widely applied in industrial processing to fabricate uniform, spherical, and low-cost powder particles composed of a wide array of materials from polymers to ceramics 49 . Based on the development of GTA strategy, we have successfully demonstrated its high-performance application in spray drying for the production of ultrafine powders across various substances, including sugar, coffee, milk, phosphor, NaCl, polyvinyl alcohol (PVA), and tartrazine (Fig. 4 a and Supplementary Fig. 13 ). Additionally, GTA facilitated the production of certain oxides, such as silica, alumina, zirconia, lithium cobalt nickel manganese oxide (LiNi 0.8 Co 0.1 Mn 0.1 O 2 ) and lithium lanthanum zirconium oxygen (Li 7 La 3 Zr 2 O 12 ), by precursor spray drying followed by sintering ( Supplementary Figs. 14–16 ). All these powders exhibited a uniform morphology and particle size distribution (Fig. 4 b and Supplementary Fig. 17 ), showcasing the GTA method's potential in diverse fields, from food processing to battery material manufacturing. Its formidable capacity for high-quality, ultrafine atomization positions GTA as a versatile and efficient solution across a broad application spectrum. Additionally, we have demonstrated the superior performance of the GTA method in rapid humidification. Humidity control is critical in both industrial and living environments, with industrial humidification systems playing a vital role in regulating moisture levels and preventing production issues 50 . Comparative humidification experiments revealed that GTA achieves a fast humidification rate, highlighting its promising potential for industrial applications ( Supplementary Fig. 18 ). Conclusion and outlook In summary, we have developed a highly efficient and nozzle-free GTA strategy that enables fast, uniform and ultrafine atomization of diverse liquids based on the principle of grid turbulence. The elevated airflow velocities and turbulent fluctuations associated with grid turbulence facilitated breakup and atomization of the liquid, promoting the creation of water droplets with an SMD of 4.8 µm. We emphasize the flexibility of the GTA platform, particularly in its capability to atomize a wide range of liquids including those with high viscosity. This adaptability makes the GTA system extensively applicable across various domains. Its versatility in breaking up liquids of different viscosities to product ultrafine droplets not only demonstrates its technical superiority but also expands its potential applications, making it an invaluable tool in industries where precise and efficient atomization of diverse liquids is critical. The GTA platform significantly enhances the capabilities and applications of atomization technologies. Additionally, our strategic approach in linking turbulence characteristics with flow manipulation, contributing to a deeper understanding of control paradigms within fluid dynamics. This advanced comprehension of turbulent gas-liquid interactions paves the way for a host of prospective developments in practical applications. These include but are not limited to, improved fuel injection systems, more effective disinfection methods for public spaces, and the atomization of molten metal to produce ultrafine metal powders, an essential component in the evolving technology of 3D printing. Each of these applications demonstrates the far-reaching impact and potential of the GTA system in both scientific research and industrial innovation. Methods High-speed camera observation A high-speed camera (Os7, IDT Vision, USA) equipped with two F-mount lenses (ATX 16–28 mm and 100 mm, Tokina, Japan) was used for the direct observation of the flow visualization process. A 100 W LED lamp (LED-100-T, Visico, China) was used to continuously illuminate the observed area, which enabled the acquisition of clear images with a short exposure time of the high-speed camera. The high-speed images were captured at different frame rates, including 2700, 4000, and 8000 fps. The analysis of the videos obtained was carried out using the Motion Studio software. All the high-speed videos were played at a frame rate of 30 fps using the images obtained at different frame rates. Computational fluid dynamics (CFD) simulations In this study, we examined the transition from a uniform laminar airflow to turbulence induced by a grid structure, a phenomenon pivotal in the breakup of droplets. To accurately replicate this transition, a series of comprehensive three-dimensional direct numerical simulations (DNSs) were conducted. These simulations employed an in-house CFD code, which integrates the finite difference method (FDM) and the immersed boundary method (IBM), as detailed in previous works 51 , 52 . The computational model and domain are illustrated in Supplementary Fig. 4, where D is the separation between wire centerlines, s denotes the distance from the inlet to the central plane of the grid structure, L is the streamwise domain length, and W and H specify the width and the height of the computational domain, respectively. In the present study, the velocity range of interest for the airflow is considerably below the speed of sound. Consequently, the airflow dynamics are governed by incompressible and isothermal Naiver-Stokes equations as follows, $$\:\begin{array}{c}\frac{\partial\:\varvec{u}}{\partial\:\text{t}}+\left(\varvec{u}\cdot\:\nabla\:\right)u=-\frac{1}{{\rho\:}_{f}}\nabla\:p+\nu\:{\nabla\:}^{2}u+f \left(1\right)\end{array}$$ $$\:\begin{array}{c}\nabla\:\cdot\:u=0\:. \left(2\right)\end{array}$$ Here, \(\:\varvec{u}\) is the velocity of airflow, \(\:{\rho\:}_{f}\) represents the density of air, p is the pressure, \(\:\nu\:\) is the kinematic viscosity of air, and \(\:\varvec{f}\) encapsulates the additional forces exerted on the fluid by the grid structure. To model the effect of the grid structure within the airflow, IBM was utilized to model the boundary of the grid structure. The surface of the grid structure was discretized into a uniform grid, with the discretization points denoted as X , located on the fixed boundary of the grid structure. Concurrently, a set of immersed boundaries (IB) points \(\:{\varvec{X}}_{ib}\) were employed to passively trace the flow, originating from the locations at X . To constraint IB points \(\:{\varvec{X}}_{ib}\) to the fixed points X , a weak coupling scheme was imposed by exerting IB forces \(\:{\varvec{F}}_{L}\) on the surface of the grid structure, as expressed in the following equation, $$\:\begin{array}{c}{\varvec{F}}_{L}=-\gamma\:\left[{\int\:}_{0}^{t}\left({\varvec{U}}_{ib}-\varvec{U}\right)dt+{\Delta\:}t\left({\varvec{U}}_{ib}-\varvec{U}\right)\right], \left(3\right)\end{array}$$ where \(\:\gamma\:\) is a large constant, \(\:\varDelta\:t\) is the time interval of the simulation, \(\:{\varvec{U}}_{ib}\) and \(\:\varvec{U}\) represent velocities of IB points \(\:{\varvec{X}}_{ib}\) and fixed points \(\:\varvec{X}\) on boundary, respectively. Note that \(\:\varvec{U}\) is set to zero during computation adhering to the no-slip velocity condition at the boundary, while \(\:{\varvec{U}}_{ib}\) is computed by interpolating the local fluid velocity from adjacent Eulerian grid points \(\:\varvec{x}\) , as follows, $$\:\begin{array}{c}{\varvec{U}}_{ib}=\sum\:u{\delta\:}_{h}\left(\varvec{X}-\varvec{x}\right)\varDelta\:V. \left(4\right)\end{array}$$ Here, u represents the fluid velocity at the Eulerian grid points x . The term \(\:\varDelta\:V={h}^{3}\) represents the volume of each grid cell, where h is the cell size. Note that the Cartesian grids encompassing the surface of grid structure are uniformly sized with h in all three spatial directions. Furthermore, the delta function \(\:{\delta\:}_{h}\) is formulated as $$\:\begin{array}{c}{{\delta\:}}_{\text{h}}\left(x\right)=\frac{1}{{h}^{3}}\varphi\:\left(\frac{x}{h}\right)\varphi\:\left(\frac{y}{h}\right)\varphi\:\left(\frac{z}{h}\right), \left(5\right)\end{array}$$ where $$\:\begin{array}{c}\varphi\:\left(r\right)=\left\{\begin{array}{c}\frac{1}{8}\left(3-2\left|r\right|+\sqrt{1+4\left|r\right|-4{r}^{2}}\right),\:\:\:\:\:\:\:0\le\:\left|r\right|<1,\\\:\frac{1}{8}\left(5-2\left|r\right|-\sqrt{-7+12\left|r\right|-4{r}^{2}}\right),\:1\le\:\left|r\right|<2,\\\:0,\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:2\le\:\left|r\right|\end{array}\right. \left(6\right)\end{array}$$ denotes a four-point smoothed delta function 53 . Similarly, \(\:\varvec{f}\) at the Eulerian grids is derived by interpolating the forces \(\:{\varvec{F}}_{L}\) exerted on the surface of the grid structure, i.e., $$\:\begin{array}{c}f=\sum\:{\varvec{F}}_{L}{{\delta\:}}_{\text{h}}\left(\varvec{x}-\varvec{X}\right)\varDelta\:V \:\left(7\right)\end{array}$$ For the flow solver, we adopted an implicit velocity decoupling procedure on staggered Cartesian grid system to solve the incompressible Navier-Stokes equations, as delineated by Kim et al 54 . The computational domain of the entire fluid field is set as \(\:15D\times\:9D\times\:9D\) for \(\:L,W\) and \(\:H\) , respectively. The characteristic length scale is defined by the distance between the centerlines of nearby wires, with D being 25.4mm divided by the mesh count. The distance between the inlet and the center plane of the grid structure s is equal to D . This study employs a grid resolution of 32 uniform grids per length D , resulting in a total grid number of approximately 40 million. Periodic boundary conditions for velocity and pressure are imposed in both the \(\:y\) and z directions. The inlet velocity is uniform, expressed as \(\:\varvec{u}={U}_{g}{\varvec{e}}_{x}\) , where \(\:{U}_{g}\) is the airflow velocity and \(\:{\varvec{e}}_{x}\) is the unit vector in the streamwise direction. At the outlet, a convective boundary condition is implemented. The kinematic viscosity of airflow is 1.48 \(\:\times\:{10}^{-5}{m}^{2}/s\) , and the inlet airflow velocity is around 18 m/s. Three different grid structures with mesh counts of 30, 60, and 150 were simulated, yielding Reynolds numbers based on D of \(\:Re={U}_{g}D/{\nu\:}_{g}=1100\) , 550 and 220, respectively. Volume of Fluid (VOF) method The Volume of Fluid (VOF) method 55 is one of the most commonly used interface capturing methods for simulating multiphase flows due to its mass conserving property, and ease in handling large interfacial deformations. In VOF framework, the different fluid phases interfaces are identified by an indicator fraction, α , which is chosen to be the fluid volume fraction on the Eulerian mesh. The fluid volume fraction α is given by $$\:\begin{array}{c}\alpha\:=\left\{\begin{array}{c}0,\:\:for\:fluid\:A\\\:0<\alpha\:<1,\:\:mixing\:region\:between\:fluid\:A\:and\:B\:\\\:1,\:\:for\:fluid\:B\end{array}\right. \left(8\right)\end{array}$$ In VOF method, the fluid interface is reconstructed by the above fluid volume fraction, which is advected with the flow. The evolution of fluid volume fraction is modeled by $$\:\begin{array}{c}\frac{\partial\:\alpha\:}{\partial\:t}+\nabla\:\cdot\:\left(\varvec{u}\alpha\:\right)+\nabla\:\cdot\:\left[\alpha\:\left(1-\alpha\:\right){\varvec{U}}_{r}\right]=0 \left(9\right)\end{array}$$ in which, U r is the artificial compression velocity on the fluid interface to guarantee the sharpness of the fluid interface 56 . The effect of the surface tension of the two-phase flow is determined by the Continuum Surface Model (CSF) 57 in the momentum equation and continuity equation. $$\:\begin{array}{c}\frac{\partial\:\rho\:\varvec{u}}{\partial\:t}+\nabla\:\cdot\:\left(\rho\:\varvec{u}\varvec{u}\right)=-\nabla\:{p}_{\text{r}\text{g}\text{h}}-\left(\mathbf{g}\cdot\:\mathbf{x}\right)\nabla\:\rho\:+\nabla\:\cdot\:\left[\mu\:\left(\nabla\:\varvec{u}+{\left(\nabla\:\varvec{u}\right)}^{T}\right)\right]+\sigma\:\kappa\:\nabla\:\alpha\: \left(10\right)\end{array}$$ $$\:\begin{array}{c}\nabla\:\cdot\:u=0\:. \left(11\right)\end{array}$$ where ρ and µ are the average density and viscosity weighted by the fluid volume fraction α , respectively. p rgh is the pressure excluding hydrostatic pressure, g is the gravity acceleration, σ is the surface tension coefficient, and κ is the mean curvature of the fluid interface. The mathematical models are also utilized to simulate the grid-turbulence atomization proposed in the present study. Moreover, the above multiphase flow model is solved with an open-source CFD platform, i.e., OpenFOAM. The grid structures, mesh resolution, and inlet airflow velocity are the same as those used in single-phase airflow simulation. Q Criterion The Q criterion is used to distinguish the vorticity-dominant region (Q > 0) and strain-dominant region (Q < 0). It is defined by the formula, $$\:\begin{array}{c}Q=\frac{1}{2}\left(Tr\left({\varvec{\varOmega\:}}^{2}\right)-Tr\left({\varvec{S}}^{2}\right)\right), \left(12\right)\end{array}$$ where \(\:\varvec{\varOmega\:}\) is the fluid rotation tensor, and expressed as, $$\:\begin{array}{c}\varOmega\:=\frac{1}{2}\left(\nabla\:\varvec{u}-\nabla\:{\varvec{u}}^{\text{T}}\right), \left(13\right)\end{array}$$ and \(\:\varvec{S}\) is the fluid strain-rate tensor as follows, $$\:\begin{array}{c}S=\frac{1}{2}\left(\nabla\:\varvec{u}+\nabla\:{\varvec{u}}^{\text{T}}\right). \left(14\right)\end{array}$$ Note that \(\:\nabla\:\varvec{u}\) is the fluid velocity gradient tensor, \(\:Tr(\cdot\:)\) represents an operator of the trace. Turbulence Intensity and Anisotropy Turbulence intensity at a given position x is calculated using the following formula, $$\:\begin{array}{c}I\left(x\right)=\frac{{{u}^{{\prime\:}}\left(x\right)}_{rms}}{⟨U\left(x\right)⟩}. \left(15\right)\end{array}$$ Here, \(\:{u}^{{\prime\:}}{\left(x\right)}_{rms}\) represents the root-mean-square of the velocity fluctuations in y-z plane at position x , and \(\:⟨U\left(x\right)⟩\) is the ensemble-averaged velocity in y-z plane at the same position