Mixture Of Droplets Research Articles

Self‐organized Patterns in Non‐reciprocal Active Droplet Systems

Non‐equilibrium patterns are widespread in nature and often arise from the self‐organization of constituents through nonreciprocal chemotactic interactions. In this study, we demonstrate how active oil‐in‐water droplet mixtures with predator‐prey interactions can result in a variety of self‐organized patterns. By manipulating physical parameters, the droplet diameter ratio and number ratio, we identify distinct classes of patterns within a binary droplet system, rationalize the pattern formation, and quantify motilities. Experimental results are recapitulated in numerical simulations using a minimal computational model that solely incorporates chemotactic interactions and steric repulsion among the constituents. The time evolution of the patterns is investigated and chemically explained. We also investigate how patterns vary with differing interaction strength by altering surfactant composition. Leveraging insights from the binary droplet system, the framework is extended to a ternary droplet mixture composed of multiple chasing droplet pairs to create chemically directed hierarchical organization. Our findings demonstrate how rationalizable, self‐organized patterns can be programmed in a chemically minimal system and provide the basis for exploration of emergent organization and higher order complexity in active colloids.

Self-organized Patterns in Non-reciprocal Active Droplet Systems.

Non-equilibrium patterns are widespread in nature and often arise from the self-organization of constituents through nonreciprocal chemotactic interactions. In this study, we demonstrate how active oil-in-water droplet mixtures with predator-prey interactions can result in a variety of self-organized patterns. By manipulating physical parameters, the droplet diameter ratio and number ratio, we identify distinct classes of patterns within a binary droplet system, rationalize the pattern formation, and quantify motilities. Experimental results are recapitulated in numerical simulations using a minimal computational model that solely incorporates chemotactic interactions and steric repulsion among the constituents. The time evolution of the patterns is investigated and chemically explained. We also investigate how patterns vary with differing interaction strength by altering surfactant composition. Leveraging insights from the binary droplet system, the framework is extended to a ternary droplet mixture composed of multiple chasing droplet pairs to create chemically directed hierarchical organization. Our findings demonstrate how rationalizable, self-organized patterns can be programmed in a chemically minimal system and provide the basis for exploration of emergent organization and higher order complexity in active colloids.

Karakteristik Pembakaran Droplet Campuran Metil Oleat – Etanol dengan Penambahan Multi -Walled Carbon Nanotubes

This research intended to investigate the combustion characteristics of methyl oleic – ethanol blend with OH functionalized multi-walled carbon nanotubes (MWCNT-OH) addition. Methyl oleic is an unsaturated fatty acid methyl ester, which is a constituent of various biodiesels. The observed fuel was a mixture of Methyl oleic with 20% vol of ethanol. MWCNT-OH content was varied by 100 ppm, 200 ppm, 300 ppm, 400 ppm, and 500 ppm (wt based). The presence of ethanol in the droplets is intended to promote the microexplosion phenomenon, generating smaller droplets and a shorter burning time. The experimental results show that the MWCNT-OH addition on the droplet of Methyl oleic – ethanol blend decreased the ignition delay and droplet burning time, while the constant burning rate and droplet temperature (and flame temperature) were increased. Reducing ignition delay time due to the higher thermal conductivity of nanofluid droplets results in more effective heat absorption from the environment and better heat transport inside the droplet. Hence, droplet vaporization, flammable mixture formation and ignition occur in a shorter time. Furthermore, this condition encourages a higher burning rate and a lower droplet burning time. The higher droplet and flame temperatures are related to the higher heating value of the methyl oleic – ethanol – MWCNT-OH mixture and higher droplet burning rate, which results in a higher heat release rate.

Simulation of electronic nicotine delivery systems (ENDS) aerosol dosimetry and nicotine pharmacokinetics

Electronic nicotine delivery systems (ENDS) heat a liquid solution typically containing propylene glycol, vegetable glycerin, water, nicotine, and flavor chemicals to deliver an aerosol to the user. ENDS aerosols are complex, multi-constituent mixtures of droplets and vapors. Lung dosimetry predictions require mechanistic models that account for the physico-chemical properties of the constituents and thermodynamic processes of the aerosol as it travels through the respiratory tract and deposits in lung airways. In this study, a model formulated to predict ENDS aerosol deposition in the oral cavity and lung airways was linked with a physiologically-based pharmacokinetic (PBPK) model to predict nicotine pharmacokinetics (PK) as a function of product characteristics and puff topography. Predicted plasma nicotine PK compared favorably with available experimental data and captured the rapid increase in plasma levels followed by a clearance phase after ENDS use. E-liquid nicotine concentration and puff duration substantially increased nicotine lung deposition and plasma nicotine levels. Increasing the puff duration from 1 to 5 s while assuming a constant aerosol flow rate resulted in an ∼5-fold increase in nicotine lung deposition (45.0 µg to 243.7 µg) and increased maximum plasma nicotine concentrations from 4.7 ng/mL to 25.0 ng/mL; increasing the e-liquid nicotine concentration from 1 % to 5 % yielded increases in nicotine lung deposition (41.0 µg to 204.5 µg) and maximum plasma nicotine concentration (4.2 ng/mL to 21.1 ng/mL). Model predictions demonstrate the sensitivity of ENDS aerosol lung deposition and plasma nicotine profiles to user behavior and allow for quantification of constituent deposition and nicotine absorption after ENDS use.