x. Note that \(\:⟨\cdot\:⟩\) represents the ensemble-averaging in y-z plane. Turbulence anisotropy \(\:\eta\:\) is a measure used to estimate the anisotropy of Reynolds stress in turbulent flows. The Reynolds stress in y-z plane at position x is denoted as \(\:⟨{u}_{i}^{{\prime\:}}{u}_{j}{\prime\:}⟩\) , where \(\:{u}_{i}{\prime\:}\) is the component of fluid velocity fluctuation. The anisotropy factor \(\:\eta\:\) is defined as the second invariant of a normalized tensor \(\:{b}_{ij}\) , which is calculated as, $$\:\begin{array}{c}{b}_{ij}=\frac{⟨{u}_{i}^{{\prime\:}}{u}_{j}{\prime\:}⟩}{⟨{u}_{k}^{{\prime\:}}{u}_{k}{\prime\:}⟩}-\frac{1}{3}{\delta\:}_{ij}, \left(16\right)\end{array}$$ namely \(\:\eta\:={b}_{ij}{b}_{ji}\) . When \(\:\eta\:\) approaches \(\:0\) , the Reynolds stress becomes more isotropic, indicating the same statistics of fluid in any direction. Conversely, a higher \(\:\eta\:\) indicates a more anisotropic state of Reynolds stress. Flow Visualization Flow visualization was realized using a smoke-wire system in a wind tunnel (Supplementary Fig. 6), which is composed of a smoke-wire controller (SW02, Dalian Hanghua Science & Technology Co., Ltd, China), a resistance wire with a diameter of 0.1 mm, a flashlamp, and a digital camera (Canon 850D). In the experiment, paraffin oil was coated on the resistance wire to produce a smoke line under the control of the controller. The smoke line was blown forward in the wind tunnel and captured by the camera. The flashlamp was used to illuminate the flow field. Photographs of the smoke line's trajectory characterized the flow characteristics and vortex dynamics. Spray Particle Size Measurement The spray particle sizes, specifically the volume distribution of the droplets, were measured using a spray laser particle size analyzer (PW180-B, Shandong NKT Analytical Instrument Co., Ltd, China). The measuring axial distance was approximately 100 mm. The instrument was able to measure sprays of diverse substances by leveraging a built-in database containing material parameters. Data analysis was conducted using accompanying software provided by the manufacturer. To determine the average diameter of the droplets, the Sauter Mean Diameter (SMD) was used, calculated using the formula: $$\:\begin{array}{c}SMD=\frac{\sum\:\left({d}_{i}^{3}{n}_{i}\right)}{\sum\:\left({d}_{i}^{2}{n}_{i}\right)}, \left(17\right)\end{array}$$ where \(\:{d}_{i}\) represents the diameter of individual droplets, and \(\:{n}_{i}\) is the number of droplets with that diameter. Evaluation of Humidification Efficiency of the Atomization System To gauge the efficiency of the atomization system, a humidification experiment was conducted in an enclosed room of dimensions 2m × 3m × 4m (Supplementary Fig. 18a). The ambient humidity was initially reduced to 20% using a dehumidifier. Once this was achieved, the dehumidifier was turned off and the atomization system was activated. A digital hygrometer was employed to monitor and record the rise in humidity in real-time. Morphology and structure Characterizations The morphological properties and elementary composition of particles were measured by a field-emission scanning electron microscope (FE-SEM, LEO-1530, Zeiss, Germany) equipped with energy-dispersive X-ray spectroscopy (EDS). The diameter distribution of the particles was measured with a laser particle sizer (Mastersizer 3000, Malvern, UK). Crystal structure of SiO 2 , Al 2 O 3 , ZrO 2 , Li 7 La 3 Zr 2 O 12 , and LiNi 0.8 Co 0.1 Mn 0.1 O 2 powder were determined by XRD (D/Max 2,500, Rigaku, Japan), where the X-ray was Cu-Kα radiation, scanning speed was 5°/min, and the scanning range was 10° − 80°. Declarations Data availability All relevant data are contained in the manuscript, Supplementary Information, and source data. Code availability Custom code used in the study is available from the corresponding authors upon reasonable request. Acknowledgments This work was supported by the Basic Science Center Program of the National Natural Science Foundation of China (NSFC) under grant No. 52388201, NSFC under grant No. 52325312, 123881019, 2252104, 92252204, and 12302285, the China Postdoctoral Science Foundation (CPSF) under grant No. 2022M721849, and the Postdoctoral Fellowship Program of CPSF under grant No. GZB20230360. Author contributions H.W. conceived the idea and supervised the research. H.W. and Z.W.L. designed the experiments. Z.W.L. and Z.K.C designed and construct the experimental system. L.H.Z., Y.S.L, Z.W.C., and S.J.L. performed the modeling and simulations. Z.W.L., S.Y.Z., Y.H., H.Y.W., Y.C.F., Y.Q.Z, P.D., S.L., and H.W. synthesized the specimens and performed the analysis of different characterizations. Z.W.L., Z.W.C., L.H.Z., and H.W. contributed to writing the manuscript. Corresponding authors Correspondence to Hui Wu or Lihao Zhao. Competing interests A patent (application number: CN202211013454.3, application date: 23 August 2022, patent status: under substantive examination) for the atomization method has been applied for on behalf of Tsinghua University. H.W. and Z.L. are listed as inventors. The invention discloses an atomization system, its usage method, and applications, which correlated with the research. The other authors declare no competing interests. References Li X et al (2024) A review on the recent advances of flash boiling atomization and combustion applications. Prog Energy Combust Sci 100:101119 Jain RG et al (2022) Foliar application of clay-delivered RNA interference for whitefly control. Nat Plants 8:535–548 Cao T et al (2022) H 2 O 2 generation enhancement by ultrasonic nebulisation with a zinc layer for spray disinfection. Chem Eng J 431:134005 Lokugamage MP et al (2021) Optimization of lipid nanoparticles for the delivery of nebulized therapeutic mRNA to the lungs. Nat Biomed Eng 5:1059–1068 Shapira T et al (2022) A TMPRSS2 inhibitor acts as a pan-SARS-CoV-2 prophylactic and therapeutic. Nature 605:340–348 de Vries RD et al (2021) Intranasal fusion inhibitory lipopeptide prevents direct-contact SARS-CoV-2 transmission in ferrets. Science 371:1379–1382 Sharma D et al (2021) Development of an anti-clogging perforated plate atomizer for a zero liquid discharge humidification-dehumidification desalination system. Desalination 515:115195 Xie Z et al (2023) Experimental study on the atomization characteristics and dust removal efficiency of a fan-shaped nozzle for purifying working environment. Sci Total Environ 894:164994 Xu F et al (2022) Research on atomization evaporation characteristics and parameter optimization of a novel spray evaporation desalting system. Desalination 542:116057 Jiang M et al (2022) Inhibiting the Leidenfrost effect above 1,000°C for sustained thermal cooling. Nature 601:568–572 Figueiredo JdA et al (2022) Microencapsulation by spray chilling in the food industry: Opportunities, challenges, and innovations. Trends Food Sci Technol 120:274–287 Mezhericher M, Nunes JK, Guzowski JJ, Stone HA (2018) Aerosol-assisted synthesis of submicron particles at room temperature using ultra-fine liquid atomization. Chem Eng J 346:606–620 Muravev V et al (2023) Size of cerium dioxide support nanocrystals dictates reactivity of highly dispersed palladium catalysts. Science 380:1174–1179 Anggara K et al (2023) Direct observation of glycans bonded to proteins and lipids at the single-molecule level. Science 382:219–223 Zhang D, Yuan X, Gong C, Zhang X (2022) High Electric Field on Water Microdroplets Catalyzes Spontaneous and Ultrafast Oxidative C–H/N–H Cross-Coupling. J Am Chem Soc 144:16184–16190 Jung W et al (2021) Three-dimensional nanoprinting via charged aerosol jets. Nature 592:54–59 Park S et al (2021) Stabilization of liquid instabilities with ionized gas jets. Nature 592:49–53 Wilson JL et al (2023) Aerodynamic interactions of drops on parallel fibres. Nat Phys Zhang Y et al (2022) Continuous air purification by aqueous interface filtration and absorption. Nature 610:74–80 Liu B et al (2023) Nanoscale Transport during Liquid Film Thinning Inhibits Bubble Coalescing Behavior in Electrolyte Solutions. Phys Rev Lett 131:104003 Erdosy DP et al (2022) Microporous water with high gas solubilities. Nature 608:712–718 Cai W et al (2019) Pantropical climate interactions. Science 363:eaav4236 Mlkvik M et al (2015) Twin-fluid atomization of viscous liquids: The effect of atomizer construction on breakup process, spray stability and droplet size. Int J Multiph Flow 77:19–31 Karnawat J, Kushari A (2006) Controlled atomization using a twin-fluid swirl atomizer. Exp Fluids 41:649–663 Sovani SD, Sojka PE, Lefebvre AH (2001) Effervescent atomization. Prog Energy Combust Sci 27:483–521 Pacheco C, Pina J, Saleh K (2016) Atomization of molten materials for particle coating: Prediction of mean droplet size for two-fluid nozzles. 26:1031–1050 Gaete-Garretón L, Briceño-Gutiérrez D, Vargas-Hernández Y, Zanelli C (2018) I. Ultrasonic atomization of distilled water. J Acoust Soc Am 144:222–227 Avvaru B, Patil MN, Gogate PR, Pandit AB (2006) Ultrasonic atomization: Effect of liquid phase properties. Ultrasonics 44:146–158 Lefebvre AH, McDonell VG (2017) Atomization and sprays. CRC Xu W et al (2022) Electrostatic atomization minimum quantity lubrication machining: from mechanism to application. Int J Extreme Manuf 4:042003 Wang J, Zhang Y, Zhang W, Fan Z (2021) Research Progress of Electrostatic Spray Technology over the Last Two Decades. J Energy Eng 147:03121003 Lee S-Y, Moiz AA, Cung KD (2018) In: Basu S (ed) Droplets and Sprays: Applications for Combustion and Propulsion. Springer Singapore, pp 277–312. Avinash Kumar Agarwal, Achintya Mukhopadhyay, & Chetankumar Patel) Bourouiba L (2020) Turbulent Gas Clouds and Respiratory Pathogen Emissions: Potential Implications for Reducing Transmission of COVID-19. JAMA 323:1837–1838 Chong KL et al (2021) Extended Lifetime of Respiratory Droplets in a Turbulent Vapor Puff and Its Implications on Airborne Disease Transmission. Phys Rev Lett 126:034502 Scharfman BE, Techet AH, Bush JWM, Bourouiba L (2016) Visualization of sneeze ejecta: steps of fluid fragmentation leading to respiratory droplets. Exp Fluids 57:24 Pallares J, Fabregat A (2022) A model to predict the short-term turbulent indoor dispersion of small droplets and droplet nuclei released from coughs and sneezes. Indoor Built Environ 31:1393–1404 Dbouk T, Drikakis D (2020) On respiratory droplets and face masks. Phys Fluids 32:063303 Lee CS, Reitz R, D. EFFECT, OF LIQUID PROPERTIES ON THE BREAKUP MECHANISM OF HIGH-SPEED LIQUID DROPS (2001). 11, 1–19 Ni R (2024) Deformation and Breakup of Bubbles and Drops in Turbulence. Annu Rev Fluid Mech 56:319–347 Hinze JO (1955) Fundamentals of the hydrodynamic mechanism of splitting in dispersion processes. AlChE J 1:289–295 Kistler AL, Vrebalovich T (1966) Grid turbulence at large Reynolds numbers. J Fluid Mech 26:37–47 ErtunÇ Ö, ÖZyilmaz N, Lienhart H, Durst F, Beronov K (2010) Homogeneity of turbulence generated by static-grid structures. J Fluid Mech 654:473–500 Zbicinski I, Grad J, Strumillo C (1996) Effect of Turbulence on Heat and Mass Transfer in the Atomization Zone. Dry Technol 14:231–244 Lemenand T, Dupont P, Valle DD, Peerhossaini H (2013) Comparative efficiency of shear, elongation and turbulent droplet breakup mechanisms: Review and application. Chem Eng Res Des 91:2587–2600 Andersson R, Andersson B (2006) Modeling the breakup of fluid particles in turbulent flows. AlChE J 52:2031–2038 Nikolaevich KA (1941) The local structure of turbulence in incompressible viscous fluid for very large Reynolds. Numbers Dokl Akad Nauk SSSR Crialesi-Esposito M, Chibbaro S, Brandt L (2023) The interaction of droplet dynamics and turbulence cascade. Commun Phys 6:5 Qi Y et al (2022) Fragmentation in turbulence by small eddies. Nat Commun 13:469 Boel E et al (2020) Unraveling Particle Formation: From Single Droplet Drying to Spray Drying and Electrospraying. Pharmaceutics 12:625 Shehadi M (2018) Review of humidity control technologies in buildings. J Build Eng 19:539–551 Huang W-X, Shin SJ, Sung HJ (2007) Simulation of flexible filaments in a uniform flow by the immersed boundary method. J Comput Phys 226:2206–2228 Huang W-X, Chang CB, Sung HJ (2011) An improved penalty immersed boundary method for fluid–flexible body interaction. J Comput Phys 230:5061–5079 Peskin CS (2002) The immersed boundary method. Acta Numer 11:479–517 Kim K, Baek S-J, Sung HJ (2002) An implicit velocity decoupling procedure for the incompressible Navier–Stokes equations. Int J Numer Methods Fluids 38:125–138 Hirt CW, Nichols BD (1981) Volume of fluid (VOF) method for the dynamics of free boundaries. J Comput Phys 39:201–225 Weller HG (2008) A new approach to VOF-based interface capturing methods for incompressible and compressible flow. OpenCFD Ltd Rep TR/HGW 4:35 Brackbill JU, Kothe DB, Zemach C (1992) A continuum method for modeling surface tension. J Comput Phys 100:335–354 Additional Declarations There is NO Competing Interest. Supplementary Files RevisedSupplementarymaterials0828.docx SupplementaryVideo1.mp4 Supplementary Video 1 SupplementaryVideo2.mp4 Supplementary Video 2 SupplementaryVideo3.mp4 Supplementary Video 3 SupplementaryVideo4.mp4 Supplementary Video 4 SupplementaryVideo5.mp4 Supplementary Video 5 SupplementaryVideo6.mp4 Supplementary Video 6 SupplementaryVideo7.mp4 Supplementary Video 7 SupplementaryVideo8.mp4 Supplementary Video 8 SupplementaryVideo9.mp4 Supplementary Video 9 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3873446","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":359712763,"identity":"2c9d18de-384e-417d-bdde-4797fc3114d6","order_by":0,"name":"Hui 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University","correspondingAuthor":false,"prefix":"","firstName":"Peng","middleName":"","lastName":"Du","suffix":""},{"id":359712773,"identity":"54719ca9-776c-4ec2-98a4-0e38bed59305","order_by":10,"name":"Sheng Lu","email":"","orcid":"","institution":"State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University","correspondingAuthor":false,"prefix":"","firstName":"Sheng","middleName":"","lastName":"Lu","suffix":""},{"id":359712774,"identity":"61f535e6-a044-4540-8915-5edf5ad07d59","order_by":11,"name":"Lihao Zhao","email":"","orcid":"","institution":"Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University","correspondingAuthor":false,"prefix":"","firstName":"Lihao","middleName":"","lastName":"Zhao","suffix":""}],"badges":[],"createdAt":"2024-01-17 17:20:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3873446/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3873446/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":65564663,"identity":"75f93cb9-b880-456c-89a6-8e29e25f37ee","added_by":"auto","created_at":"2024-09-30 05:08:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3240424,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGTA design and construction. a\u003c/strong\u003e, Schematic illustration of turbulence generated by sneezing and a grid. \u003cstrong\u003eb\u003c/strong\u003e, Illustration of the GTA system. Liquid continuously flows out from the vessel and uniformly splits to fill into mesh cells as the mesh rotates. The liquid is subsequently ejected into a spray by the high-speed airflow generated by the air knife, resulting in a high-quality atomization with high speed. \u003cstrong\u003ec\u003c/strong\u003e, Photographs of the GTA equipment. A clear and uniform Tyndall phenomenon was observed. \u003cstrong\u003ed\u003c/strong\u003e, Optical microscope image of the mesh during the GTA process. Liquid has been spitted and filled into the mesh cells and then sprayed out by the air knife. \u003cstrong\u003ee\u003c/strong\u003e, Photographs of a collection of meshes with various counts and meshes made with different materials including nylon, copper and stainless steel (right column). The meshes are commercially accessible with typical costs of ~3 US dollars per piece (stainless steel mesh sifter, 7.5-inch, right column), indicating that the GTA system can be easily constructed, duplicated and scaled up with low costs. \u003cstrong\u003ef\u003c/strong\u003e, High-speed camera image of the GTA process using different liquids, including water (H\u003csub\u003e2\u003c/sub\u003eO), 3 wt% H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, ethanol, crude oil, olive oil, lubricating oil, and silicone oil, with viscosity values from 1.0 to 990.0 cP. We clearly observed that different liquids were ejected quickly, forming a uniform mist of ultrafine microdroplets.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-3873446/v1/c8b9633c6796b91d77498ee8.png"},{"id":65564658,"identity":"65d617c1-b10e-45d2-9441-2f175ce35266","added_by":"auto","created_at":"2024-09-30 05:08:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":4188013,"visible":true,"origin":"","legend":"\u003cp\u003ea, CFD simulation result depicting the flow structures and the nondimensionalized magnitude of airflow velocity U/U\u003csub\u003eg\u003c/sub\u003e as it passes through a mesh. U\u003csub\u003eg\u003c/sub\u003e is the magnitude of the initial airflow velocity. b, Experimental flow visualization illustrating the airflow dynamics as it passes through a mesh, captured using the smoke wire technique to trace the airflow patterns. c, Turbulence intensity I and anisotropy η along the x-axis at y=0 and z=0 using meshes with different counts (see the “Turbulence Intensity and Anisotropy” section in the Methods). d, CFD simulation result depicting the nondimensionalized vorticity magnitude, normalized with time T where T=D/U\u003csub\u003eg\u003c/sub\u003e, as airflow passes through meshes with different counts. D is equal to 25.4 mm divided by mesh counts. e, A comparison of experimental flow visualizations with and without the presence of mesh. The upper image illustrates the smooth airflow pattern without a mesh (the mesh was removed from the sieve, leaving only its metal frame), while the lower image captures the disrupted airflow with the mesh in place, highlighting the significant impact of the mesh on airflow dynamics.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-3873446/v1/a4ce61c3c0ee2adf5cd63af1.png"},{"id":65564653,"identity":"2515832c-6895-4aa0-8fb9-efe7740db65a","added_by":"auto","created_at":"2024-09-30 05:08:10","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":5936315,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLiquid breakup mechanisms. a\u003c/strong\u003e, Simulation results of VOF illustrating the bag formation process.\u003cstrong\u003e b\u003c/strong\u003e, A high-speed camera image of the GTA process illustrating bag formation. The droplets formed bubbles when blown by high-speed airflow, followed by breaking into small fragments and mist (see \u003cstrong\u003eSupplementary Video 8\u003c/strong\u003e).\u003cstrong\u003ec\u003c/strong\u003e, Simulation results of VOF illustrating the liquid stretching process. \u003cstrong\u003ed\u003c/strong\u003e, Simulation results of VOF illustrating the turbulence-induced liquid breakup process, coupled with airflow velocity field. \u0026nbsp;\u003cem\u003eU\u003c/em\u003e\u003csub\u003eg\u003c/sub\u003e is the magnitude of the initial airflow velocity. \u003cstrong\u003ee\u003c/strong\u003e, A 2D map of vortices identified by the Q criterion in grid turbulence, coupled with contour lines of pressure fluctuations (see the “\u003cstrong\u003eQ Criterion\u003c/strong\u003e” in the \u003cstrong\u003eMethods\u003c/strong\u003e). Here, the Q value reflects the difference between the magnitudes of the fluid vorticity and strain rate. Q \u0026gt; 0 represents vorticity-dominant region and Q \u0026lt; 0 signifies strain-dominant region. \u003cstrong\u003ef\u003c/strong\u003e, Schematic illustration of the energy cascade process during the evolution of grid turbulence. \u003cstrong\u003eg\u003c/strong\u003e, Size distribution of water droplets generated by GTA. \u003cstrong\u003eh\u003c/strong\u003e, Sauter Mean Diameter (SMD) of droplets generated by GTA for different liquids. \u003cstrong\u003ei\u003c/strong\u003e, SMD of droplets generated by GTA for glycerin/water mixtures with different ratios and viscosities.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-3873446/v1/b0c1d4fbe4f10af33b7bd163.png"},{"id":65564668,"identity":"0c60a1e0-f4e2-4e4d-9d0a-680cfbcc6931","added_by":"auto","created_at":"2024-09-30 05:08:13","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":948286,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGTA as a generalized strategy to fabricate ultrafine powders. a\u003c/strong\u003e, Photographs of a rich variety of powders fabricated by GTA spray-dry (Nos. 1-12: sugar, coffee, milk, phosphor, NaCl, PVA, tartrazine, silica, alumina, zirconia, LiNi\u003csub\u003e0.8\u003c/sub\u003eCo\u003csub\u003e0.1\u003c/sub\u003eMn\u003csub\u003e0.1\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e and Li\u003csub\u003e7\u003c/sub\u003eLa\u003csub\u003e3\u003c/sub\u003eZr\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e12\u003c/sub\u003e). Detailed fabrication processes are provided in the \u003cstrong\u003eMethods\u003c/strong\u003e and \u003cstrong\u003eSupplementary information\u003c/strong\u003e. \u003cstrong\u003eb\u003c/strong\u003e, Scanning electron microscopy (SEM) images of the corresponding powders (Nos. 1-12).\u003c/p\u003e","description":"","filename":"image4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3873446/v1/1081dcaf3bece8f4d15e053d.jpeg"},{"id":65567363,"identity":"3c067a42-3a6f-41e6-a7fe-e9e3837f0873","added_by":"auto","created_at":"2024-09-30 05:40:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":16664979,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3873446/v1/eab65913-07c9-42c6-8639-6f551367b895.pdf"},{"id":65564673,"identity":"62a9e914-2b07-44ef-b00b-fee24a9f31de","added_by":"auto","created_at":"2024-09-30 05:08:14","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":24899426,"visible":true,"origin":"","legend":"","description":"","filename":"RevisedSupplementarymaterials0828.docx","url":"https://assets-eu.researchsquare.com/files/rs-3873446/v1/11ba1ef1bfe5a60c388268ff.docx"},{"id":65564656,"identity":"0afa8563-a54f-4b9b-b04b-72cbea61064e","added_by":"auto","created_at":"2024-09-30 05:08:12","extension":"mp4","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":33211320,"visible":true,"origin":"","legend":"Supplementary Video 1","description":"","filename":"SupplementaryVideo1.mp4","url":"https://assets-eu.researchsquare.com/files/rs-3873446/v1/cae2659ff34d9366ae4795ca.mp4"},{"id":65564660,"identity":"7de1b9ee-1eed-48c1-9fa8-931559ae9f1d","added_by":"auto","created_at":"2024-09-30 05:08:12","extension":"mp4","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":19225882,"visible":true,"origin":"","legend":"Supplementary Video 2","description":"","filename":"SupplementaryVideo2.mp4","url":"https://assets-eu.researchsquare.com/files/rs-3873446/v1/9e8610d1e341fda6689f5bcc.mp4"},{"id":65564655,"identity":"72a28927-3b01-4882-bdd7-9e7fb4728bfb","added_by":"auto","created_at":"2024-09-30 05:08:11","extension":"mp4","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":28077892,"visible":true,"origin":"","legend":"Supplementary Video 3","description":"","filename":"SupplementaryVideo3.mp4","url":"https://assets-eu.researchsquare.com/files/rs-3873446/v1/cd48a6b0efef02e3ae923d3f.mp4"},{"id":65565913,"identity":"aa2649a7-a88b-4439-951e-0c1653e1b145","added_by":"auto","created_at":"2024-09-30 05:24:12","extension":"mp4","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":23804600,"visible":true,"origin":"","legend":"Supplementary Video 4","description":"","filename":"SupplementaryVideo4.mp4","url":"https://assets-eu.researchsquare.com/files/rs-3873446/v1/53b183e3ccdb6494f319dc6c.mp4"},{"id":65564664,"identity":"2c5548e7-9523-44ee-9cba-42529749b5a9","added_by":"auto","created_at":"2024-09-30 05:08:13","extension":"mp4","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":23492237,"visible":true,"origin":"","legend":"Supplementary Video 5","description":"","filename":"SupplementaryVideo5.mp4","url":"https://assets-eu.researchsquare.com/files/rs-3873446/v1/35970e5bf1ace1989142553f.mp4"},{"id":65564657,"identity":"ed9c0505-3b99-41cb-b3b3-f4fb509aca72","added_by":"auto","created_at":"2024-09-30 05:08:12","extension":"mp4","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":33298933,"visible":true,"origin":"","legend":"Supplementary Video 6","description":"","filename":"SupplementaryVideo6.mp4","url":"https://assets-eu.researchsquare.com/files/rs-3873446/v1/a5c092b2d0e9c08efdf24a62.mp4"},{"id":65564679,"identity":"30f3daa2-55c2-44b3-a8b6-32f1b6c69514","added_by":"auto","created_at":"2024-09-30 05:08:15","extension":"mp4","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":30695012,"visible":true,"origin":"","legend":"Supplementary Video 7","description":"","filename":"SupplementaryVideo7.mp4","url":"https://assets-eu.researchsquare.com/files/rs-3873446/v1/dcb689603952acfd998ccfed.mp4"},{"id":65564659,"identity":"a6f03dfb-81a7-43ad-8f78-96ec02d14b8c","added_by":"auto","created_at":"2024-09-30 05:08:12","extension":"mp4","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":30571015,"visible":true,"origin":"","legend":"Supplementary Video 8","description":"","filename":"SupplementaryVideo8.mp4","url":"https://assets-eu.researchsquare.com/files/rs-3873446/v1/61da1de3b23e2222e7923e8e.mp4"},{"id":65564666,"identity":"f6f5b8a9-a85f-44eb-9a5a-b21067200877","added_by":"auto","created_at":"2024-09-30 05:08:13","extension":"mp4","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":14970013,"visible":true,"origin":"","legend":"Supplementary Video 9","description":"","filename":"SupplementaryVideo9.mp4","url":"https://assets-eu.researchsquare.com/files/rs-3873446/v1/656fe754870f5e9f739a4361.mp4"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Complete breakup of liquids into ultrafine droplets by grid turbulence","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLiquid atomization holds fundamental importance as a cornerstone for various scientific and industrial processes. This phenomenon has been extensively studied not only for its direct applications but also for its potential to enhance the efficiency and effectiveness of diverse processes, including fuel combustion\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, disinfectant and pesticide spraying\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, drug delivery\u003csup\u003e\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e, environmental humidification and purification\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, seawater desalination\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, cooling\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, and food industry\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, among many others. Specifically, the significance and importance of liquid atomization are pronounced in the realm of material processing and nanotechnology. Completely breaking up bulk liquid into ultrafine droplets is especially critical in this domain, playing a vital role in the production of nano-medicine, aerosol and nanomaterials using methods such as spray drying\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, spray pyrolysis\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, molecular coating\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, water microdroplet chemistry\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, and nanoscale printing\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. In these sophisticated applications, the size of liquid droplets is paramount, and minimizing liquid droplet size has long been recognized as a critical goal. Consequently, given the important role that ultrafine droplets play in diverse materials processing and nanotechnology contexts, effectively breaking up bulk liquid into such ultrafine droplets poses a significant scientific challenge that calls for innovative solution.\u003c/p\u003e \u003cp\u003eCurrent industrial liquid atomization is commonly achieved through the use of high-speed airflow; such process involves complex interactions between gas and liquid flow. The fundamental understanding of this gas-liquid interaction has been a persistent research focus, encompassing both substantial scientific challenges and practical implications that extend across scales ranging from the complexities of the global water cycle to the intricate atomization processes\u003csup\u003e\u003cspan additionalcitationids=\"CR18 CR19 CR20 CR21\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. A prominent illustration of the gas-liquid interactions is found in the widely applied technique of pneumatic two-fluid nozzle atomization. This method harnesses high-speed airflow to efficiently break up liquids. Owing to its straightforward design, rapid operational speed, and ability to atomize high-temperature liquids, including molten metals, this technology has achieved considerable success in various engineering applications. Its simplicity, combined with versatility and efficiency, especially in handling challenging materials, positions it as a cornerstone technology in these fields\u003csup\u003e\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. However, two-fluid nozzle atomization provides limited shear force to break up the bulk liquid and typically yields droplets ranging from tens to hundreds of micrometers\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. The spraying of sub-10-\u0026micro;m droplets, crucial in applications such as aerosol medications due to their high surface area-to-volume ratio as well as superior penetration and dispersion, remains challenging using conventional two-fluid nozzle atomization. Ultrasonic atomization has been applied to generate ultrafine droplets with sizes down to a few micrometers, but it often struggles with atomizing liquids of high viscosity. Moreover, the relatively low flow rate and high operating cost of ultrasonic atomization hinder its broad industrial adoption\u003csup\u003e\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Electrostatic spraying has also been developed to generate mists but is contingent upon the use of liquids that have appropriate conductivity and/or low viscosity, and it tends to provide very limited processing efficiency\u003csup\u003e\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. The absence of a versatile method capable of producing high-quality, ultrafine droplets is a notable limitation in both fundamental science and practical applications. Consequently, development of new strategies for high-performance atomization assumes critical importance. This endeavor becomes particularly significant in the context of traditional pneumatic two-fluid atomization. Reforming and enhancing this established method to consistently generate sub-10-\u0026micro;m ultrafine droplets would not only be a remarkable technological breakthrough but also a major leap forward in meeting the advanced needs of various industrial processes.\u003c/p\u003e \u003cp\u003eThe physics of turbulence and the interactions between turbulent gas and liquid droplets have been intensively studied as one of the most challenging and valuable research topics in both science and engineering\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. During the global COVID-19 pandemic, scientists conducted urgent research on how coughing and sneezing spread viruses, revealing that the effect strongly depends on the turbulent flow dynamics of human airflows. Bourouiba et al. reported experimental observations and the physical mechanisms of ultrafine droplet formation during sneezing\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. It was found that sneezes feature turbulent multiphase flows that may contain pathogen-bearing droplets of mucosal fluid (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). During sneezing, air expelled at high velocity can fragment mucus and saliva into tiny droplets laden with solid or semi-solid particles. These droplets evaporate swiftly in the turbulent setting, quickly morphing into aerosols that can travel considerable distances\u003csup\u003e\u003cspan additionalcitationids=\"CR34 CR35\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. This effect is particularly pronounced when wearing a mask, as the \u0026ldquo;thin meshes\u0026rdquo; play a significant role in reducing the size of saliva droplets\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Although the \u0026ldquo;sneezing\u0026rdquo; itself may not generate ultrafine droplets in a uniform, continuous, and stable manner, this phenomenon provides insightful observations into its scientific mechanisms, suggesting that gas turbulence could be a fundamental factor in facilitating the process of ultrafine atomization. This correlation opens up potential avenues for research, where the dynamics observed in natural processes like sneezing could inform and inspire innovative approaches in atomization technology, particularly in achieving ultrafine droplet production.\u003c/p\u003e \u003cp\u003eHerein, we were inspired by \u0026ldquo;sneezing\u0026rdquo; and its mechanisms to establish a grid-turbulence atomization (GTA) system for rapid and ultrafine liquid spraying. In general, the breakup of droplets in high-speed airflow is predominantly governed by the Weber number (\u003cem\u003eWe\u003c/em\u003e), which represents the ratio of fluid inertial forces to the surface tension forces of the droplets. The Weber number is defined as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:We={\\rho\\:}_{g}{U}^{2}D/\\sigma\\:\\:,\\)\u003c/span\u003e\u003c/span\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\rho\\:}_{g}\\)\u003c/span\u003e\u003c/span\u003e is air density, \u003cem\u003eU\u003c/em\u003e is the slip velocity between droplet and flow, D is the droplet size and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\sigma\\:\\)\u003c/span\u003e\u003c/span\u003e is the interfacial tension. As Weber number increases, the droplets undergo various breakup regimes\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e: deformation and flattening (\u003cem\u003eWe\u003c/em\u003e \u0026lt;\u0026thinsp;12), bag breakup (12\u0026thinsp;\u0026lt;\u0026thinsp;\u003cem\u003eWe\u003c/em\u003e \u0026lt;\u0026thinsp;80), boundary layer or \u0026ldquo;shear\u0026rdquo; breakup (\u003cem\u003eWe\u003c/em\u003e \u0026gt;\u0026thinsp;80), stretching and thinning breakup (80\u0026thinsp;\u0026lt;\u0026thinsp;\u003cem\u003eWe\u003c/em\u003e \u0026lt;\u0026thinsp;350) and catastrophic breakup (\u003cem\u003eWe\u003c/em\u003e \u0026gt;\u0026thinsp;350). Theses regimes depend on the slip velocity and the droplet size. To accelerate the breakup of the droplets into ultrafine size, we designed and constructed a rapid rotating metal mesh to continuously deliver liquid that is sprayed out with a vertically blown grid-turbulence airflow, where the initial droplet size is constrained by the mesh size, resulting in a corresponding Weber number around O(10). The GTA setup initiates a bag formation process near the mesh. As the airflow continues to act on the liquid, the thin hollow bags begin to deform and stretch into elongated liquid threads. Additionally, the grid-induced turbulence further breaks up the droplets larger than the Kolmogorov scale, in accordance with Kolmogorov-Hinze theory\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Due to the high-speed airflow through the mesh holes and the intense grid-induced turbulent flows, the droplets experience three typical stages of breakup: bag formation, stretching, and turbulence-induced breakup. Under this three-stage breakup mechanism, we demonstrated that GTA can be applied as a generalized strategy for effective atomization of liquids, achieving water droplets with a Sauter mean diameter (SMD) of 4.8 \u0026micro;m. Beyond water, high-viscosity liquids such as olive oil, lubricating oil, and methyl silicone oil (with a viscosity of 990.0 cP) can be atomized by GTA. This capability holds particular importance in fields such as heavy oil atomization for combustion processes and inkjet printing technology. In these areas, the precision in droplet control is not just a matter of enhanced efficiency but also crucial for maintaining high-quality outcomes. The ability to accurately manage droplet size and distribution is key to optimizing performance in these applications, thereby underscoring the importance of advanced atomization technologies. As a result of the high-quality solution spray through GTA, we successfully manufactured ultrafine and uniform powders including milk, coffee, sugar, polymers and ceramics by spray-drying. The GTA system exemplifies a sophisticated interplay between turbulent gas and liquids, achieving high-quality two-fluid atomization.\u003c/p\u003e"},{"header":"Design and working mechanisms of GTA","content":"\u003cp\u003eGrid turbulence is a specific type of turbulence generated when fluid flows pass through a grid or a mesh-like solid structure (lower Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). It serves as a classic prototype for deepening our understanding of turbulence physics due to its reproducibility and simplicity\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. In this study, we designed a GTA system that combines grid turbulence with intensive liquid spraying, utilizing a continuously rotating mesh which carries liquid for rapid atomization (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb, c and \u003cb\u003eSupplementary Videos 1 and 2\u003c/b\u003e). The system consisted of a mesh fixed to a rotating shaft, a vessel containing liquid, and an air knife set above the mesh to provide high-speed gas blowing vertically.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFirstly, a slit in the bottom of the vessel allowed the liquid to flow out of it and be continuously and uniformly separated into the mesh cells as the mesh rotated (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb, c). With such rotating grid system, before effective atomization, bulk liquids were separated and filled into grid cells of the mesh (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). Secondly, the liquid was subsequently ejected from each mesh cell by a high-speed airflow provided by a vertically oriented air knife, forming a mist of microdroplets that vibrated and moved at exceedingly high speeds and frequencies. A clear and uniform Tyndall phenomenon could be observed during the process, indicating a stable and ultrafine liquid spray (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec and \u003cb\u003eSupplementary Videos 2\u003c/b\u003e and \u003cb\u003e3\u003c/b\u003e). To ensure full utilization of the airflow's speed and energy while avoiding significant resistance to the mesh rotation, the air knife was positioned very close to the mesh (typically\u0026thinsp;~\u0026thinsp;1 millimeters) without making direct contact.\u003c/p\u003e \u003cp\u003eIn the GTA process, the effective separation and filling of bulk liquids into the mesh grid cells are critically dependent on the wettability of the liquid on the mesh. This wettability is influenced by both the type of liquid and the material of the mesh. The meshes employed here were commercially available and economical, typically priced at ~\u0026thinsp;3 US dollars per piece (7.5-inch size), showcasing the cost-effectiveness of the GTA system. Additionally, the GTA system offers extensive flexibility in terms of both mesh count and material, including but not limited to nylon, copper, and stainless steel, making the system highly adaptable for handling various liquids with different wetting properties (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee and \u003cb\u003eSupplementary Fig.\u0026nbsp;1\u003c/b\u003e). We tested the wettability of different liquids on stainless steel meshes (\u003cb\u003eSupplementary Fig.\u0026nbsp;2\u003c/b\u003e) and the wettability of water on various material substrates (\u003cb\u003eSupplementary Fig.\u0026nbsp;3\u003c/b\u003e). Liquids with good wettability tend to spread more easily on the mesh and infiltrate the mesh pores, which facilitates efficient atomization. For liquids with relatively poor wettability, to ensure rapid and even spreading on the mesh while it is rotating quickly, we placed the vessel containing the liquid adjacent to the mesh (typically\u0026thinsp;~\u0026thinsp;1 millimeters). This setup not only supplied the liquid but also served as a scraper, effectively assisting in the application and distribution of the liquid across the mesh. This versatility, combined with the system's simplicity and financial practicality, underscores its utility in a diverse array of applications.\u003c/p\u003e \u003cp\u003eTo demonstrate the universality of the GTA strategy, we sprayed various kinds of liquids, including water (H\u003csub\u003e2\u003c/sub\u003eO), 3 wt% hydrogen peroxide in water (3 wt% H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e), ethanol, isopropanol, kerosene, crude oil, ethylene glycol, peanut oil, olive oil, lubricating oil, and methyl silicone oil (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef and \u003cb\u003eSupplementary Fig.\u0026nbsp;4\u003c/b\u003e). The high-speed camera results showed that the atomization process for all liquids was stable. All liquids were ejected from the mesh by the gas flow, forming a mist followed by high-speed oscillations of the microdroplets (\u003cb\u003eSupplementary Video 4\u003c/b\u003e). A notable aspect of our study is the broad range of liquid viscosities we successfully atomized, ranging from ~\u0026thinsp;1\u0026ndash;1000 cP (\u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e and \u003cb\u003eSupplementary Video 5\u003c/b\u003e). This demonstrates the applicability of the GTA system in various scenarios, especially in critical areas such as fuel combustion. This versatility stands out, particularly when compared to a conventional ultrasonic atomizer equipped with a 1.7 MHz ultrasonic chip, which struggled with these higher-viscosity liquids (\u003cb\u003eSupplementary Fig.\u0026nbsp;5\u003c/b\u003e and \u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e).\u003c/p\u003e"},{"header":"Three stages of liquid breakup","content":"\u003cp\u003eTo better understand the mechanisms involved in liquid fragmentation and facilitate the production of ultrafine droplets, it is first very important to understand the formation of turbulent gas flow in our GTA system. High-fidelity computational fluid dynamics (CFD) simulations (see the \u0026ldquo;\u003cb\u003eComputational fluid dynamics (CFD) simulations\u003c/b\u003e\u0026rdquo; section in the \u003cb\u003eMethods\u003c/b\u003e and \u003cb\u003eSupplementary Fig.\u0026nbsp;6\u003c/b\u003e) vividly illustrated the evolution of grid-generated turbulence as airflow progresses downstream of a grid. As the gas flow encounters the grid, the flow velocity field is significantly disturbed because of the obstacle of the grid. The flow forms a strong shear layer near the grid and produces shedding vortices immediately downstream of the grid. These vortices interact and break up into smaller scales, inducing a flow transition from laminar to turbulent as it moves downstream and forming homogeneous, isotropic turbulence (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, \u003cb\u003eSupplementary Fig.\u0026nbsp;7a\u003c/b\u003e and \u003cb\u003eSupplementary Video 6\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe simulation results were also found to be quantitatively consistent with experimental flow visualization using a smoke-wire system (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, \u003cb\u003eSupplementary Fig.\u0026nbsp;7b\u003c/b\u003e and \u003cb\u003eSupplementary Video 7\u003c/b\u003e. The details of flow visualization are provided in the \u0026ldquo;\u003cb\u003eFlow Visualization\u003c/b\u003e\u0026rdquo; section in the \u003cb\u003eMethods\u003c/b\u003e and \u003cb\u003eSupplementary Fig.\u0026nbsp;8\u003c/b\u003e). The smoke streak lines, which visualized the flow process, showed that the original laminar flow began to destabilize after passing through the mesh, forming vortices that then broke down into smaller-scale turbulent eddies.\u003c/p\u003e \u003cp\u003eThe turbulence intensity along the streamwise direction initially increased, indicating the augmentation of turbulence, and then gradually decayed, reflecting the decay of turbulence (the upper panel of Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec and the \u0026ldquo;\u003cb\u003eTurbulence Intensity and Anisotropy\u003c/b\u003e\u0026rdquo; section in the \u003cb\u003eMethods\u003c/b\u003e). As the mesh count increased, the distance from the meshes to the peak of turbulence intensity became shorter, and the turbulence decayed faster. This demonstrates the evolution of grid turbulence produced with different mesh counts. In the vorticity contour map with mesh of 150 counts, the flow field visibly became more chaotic at 0.5 mm distance from the edge of the mesh compared with meshes of 30 and 60 counts, indicating an earlier onset of turbulence (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed and \u003cb\u003eSupplementary Fig.\u0026nbsp;9\u003c/b\u003e). Meanwhile, the grid turbulence became isotropic before the turbulence intensity reached the peak (the lower panel of Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec and the \u0026ldquo;\u003cb\u003eTurbulence Intensity and Anisotropy\u003c/b\u003e\u0026rdquo; section in the \u003cb\u003eMethods\u003c/b\u003e). The isotropic turbulence has been found to promote heat and mass transfer, increasing the evaporation rate of droplets\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. As a comparison, the smoke streak lines still maintained uniform and straight indicating the laminar flow, when we removed the mesh from the sieve (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee).\u003c/p\u003e \u003cp\u003eWith such grid-turbulence flow field, we propose that the liquid underwent a three-stage process to achieve ultrafine atomization during GTA: bag formation, stretching, and turbulence-induced breakup. We used the Volume of Fluid (VOF) method to validate this process (the \u0026ldquo;\u003cb\u003eVolume of Fluid (VOF) method\u003c/b\u003e\u0026rdquo; section in the \u003cb\u003eMethods\u003c/b\u003e). First, during the early development of grid-generated turbulence, the high-speed airflow blew out from the grid, creating a significant velocity difference from the liquid spreading in the mesh cells. Such a velocity difference leads to the formation of thin, hollow liquid bags connected to the edge of the original droplets in the mesh cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Correspondingly, the formation of these bags was observed experimentally using the high-speed camera (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb and \u003cb\u003eSupplementary Video 8\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSecond, as the airflow continues to act on the liquid, the thin hollow bags begin to deform and stretch into elongated liquid threads. The VOF simulations demonstrated this stretching phase, where the liquid threads are pulled into long, thin filaments by the aerodynamic forces. During this stage, the liquid remains continuous and does not break into droplets (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003eThird, once droplets entered the turbulence region, they underwent turbulence-induced breakup (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed). At this stage, the flow field evolved into turbulence after experiencing instability, resulting in multi-scale vortices. We employed the Q criterion (see the \u0026ldquo;\u003cb\u003eQ criterion\u003c/b\u003e\u0026rdquo; in the \u003cb\u003eMethods\u003c/b\u003e), which reflects the difference between the magnitudes of the fluid vorticity and strain rate to identify the vortices. The contours of pressure fluctuations and Q show that the generation of vortices was accompanied by pressure fluctuations (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee). Lower pressure usually occurred in vorticity-dominant regions (Q\u0026thinsp;\u0026gt;\u0026thinsp;0), whereas higher pressure typically arose in strain-dominant regions (Q\u0026thinsp;\u0026lt;\u0026thinsp;0). Liquid droplets tended to concentrate in the strain-dominant regions due to the centrifugal effect (\u003cb\u003eSupplementary Fig.\u0026nbsp;10\u003c/b\u003e and \u003cb\u003eSupplementary Video 9\u003c/b\u003e). These areas exhibited high pressure and strong stretching, leading to the breakup of droplets\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Additionally, as turbulence evolved, large vortex structures disintegrated into finer vortices, with their energy cascading down to smaller scales. This process continued until reaching the dissipation scale, where the kinetic energy was ultimately dissipated (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef)\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. This process forms multi-scale distribution of vortices from the large scale to the dissipation scale. Previous studies have shown that small droplets are influenced by these multi-scale vortices, resulting in their fragmentation into smaller droplets, following the Kolmogorov-Hinze (KH) theory\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. KH theory is the cornerstone of small droplet break up in turbulence, and identifies a Hinze scale to estimate the maximum droplet size for which the surface tension forces of the droplet can resist pressure fluctuations from turbulence\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. Based on the KH theory, the Hinze scale decreases with the increasing dissipation rate of turbulence, indicating that turbulence augmentation leads to forming finer droplets (\u003cb\u003eSupplementary Note 1\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eIn a concise overview of the liquid atomization mechanism, the airflow passing through the mesh initiates a high-speed zone, resulting in the formation of thin, hollow liquid bags. The continued interaction with the liquid film causes these hollow bags to deform and stretch into elongated liquid threads. As the airflow progresses, it undergoes a gradual transition into turbulence, giving rise to vortices of varying scales with fluctuations in physical quantities. These turbulent conditions exert stress on the droplet surface, leading to further droplet breakup.\u003c/p\u003e \u003cp\u003eTaking advantages of the three-stage breakup mechanism, the GTA method proved highly effective in achieving superior atomization quality. The resulting water spray from the GTA method displayed a uniform particle size distribution, with the Sauter mean diameter (SMD) reaching 4.8 \u0026micro;m (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eg, measured using laser diffraction analysis, see the \u0026ldquo;\u003cb\u003eSpray particle size measurement\u003c/b\u003e\u0026rdquo; section in the \u003cb\u003eMethods\u003c/b\u003e). This closely rivals the particle sizes attained by commercial ultrasonic atomization, for which we tested frequencies of 1.7 MHz, 2.4 MHz, and 3.0 MHz, with the smallest droplet size achieved being 6.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25 \u0026micro;m at 3.0 MHz (\u003cb\u003eSupplementary Fig.\u0026nbsp;11\u003c/b\u003e). The GTA method also demonstrated remarkable atomization effectiveness across various liquids, achieving droplet sizes with a SMD of around 3.9 \u0026micro;m for ethanol, kerosene, and isopropanol (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eh and \u003cb\u003eSupplementary Fig.\u0026nbsp;12\u003c/b\u003e). Additionally, the GTA method showcased its capability for ultrafine atomization of a range of high-viscosity liquids, as demonstrated in the atomization of glycerol and water mixtures with varying ratios (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ei). These liquids have similar surface tensions but significantly different viscosities (\u003cb\u003eSupplementary Table\u0026nbsp;2\u003c/b\u003e). The droplet diameters remained consistently fine across different viscosities, which is challenging for ultrasonic atomization\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. These results underscore that grid turbulence substantially augments gas-liquid interactions, thereby facilitating finer atomization.\u003c/p\u003e"},{"header":"Ultrafine atomization for applications","content":"\u003cp\u003eLiquid atomization, as a method for fluid disintegration, has been widely employed in various industrial applications, including spray drying, coating, incineration, emulsion preparation, and medical devices.\u003c/p\u003e \u003cp\u003eSpray drying has been widely applied in industrial processing to fabricate uniform, spherical, and low-cost powder particles composed of a wide array of materials from polymers to ceramics\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Based on the development of GTA strategy, we have successfully demonstrated its high-performance application in spray drying for the production of ultrafine powders across various substances, including sugar, coffee, milk, phosphor, NaCl, polyvinyl alcohol (PVA), and tartrazine (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea and \u003cb\u003eSupplementary Fig.\u0026nbsp;13\u003c/b\u003e). Additionally, GTA facilitated the production of certain oxides, such as silica, alumina, zirconia, lithium cobalt nickel manganese oxide (LiNi\u003csub\u003e0.8\u003c/sub\u003eCo\u003csub\u003e0.1\u003c/sub\u003eMn\u003csub\u003e0.1\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e) and lithium lanthanum zirconium oxygen (Li\u003csub\u003e7\u003c/sub\u003eLa\u003csub\u003e3\u003c/sub\u003eZr\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e12\u003c/sub\u003e), by precursor spray drying followed by sintering (\u003cb\u003eSupplementary Figs.\u0026nbsp;14\u0026ndash;16\u003c/b\u003e). All these powders exhibited a uniform morphology and particle size distribution (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb and \u003cb\u003eSupplementary Fig.\u0026nbsp;17\u003c/b\u003e), showcasing the GTA method's potential in diverse fields, from food processing to battery material manufacturing. Its formidable capacity for high-quality, ultrafine atomization positions GTA as a versatile and efficient solution across a broad application spectrum.\u003c/p\u003e \u003cp\u003eAdditionally, we have demonstrated the superior performance of the GTA method in rapid humidification. Humidity control is critical in both industrial and living environments, with industrial humidification systems playing a vital role in regulating moisture levels and preventing production issues\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. Comparative humidification experiments revealed that GTA achieves a fast humidification rate, highlighting its promising potential for industrial applications (\u003cb\u003eSupplementary Fig.\u0026nbsp;18\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Conclusion and outlook","content":"\u003cp\u003eIn summary, we have developed a highly efficient and nozzle-free GTA strategy that enables fast, uniform and ultrafine atomization of diverse liquids based on the principle of grid turbulence. The elevated airflow velocities and turbulent fluctuations associated with grid turbulence facilitated breakup and atomization of the liquid, promoting the creation of water droplets with an SMD of 4.8 \u0026micro;m. We emphasize the flexibility of the GTA platform, particularly in its capability to atomize a wide range of liquids including those with high viscosity. This adaptability makes the GTA system extensively applicable across various domains. Its versatility in breaking up liquids of different viscosities to product ultrafine droplets not only demonstrates its technical superiority but also expands its potential applications, making it an invaluable tool in industries where precise and efficient atomization of diverse liquids is critical.\u003c/p\u003e \u003cp\u003eThe GTA platform significantly enhances the capabilities and applications of atomization technologies. Additionally, our strategic approach in linking turbulence characteristics with flow manipulation, contributing to a deeper understanding of control paradigms within fluid dynamics. This advanced comprehension of turbulent gas-liquid interactions paves the way for a host of prospective developments in practical applications. These include but are not limited to, improved fuel injection systems, more effective disinfection methods for public spaces, and the atomization of molten metal to produce ultrafine metal powders, an essential component in the evolving technology of 3D printing. Each of these applications demonstrates the far-reaching impact and potential of the GTA system in both scientific research and industrial innovation.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003eHigh-speed camera observation\u003c/h2\u003e\n \u003cp\u003eA high-speed camera (Os7, IDT Vision, USA) equipped with two F-mount lenses (ATX 16\u0026ndash;28 mm and 100 mm, Tokina, Japan) was used for the direct observation of the flow visualization process. A 100 W LED lamp (LED-100-T, Visico, China) was used to continuously illuminate the observed area, which enabled the acquisition of clear images with a short exposure time of the high-speed camera. The high-speed images were captured at different frame rates, including 2700, 4000, and 8000 fps. The analysis of the videos obtained was carried out using the Motion Studio software. All the high-speed videos were played at a frame rate of 30 fps using the images obtained at different frame rates.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eComputational fluid dynamics (CFD) simulations\u003c/h2\u003e\n \u003cp\u003eIn this study, we examined the transition from a uniform laminar airflow to turbulence induced by a grid structure, a phenomenon pivotal in the breakup of droplets. To accurately replicate this transition, a series of comprehensive three-dimensional direct numerical simulations (DNSs) were conducted. These simulations employed an in-house CFD code, which integrates the finite difference method (FDM) and the immersed boundary method (IBM), as detailed in previous works\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. The computational model and domain are illustrated in Supplementary Fig.\u0026nbsp;4, where \u003cem\u003eD\u003c/em\u003e is the separation between wire centerlines, \u003cem\u003es\u003c/em\u003e denotes the distance from the inlet to the central plane of the grid structure, \u003cem\u003eL\u003c/em\u003e is the streamwise domain length, and \u003cem\u003eW\u003c/em\u003e and \u003cem\u003eH\u003c/em\u003e specify the width and the height of the computational domain, respectively.\u003c/p\u003e\n \u003cp\u003eIn the present study, the velocity range of interest for the airflow is considerably below the speed of sound. Consequently, the airflow dynamics are governed by incompressible and isothermal Naiver-Stokes equations as follows,\u003c/p\u003e\n \u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equa\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}\\frac{\\partial\\:\\varvec{u}}{\\partial\\:\\text{t}}+\\left(\\varvec{u}\\cdot\\:\\nabla\\:\\right)u=-\\frac{1}{{\\rho\\:}_{f}}\\nabla\\:p+\\nu\\:{\\nabla\\:}^{2}u+f \\left(1\\right)\\end{array}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Equb\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equb\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}\\nabla\\:\\cdot\\:u=0\\:. \\left(2\\right)\\end{array}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eHere, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{u}\\)\u003c/span\u003e\u003c/span\u003e is the velocity of airflow, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\rho\\:}_{f}\\)\u003c/span\u003e\u003c/span\u003e represents the density of air, \u003cem\u003ep\u003c/em\u003e is the pressure, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\nu\\:\\)\u003c/span\u003e\u003c/span\u003e is the kinematic viscosity of air, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{f}\\)\u003c/span\u003e\u003c/span\u003e encapsulates the additional forces exerted on the fluid by the grid structure.\u003c/p\u003e\n \u003cp\u003eTo model the effect of the grid structure within the airflow, IBM was utilized to model the boundary of the grid structure. The surface of the grid structure was discretized into a uniform grid, with the discretization points denoted as \u003cstrong\u003eX\u003c/strong\u003e, located on the fixed boundary of the grid structure. Concurrently, a set of immersed boundaries (IB) points \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{X}}_{ib}\\)\u003c/span\u003e\u003c/span\u003e were employed to passively trace the flow, originating from the locations at \u003cstrong\u003eX\u003c/strong\u003e. To constraint IB points \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{X}}_{ib}\\)\u003c/span\u003e\u003c/span\u003e to the fixed points \u003cstrong\u003eX\u003c/strong\u003e, a weak coupling scheme was imposed by exerting IB forces \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{F}}_{L}\\)\u003c/span\u003e\u003c/span\u003eon the surface of the grid structure, as expressed in the following equation,\u003c/p\u003e\n \u003cdiv id=\"Equc\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equc\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}{\\varvec{F}}_{L}=-\\gamma\\:\\left[{\\int\\:}_{0}^{t}\\left({\\varvec{U}}_{ib}-\\varvec{U}\\right)dt+{\\Delta\\:}t\\left({\\varvec{U}}_{ib}-\\varvec{U}\\right)\\right], \\left(3\\right)\\end{array}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\gamma\\:\\)\u003c/span\u003e\u003c/span\u003e is a large constant, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varDelta\\:t\\)\u003c/span\u003e\u003c/span\u003e is the time interval of the simulation, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{U}}_{ib}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{U}\\)\u003c/span\u003e\u003c/span\u003e represent velocities of IB points \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{X}}_{ib}\\)\u003c/span\u003e\u003c/span\u003e and fixed points \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{X}\\)\u003c/span\u003e\u003c/span\u003e on boundary, respectively. Note that \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{U}\\)\u003c/span\u003e\u003c/span\u003e is set to zero during computation adhering to the no-slip velocity condition at the boundary, while \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{U}}_{ib}\\)\u003c/span\u003e\u003c/span\u003e is computed by interpolating the local fluid velocity from adjacent Eulerian grid points \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{x}\\)\u003c/span\u003e\u003c/span\u003e, as follows,\u003c/p\u003e\n \u003cdiv id=\"Equd\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equd\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}{\\varvec{U}}_{ib}=\\sum\\:u{\\delta\\:}_{h}\\left(\\varvec{X}-\\varvec{x}\\right)\\varDelta\\:V. \\left(4\\right)\\end{array}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eHere, \u003cstrong\u003eu\u003c/strong\u003e represents the fluid velocity at the Eulerian grid points \u003cstrong\u003ex\u003c/strong\u003e. The term \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varDelta\\:V={h}^{3}\\)\u003c/span\u003e\u003c/span\u003e represents the volume of each grid cell, where \u003cem\u003eh\u003c/em\u003e is the cell size. Note that the Cartesian grids encompassing the surface of grid structure are uniformly sized with \u003cem\u003eh\u003c/em\u003e in all three spatial directions. Furthermore, the delta function \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\delta\\:}_{h}\\)\u003c/span\u003e\u003c/span\u003e is formulated as\u003c/p\u003e\n \u003cdiv id=\"Eque\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Eque\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}{{\\delta\\:}}_{\\text{h}}\\left(x\\right)=\\frac{1}{{h}^{3}}\\varphi\\:\\left(\\frac{x}{h}\\right)\\varphi\\:\\left(\\frac{y}{h}\\right)\\varphi\\:\\left(\\frac{z}{h}\\right), \\left(5\\right)\\end{array}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003ewhere\u003c/p\u003e\n \u003cdiv id=\"Equf\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equf\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}\\varphi\\:\\left(r\\right)=\\left\\{\\begin{array}{c}\\frac{1}{8}\\left(3-2\\left|r\\right|+\\sqrt{1+4\\left|r\\right|-4{r}^{2}}\\right),\\:\\:\\:\\:\\:\\:\\:0\\le\\:\\left|r\\right|\u0026lt;1,\\\\\\:\\frac{1}{8}\\left(5-2\\left|r\\right|-\\sqrt{-7+12\\left|r\\right|-4{r}^{2}}\\right),\\:1\\le\\:\\left|r\\right|\u0026lt;2,\\\\\\:0,\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:2\\le\\:\\left|r\\right|\\end{array}\\right. \\left(6\\right)\\end{array}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003edenotes a four-point smoothed delta function\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eSimilarly, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{f}\\)\u003c/span\u003e\u003c/span\u003e at the Eulerian grids is derived by interpolating the forces \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{F}}_{L}\\)\u003c/span\u003e\u003c/span\u003e exerted on the surface of the grid structure, i.e.,\u003c/p\u003e\n \u003cdiv id=\"Equg\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equg\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}f=\\sum\\:{\\varvec{F}}_{L}{{\\delta\\:}}_{\\text{h}}\\left(\\varvec{x}-\\varvec{X}\\right)\\varDelta\\:V \\:\\left(7\\right)\\end{array}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eFor the flow solver, we adopted an implicit velocity decoupling procedure on staggered Cartesian grid system to solve the incompressible Navier-Stokes equations, as delineated by Kim et al\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. The computational domain of the entire fluid field is set as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:15D\\times\\:9D\\times\\:9D\\)\u003c/span\u003e\u003c/span\u003e for \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:L,W\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:H\\)\u003c/span\u003e\u003c/span\u003e, respectively. The characteristic length scale is defined by the distance between the centerlines of nearby wires, with \u003cem\u003eD\u003c/em\u003e being 25.4mm divided by the mesh count. The distance between the inlet and the center plane of the grid structure \u003cem\u003es\u003c/em\u003e is equal to \u003cem\u003eD\u003c/em\u003e. This study employs a grid resolution of 32 uniform grids per length \u003cem\u003eD\u003c/em\u003e, resulting in a total grid number of approximately 40\u0026nbsp;million. Periodic boundary conditions for velocity and pressure are imposed in both the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:y\\)\u003c/span\u003e\u003c/span\u003e and \u003cem\u003ez\u003c/em\u003e directions. The inlet velocity is uniform, expressed as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{u}={U}_{g}{\\varvec{e}}_{x}\\)\u003c/span\u003e\u003c/span\u003e, where \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{U}_{g}\\)\u003c/span\u003e\u003c/span\u003e is the airflow velocity and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{e}}_{x}\\)\u003c/span\u003e\u003c/span\u003e is the unit vector in the streamwise direction. At the outlet, a convective boundary condition is implemented. The kinematic viscosity of airflow is 1.48\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\times\\:{10}^{-5}{m}^{2}/s\\)\u003c/span\u003e\u003c/span\u003e, and the inlet airflow velocity is around 18 m/s. Three different grid structures with mesh counts of 30, 60, and 150 were simulated, yielding Reynolds numbers based on D of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:Re={U}_{g}D/{\\nu\\:}_{g}=1100\\)\u003c/span\u003e\u003c/span\u003e, 550 and 220, respectively.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003eVolume of Fluid (VOF) method\u003c/h2\u003e\n \u003cp\u003eThe Volume of Fluid (VOF) method\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e is one of the most commonly used interface capturing methods for simulating multiphase flows due to its mass conserving property, and ease in handling large interfacial deformations. In VOF framework, the different fluid phases interfaces are identified by an indicator fraction, \u003cem\u003e\u0026alpha;\u003c/em\u003e, which is chosen to be the fluid volume fraction on the Eulerian mesh. The fluid volume fraction \u003cem\u003e\u0026alpha;\u003c/em\u003e is given by\u003c/p\u003e\n \u003cdiv id=\"Equh\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equh\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}\\alpha\\:=\\left\\{\\begin{array}{c}0,\\:\\:for\\:fluid\\:A\\\\\\:0\u0026lt;\\alpha\\:\u0026lt;1,\\:\\:mixing\\:region\\:between\\:fluid\\:A\\:and\\:B\\:\\\\\\:1,\\:\\:for\\:fluid\\:B\\end{array}\\right. \\left(8\\right)\\end{array}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eIn VOF method, the fluid interface is reconstructed by the above fluid volume fraction, which is advected with the flow. The evolution of fluid volume fraction is modeled by\u003c/p\u003e\n \u003cdiv id=\"Equi\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equi\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}\\frac{\\partial\\:\\alpha\\:}{\\partial\\:t}+\\nabla\\:\\cdot\\:\\left(\\varvec{u}\\alpha\\:\\right)+\\nabla\\:\\cdot\\:\\left[\\alpha\\:\\left(1-\\alpha\\:\\right){\\varvec{U}}_{r}\\right]=0 \\left(9\\right)\\end{array}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003ein which, \u003cstrong\u003eU\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003er\u003c/strong\u003e\u003c/sub\u003e is the artificial compression velocity on the fluid interface to guarantee the sharpness of the fluid interface\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eThe effect of the surface tension of the two-phase flow is determined by the Continuum Surface Model (CSF)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e in the momentum equation and continuity equation.\u003c/p\u003e\n \u003cdiv id=\"Equj\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equj\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}\\frac{\\partial\\:\\rho\\:\\varvec{u}}{\\partial\\:t}+\\nabla\\:\\cdot\\:\\left(\\rho\\:\\varvec{u}\\varvec{u}\\right)=-\\nabla\\:{p}_{\\text{r}\\text{g}\\text{h}}-\\left(\\mathbf{g}\\cdot\\:\\mathbf{x}\\right)\\nabla\\:\\rho\\:+\\nabla\\:\\cdot\\:\\left[\\mu\\:\\left(\\nabla\\:\\varvec{u}+{\\left(\\nabla\\:\\varvec{u}\\right)}^{T}\\right)\\right]+\\sigma\\:\\kappa\\:\\nabla\\:\\alpha\\: \\left(10\\right)\\end{array}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Equk\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equk\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}\\nabla\\:\\cdot\\:u=0\\:. \\left(11\\right)\\end{array}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003ewhere \u003cem\u003e\u0026rho;\u003c/em\u003e and \u003cem\u003e\u0026micro;\u003c/em\u003e are the average density and viscosity weighted by the fluid volume fraction \u003cem\u003e\u0026alpha;\u003c/em\u003e, respectively. \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ergh\u003c/em\u003e\u003c/sub\u003e is the pressure excluding hydrostatic pressure, \u003cstrong\u003eg\u003c/strong\u003e is the gravity acceleration, \u003cem\u003e\u0026sigma;\u003c/em\u003e is the surface tension coefficient, and \u003cem\u003e\u0026kappa;\u003c/em\u003e is the mean curvature of the fluid interface.\u003c/p\u003e\n \u003cp\u003eThe mathematical models are also utilized to simulate the grid-turbulence atomization proposed in the present study. Moreover, the above multiphase flow model is solved with an open-source CFD platform, i.e., OpenFOAM. The grid structures, mesh resolution, and inlet airflow velocity are the same as those used in single-phase airflow simulation.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003eQ Criterion\u003c/h2\u003e\n \u003cp\u003eThe Q criterion is used to distinguish the vorticity-dominant region (Q\u0026thinsp;\u0026gt;\u0026thinsp;0) and strain-dominant region (Q\u0026thinsp;\u0026lt;\u0026thinsp;0). It is defined by the formula,\u003c/p\u003e\n \u003cdiv id=\"Equl\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equl\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}Q=\\frac{1}{2}\\left(Tr\\left({\\varvec{\\varOmega\\:}}^{2}\\right)-Tr\\left({\\varvec{S}}^{2}\\right)\\right), \\left(12\\right)\\end{array}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{\\varOmega\\:}\\)\u003c/span\u003e\u003c/span\u003e is the fluid rotation tensor, and expressed as,\u003c/p\u003e\n \u003cdiv id=\"Equm\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equm\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}\\varOmega\\:=\\frac{1}{2}\\left(\\nabla\\:\\varvec{u}-\\nabla\\:{\\varvec{u}}^{\\text{T}}\\right), \\left(13\\right)\\end{array}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eand \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{S}\\)\u003c/span\u003e\u003c/span\u003e is the fluid strain-rate tensor as follows,\u003c/p\u003e\n \u003cdiv id=\"Equn\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equn\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}S=\\frac{1}{2}\\left(\\nabla\\:\\varvec{u}+\\nabla\\:{\\varvec{u}}^{\\text{T}}\\right). \\left(14\\right)\\end{array}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eNote that \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\nabla\\:\\varvec{u}\\)\u003c/span\u003e\u003c/span\u003e is the fluid velocity gradient tensor, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:Tr(\\cdot\\:)\\)\u003c/span\u003e\u003c/span\u003e represents an operator of the trace.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eTurbulence Intensity and Anisotropy\u003c/h2\u003e\n \u003cp\u003eTurbulence intensity at a given position \u003cem\u003ex\u003c/em\u003e is calculated using the following formula,\u003c/p\u003e\n \u003cdiv id=\"Equo\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equo\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}I\\left(x\\right)=\\frac{{{u}^{{\\prime\\:}}\\left(x\\right)}_{rms}}{\u0026lang;U\\left(x\\right)\u0026rang;}. \\left(15\\right)\\end{array}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eHere, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{u}^{{\\prime\\:}}{\\left(x\\right)}_{rms}\\)\u003c/span\u003e\u003c/span\u003e represents the root-mean-square of the velocity fluctuations in y-z plane at position \u003cem\u003ex\u003c/em\u003e, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\u0026lang;U\\left(x\\right)\u0026rang;\\)\u003c/span\u003e\u003c/span\u003e is the ensemble-averaged velocity in y-z plane at the same position \u003cem\u003ex.\u003c/em\u003e Note that \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\u0026lang;\\cdot\\:\u0026rang;\\)\u003c/span\u003e\u003c/span\u003e represents the ensemble-averaging in y-z plane.\u003c/p\u003e\n \u003cp\u003eTurbulence anisotropy \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\eta\\:\\)\u003c/span\u003e\u003c/span\u003e is a measure used to estimate the anisotropy of Reynolds stress in turbulent flows. The Reynolds stress in y-z plane at position \u003cem\u003ex\u003c/em\u003e is denoted as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\u0026lang;{u}_{i}^{{\\prime\\:}}{u}_{j}{\\prime\\:}\u0026rang;\\)\u003c/span\u003e\u003c/span\u003e, where \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{u}_{i}{\\prime\\:}\\)\u003c/span\u003e\u003c/span\u003e is the component of fluid velocity fluctuation. The anisotropy factor \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\eta\\:\\)\u003c/span\u003e\u003c/span\u003e is defined as the second invariant of a normalized tensor\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{b}_{ij}\\)\u003c/span\u003e\u003c/span\u003e, which is calculated as,\u003c/p\u003e\n \u003cdiv id=\"Equp\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equp\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}{b}_{ij}=\\frac{\u0026lang;{u}_{i}^{{\\prime\\:}}{u}_{j}{\\prime\\:}\u0026rang;}{\u0026lang;{u}_{k}^{{\\prime\\:}}{u}_{k}{\\prime\\:}\u0026rang;}-\\frac{1}{3}{\\delta\\:}_{ij}, \\left(16\\right)\\end{array}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003enamely \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\eta\\:={b}_{ij}{b}_{ji}\\)\u003c/span\u003e\u003c/span\u003e. When \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\eta\\:\\)\u003c/span\u003e\u003c/span\u003e approaches \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:0\\)\u003c/span\u003e\u003c/span\u003e, the Reynolds stress becomes more isotropic, indicating the same statistics of fluid in any direction. Conversely, a higher \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\eta\\:\\)\u003c/span\u003e\u003c/span\u003e indicates a more anisotropic state of Reynolds stress.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eFlow Visualization\u003c/h2\u003e\n \u003cp\u003eFlow visualization was realized using a smoke-wire system in a wind tunnel (Supplementary Fig.\u0026nbsp;6), which is composed of a smoke-wire controller (SW02, Dalian Hanghua Science \u0026amp; Technology Co., Ltd, China), a resistance wire with a diameter of 0.1 mm, a flashlamp, and a digital camera (Canon 850D). In the experiment, paraffin oil was coated on the resistance wire to produce a smoke line under the control of the controller. The smoke line was blown forward in the wind tunnel and captured by the camera. The flashlamp was used to illuminate the flow field. Photographs of the smoke line\u0026apos;s trajectory characterized the flow characteristics and vortex dynamics.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eSpray Particle Size Measurement\u003c/h2\u003e\n \u003cp\u003eThe spray particle sizes, specifically the volume distribution of the droplets, were measured using a spray laser particle size analyzer (PW180-B, Shandong NKT Analytical Instrument Co., Ltd, China). The measuring axial distance was approximately 100 mm. The instrument was able to measure sprays of diverse substances by leveraging a built-in database containing material parameters. Data analysis was conducted using accompanying software provided by the manufacturer.\u003c/p\u003e\n \u003cp\u003eTo determine the average diameter of the droplets, the Sauter Mean Diameter (SMD) was used, calculated using the formula:\u003c/p\u003e\n \u003cdiv id=\"Equq\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equq\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}SMD=\\frac{\\sum\\:\\left({d}_{i}^{3}{n}_{i}\\right)}{\\sum\\:\\left({d}_{i}^{2}{n}_{i}\\right)}, \\left(17\\right)\\end{array}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{d}_{i}\\)\u003c/span\u003e\u003c/span\u003e represents the diameter of individual droplets, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{n}_{i}\\)\u003c/span\u003e\u003c/span\u003e is the number of droplets with that diameter.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eEvaluation of Humidification Efficiency of the Atomization System\u003c/h2\u003e\n \u003cp\u003eTo gauge the efficiency of the atomization system, a humidification experiment was conducted in an enclosed room of dimensions 2m \u0026times; 3m \u0026times; 4m (Supplementary Fig.\u0026nbsp;18a). The ambient humidity was initially reduced to 20% using a dehumidifier. Once this was achieved, the dehumidifier was turned off and the atomization system was activated. A digital hygrometer was employed to monitor and record the rise in humidity in real-time.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003eMorphology and structure Characterizations\u003c/h2\u003e\n \u003cp\u003eThe morphological properties and elementary composition of particles were measured by a field-emission scanning electron microscope (FE-SEM, LEO-1530, Zeiss, Germany) equipped with energy-dispersive X-ray spectroscopy (EDS). The diameter distribution of the particles was measured with a laser particle sizer (Mastersizer 3000, Malvern, UK). Crystal structure of SiO\u003csub\u003e2\u003c/sub\u003e, Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e, ZrO\u003csub\u003e2\u003c/sub\u003e, Li\u003csub\u003e7\u003c/sub\u003eLa\u003csub\u003e3\u003c/sub\u003eZr\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e12\u003c/sub\u003e, and LiNi\u003csub\u003e0.8\u003c/sub\u003eCo\u003csub\u003e0.1\u003c/sub\u003eMn\u003csub\u003e0.1\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e powder were determined by XRD (D/Max 2,500, Rigaku, Japan), where the X-ray was Cu-K\u0026alpha; radiation, scanning speed was 5\u0026deg;/min, and the scanning range was 10\u0026deg; \u0026minus;\u0026thinsp;80\u0026deg;.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eData availability\u003c/p\u003e\n\u003cp\u003eAll relevant data are contained in the manuscript, Supplementary Information, and source data.\u003c/p\u003e\n\u003cp\u003eCode availability\u003c/p\u003e\n\u003cp\u003eCustom code used in the study is available from the corresponding authors upon reasonable request.\u003c/p\u003e\n\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Basic Science Center Program of the National Natural Science Foundation of China (NSFC) under grant No. 52388201, NSFC under grant No. 52325312, 123881019, 2252104, 92252204, and 12302285, the China Postdoctoral Science Foundation (CPSF) under grant No. 2022M721849, and the Postdoctoral Fellowship Program of CPSF under\u0026nbsp;grant No.\u0026nbsp;GZB20230360.\u003c/p\u003e\n\u003cp\u003eAuthor contributions\u003c/p\u003e\n\u003cp\u003eH.W. conceived the idea and supervised the research. H.W. and Z.W.L. designed the experiments. Z.W.L. and Z.K.C designed and construct the experimental system. L.H.Z., Y.S.L, Z.W.C., and S.J.L. performed the modeling and simulations. Z.W.L., S.Y.Z., Y.H., H.Y.W., Y.C.F., Y.Q.Z, P.D., S.L., and H.W. synthesized the specimens and performed the analysis of different characterizations. Z.W.L., Z.W.C., L.H.Z., and H.W. contributed to writing the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCorresponding authors\u003c/p\u003e\n\u003cp\u003eCorrespondence to Hui Wu or Lihao Zhao.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eA patent (application number: CN202211013454.3, application date: 23 August 2022, patent status: under substantive examination) for the atomization method has been applied for on behalf of Tsinghua University. H.W. and Z.L. are listed as inventors. The invention discloses an atomization system, its usage method, and applications, which correlated with the research. The other authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLi X et al (2024) A review on the recent advances of flash boiling atomization and combustion applications. Prog Energy Combust Sci 100:101119\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJain RG et al (2022) Foliar application of clay-delivered RNA interference for whitefly control. Nat Plants 8:535\u0026ndash;548\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCao T et al (2022) H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e generation enhancement by ultrasonic nebulisation with a zinc layer for spray disinfection. Chem Eng J 431:134005\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLokugamage MP et al (2021) Optimization of lipid nanoparticles for the delivery of nebulized therapeutic mRNA to the lungs. Nat Biomed Eng 5:1059\u0026ndash;1068\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShapira T et al (2022) A TMPRSS2 inhibitor acts as a pan-SARS-CoV-2 prophylactic and therapeutic. Nature 605:340\u0026ndash;348\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Vries RD et al (2021) Intranasal fusion inhibitory lipopeptide prevents direct-contact SARS-CoV-2 transmission in ferrets. Science 371:1379\u0026ndash;1382\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSharma D et al (2021) Development of an anti-clogging perforated plate atomizer for a zero liquid discharge humidification-dehumidification desalination system. Desalination 515:115195\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXie Z et al (2023) Experimental study on the atomization characteristics and dust removal efficiency of a fan-shaped nozzle for purifying working environment. Sci Total Environ 894:164994\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu F et al (2022) Research on atomization evaporation characteristics and parameter optimization of a novel spray evaporation desalting system. Desalination 542:116057\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJiang M et al (2022) Inhibiting the Leidenfrost effect above 1,000\u0026deg;C for sustained thermal cooling. Nature 601:568\u0026ndash;572\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFigueiredo JdA et al (2022) Microencapsulation by spray chilling in the food industry: Opportunities, challenges, and innovations. Trends Food Sci Technol 120:274\u0026ndash;287\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMezhericher M, Nunes JK, Guzowski JJ, Stone HA (2018) Aerosol-assisted synthesis of submicron particles at room temperature using ultra-fine liquid atomization. Chem Eng J 346:606\u0026ndash;620\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuravev V et al (2023) Size of cerium dioxide support nanocrystals dictates reactivity of highly dispersed palladium catalysts. Science 380:1174\u0026ndash;1179\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnggara K et al (2023) Direct observation of glycans bonded to proteins and lipids at the single-molecule level. Science 382:219\u0026ndash;223\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang D, Yuan X, Gong C, Zhang X (2022) High Electric Field on Water Microdroplets Catalyzes Spontaneous and Ultrafast Oxidative C\u0026ndash;H/N\u0026ndash;H Cross-Coupling. J Am Chem Soc 144:16184\u0026ndash;16190\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJung W et al (2021) Three-dimensional nanoprinting via charged aerosol jets. Nature 592:54\u0026ndash;59\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark S et al (2021) Stabilization of liquid instabilities with ionized gas jets. Nature 592:49\u0026ndash;53\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilson JL et al (2023) Aerodynamic interactions of drops on parallel fibres. Nat Phys\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang Y et al (2022) Continuous air purification by aqueous interface filtration and absorption. Nature 610:74\u0026ndash;80\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu B et al (2023) Nanoscale Transport during Liquid Film Thinning Inhibits Bubble Coalescing Behavior in Electrolyte Solutions. Phys Rev Lett 131:104003\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eErdosy DP et al (2022) Microporous water with high gas solubilities. Nature 608:712\u0026ndash;718\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCai W et al (2019) Pantropical climate interactions. Science 363:eaav4236\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMlkvik M et al (2015) Twin-fluid atomization of viscous liquids: The effect of atomizer construction on breakup process, spray stability and droplet size. Int J Multiph Flow 77:19\u0026ndash;31\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKarnawat J, Kushari A (2006) Controlled atomization using a twin-fluid swirl atomizer. Exp Fluids 41:649\u0026ndash;663\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSovani SD, Sojka PE, Lefebvre AH (2001) Effervescent atomization. Prog Energy Combust Sci 27:483\u0026ndash;521\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePacheco C, Pina J, Saleh K (2016) Atomization of molten materials for particle coating: Prediction of mean droplet size for two-fluid nozzles. 26:1031\u0026ndash;1050\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGaete-Garret\u0026oacute;n L, Brice\u0026ntilde;o-Guti\u0026eacute;rrez D, Vargas-Hern\u0026aacute;ndez Y, Zanelli C (2018) I. Ultrasonic atomization of distilled water. J Acoust Soc Am 144:222\u0026ndash;227\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAvvaru B, Patil MN, Gogate PR, Pandit AB (2006) Ultrasonic atomization: Effect of liquid phase properties. Ultrasonics 44:146\u0026ndash;158\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLefebvre AH, McDonell VG (2017) Atomization and sprays. CRC\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu W et al (2022) Electrostatic atomization minimum quantity lubrication machining: from mechanism to application. Int J Extreme Manuf 4:042003\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang J, Zhang Y, Zhang W, Fan Z (2021) Research Progress of Electrostatic Spray Technology over the Last Two Decades. J Energy Eng 147:03121003\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee S-Y, Moiz AA, Cung KD (2018) In: Basu S (ed) Droplets and Sprays: Applications for Combustion and Propulsion. Springer Singapore, pp 277\u0026ndash;312. Avinash Kumar Agarwal, Achintya Mukhopadhyay, \u0026amp; Chetankumar Patel)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBourouiba L (2020) Turbulent Gas Clouds and Respiratory Pathogen Emissions: Potential Implications for Reducing Transmission of COVID-19. JAMA 323:1837\u0026ndash;1838\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChong KL et al (2021) Extended Lifetime of Respiratory Droplets in a Turbulent Vapor Puff and Its Implications on Airborne Disease Transmission. Phys Rev Lett 126:034502\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScharfman BE, Techet AH, Bush JWM, Bourouiba L (2016) Visualization of sneeze ejecta: steps of fluid fragmentation leading to respiratory droplets. Exp Fluids 57:24\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePallares J, Fabregat A (2022) A model to predict the short-term turbulent indoor dispersion of small droplets and droplet nuclei released from coughs and sneezes. Indoor Built Environ 31:1393\u0026ndash;1404\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDbouk T, Drikakis D (2020) On respiratory droplets and face masks. Phys Fluids 32:063303\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee CS, Reitz R, D. EFFECT, OF LIQUID PROPERTIES ON THE BREAKUP MECHANISM OF HIGH-SPEED LIQUID DROPS (2001). 11, 1\u0026ndash;19\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNi R (2024) Deformation and Breakup of Bubbles and Drops in Turbulence. Annu Rev Fluid Mech 56:319\u0026ndash;347\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHinze JO (1955) Fundamentals of the hydrodynamic mechanism of splitting in dispersion processes. AlChE J 1:289\u0026ndash;295\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKistler AL, Vrebalovich T (1966) Grid turbulence at large Reynolds numbers. J Fluid Mech 26:37\u0026ndash;47\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eErtun\u0026Ccedil; \u0026Ouml;, \u0026Ouml;Zyilmaz N, Lienhart H, Durst F, Beronov K (2010) Homogeneity of turbulence generated by static-grid structures. J Fluid Mech 654:473\u0026ndash;500\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZbicinski I, Grad J, Strumillo C (1996) Effect of Turbulence on Heat and Mass Transfer in the Atomization Zone. Dry Technol 14:231\u0026ndash;244\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLemenand T, Dupont P, Valle DD, Peerhossaini H (2013) Comparative efficiency of shear, elongation and turbulent droplet breakup mechanisms: Review and application. Chem Eng Res Des 91:2587\u0026ndash;2600\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndersson R, Andersson B (2006) Modeling the breakup of fluid particles in turbulent flows. AlChE J 52:2031\u0026ndash;2038\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNikolaevich KA (1941) The local structure of turbulence in incompressible viscous fluid for very large Reynolds. Numbers Dokl Akad Nauk SSSR\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCrialesi-Esposito M, Chibbaro S, Brandt L (2023) The interaction of droplet dynamics and turbulence cascade. Commun Phys 6:5\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQi Y et al (2022) Fragmentation in turbulence by small eddies. Nat Commun 13:469\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoel E et al (2020) Unraveling Particle Formation: From Single Droplet Drying to Spray Drying and Electrospraying. Pharmaceutics 12:625\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShehadi M (2018) Review of humidity control technologies in buildings. J Build Eng 19:539\u0026ndash;551\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang W-X, Shin SJ, Sung HJ (2007) Simulation of flexible filaments in a uniform flow by the immersed boundary method. J Comput Phys 226:2206\u0026ndash;2228\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang W-X, Chang CB, Sung HJ (2011) An improved penalty immersed boundary method for fluid\u0026ndash;flexible body interaction. J Comput Phys 230:5061\u0026ndash;5079\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeskin CS (2002) The immersed boundary method. Acta Numer 11:479\u0026ndash;517\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim K, Baek S-J, Sung HJ (2002) An implicit velocity decoupling procedure for the incompressible Navier\u0026ndash;Stokes equations. Int J Numer Methods Fluids 38:125\u0026ndash;138\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHirt CW, Nichols BD (1981) Volume of fluid (VOF) method for the dynamics of free boundaries. J Comput Phys 39:201\u0026ndash;225\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeller HG (2008) A new approach to VOF-based interface capturing methods for incompressible and compressible flow. OpenCFD Ltd Rep TR/HGW 4:35\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrackbill JU, Kothe DB, Zemach C (1992) A continuum method for modeling surface tension. J Comput Phys 100:335\u0026ndash;354\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3873446/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3873446/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cb\u003eUltrafine droplets play an important role in materials processing and nanotechnology, with crucial applications in nanoparticle preparation, molecular spraying, water evaporation, nanodrug delivery, nano-printing/coating, among numerous others. While the potential of turbulent gas flow to enhance liquid breakup is acknowledged, the construction of turbulence-driven atomizers for generating ultrafine droplets remains a significant challenge. Herein, we report the innovation of grid-turbulence atomization (GTA), which employed a rotating mesh to deliver liquid and an air knife to spray ultrafine droplets. The airflow across the mesh transitions from laminar to grid-turbulence, leading to complete liquid breakup with three-stages: bag formation, stretching, and turbulence-induced breakup. Ultrafine water droplets with a 4.8 \u0026micro;m Sauter mean diameter have been achieved through GTA\u003c/b\u003e. \u003cb\u003eThe GTA system demonstrates versatility in atomizing various liquids including those with high viscosities of ~\u0026thinsp;1000 cP. We further achieved high-quality production of ultrafine powders including milk, coffee, sugar, polymers, and ceramics, based on the combination of GTA and spray-drying. Our strategic methodology establishes pivotal link between turbulence characteristics and materials processing, influencing a wide range of applications and sparking further innovation in the field.\u003c/b\u003e\u003c/p\u003e","manuscriptTitle":"Complete breakup of liquids into ultrafine droplets by grid turbulence","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-30 05:08:05","doi":"10.21203/rs.3.rs-3873446/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"318e928d-ca30-4f0e-9b59-5daef8217ea7","owner":[],"postedDate":"September 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":38277858,"name":"Physical sciences/Materials science/Nanoscale materials"},{"id":38277859,"name":"Physical sciences/Chemistry/Chemical engineering"}],"tags":[],"updatedAt":"2024-09-30T05:08:07+00:00","versionOfRecord":[],"versionCreatedAt":"2024-09-30 05:08:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3873446","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3873446","identity":"rs-3873446","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}