Semi-supervised urban haze pollution prediction based on multi-source heterogeneous data

Particulate matter (PM) is defined by the Texas Commission on Environmental Quality (TCEQ) as “a mixture of solid particles and liquid droplets found in the air”. These particles vary widely in size. Those particles that are less than 2.5 μm in aerodynamic diameter are known as Particulate Matter 2.5 or PM2.5. Urban haze pollution represented by PM2.5 is becoming serious, so air pollution monitoring is very important. However, due to high cost, the number of air monitoring stations is limited. Our work focuses on integrating multi-source heterogeneous data of Nanchang, China, which includes Taxi track, human mobility, Road networks, Points of Interest (POIs), Meteorology (e.g., temperature, dew point, humidity, wind speed, wind direction, atmospheric pressure, weather activity, weather conditions) and PM2.5 forecast data of air monitoring stations. This research presents an innovative approach to air quality prediction by integrating the above data sets from various sources and utilizing diverse architectures in Nanchang City, China. So for that, semi-supervised learning techniques will be used, namely collaborative training algorithm Co-Training (Co-T), who further adjusting algorithm Tri-Training (Tri-T). The objective is to accurately estimate haze pollution by integrating and using these multi-source heterogeneous data. We achieved this for the first time by employing a semi-supervised co-training strategy to accurately estimate pollution levels after applying the U-air system to environmental data. In particular, the algorithm of U-Air system is reproduced on these highly diverse heterogeneous data of Nanchang City, and the semi-supervised learning Co-T and Tri-T are used to conduct more detailed urban haze pollution prediction. Compared with Co-T, which train time classifier (TC) and subspace classifier (SC) respectively from the separated spatio-temporal perspective, the Tri-T is more accurate with a and faster because of its testing accuracy up to 85.62 %. The forecast results also present the potential of the city multi-source heterogeneous data and the effectiveness of the semi-supervised learning. We hope that this synthesis will motivate atmospheric environmental officials, scientists, and environmentalists in China to explore machine learning technology for controlling the discharge of pollutants and environmental management.

The role of soil dispersivity and initial moisture content in splash erosion: Findings from consecutive single-drop splash tests

Dispersive soil is commonly associated with hydraulic erosion due to its tendency to disperse when in contact with water. Nevertheless, the erosion process of dispersive soil remains poorly understood. This study aims to explore the influence of dispersivity and initial moisture content on the splash erosion of dispersive soil, which is a crucial stage of hydraulic erosion. Consecutive single-drop splash tests were conducted on artificially prepared dispersive soil (made by adding sodium carbonate to the soil) with varying dispersivity levels and moisture contents. A high-speed and a single-lens reflex (SLR) camera were employed to capture the process of erosion in exquisite detail. The results demonstrated the significant influence of dispersivity on splash erosion. At moisture content below 20%, increased dispersivity weakened the splash erosion effect, leading to reduced infiltration, splashed soil mass, crater volume, and depth. Conversely, when the initial moisture content reached 20% or saturation, intensified dispersivity exacerbated splash erosion. Dispersivity also increased the sensitivity of the soil splash process to changes in moisture content. Dispersive soil exhibited greater sensitivity compared to non-dispersive soil, affecting the mass of splashed soil, soil-water mixture droplets area, water-soil mass ratio, and particle ejection distance. Dispersivity also caused splashed particles to fragment, resulting in more soil-water mixture droplets and a greater splash distance. Furthermore, dispersivity reduced infiltration ratio and increased runoff yield after erosion events, indicating a higher risk of transporting splashed soil particles through runoff. These insights contribute to erosion models and have practical applications in managing dispersive soil.

Interaction of Acoustic Waves with a Layer of Multifractional Polydispersed Vapor–Gas–Droplet Mixture with Account of Phase Transitions

Interaction of Acoustic Waves with a Layer of Multifractional Polydispersed Vapor–Gas–Droplet Mixture with Account of Phase Transitions

Solutal and Gravitational Effects during Binary Mixture Droplets Evaporation

Solutal and Gravitational Effects during Binary Mixture Droplets Evaporation

Evaporation dynamics of a binary mixture droplet subjected to forced convection

Evaporation of binary mixture droplets (BMDs) is a ubiquitous natural phenomenon with numerous industrial applications. In this study, a theoretical model of BMD evaporation under forced convection is established by considering the influence of evaporative cooling, thermal and Marangoni effects, convection, and a Stefan flow. The dynamic evaporation of a binary ethanol–water droplet on a heated substrate is simulated, and the internal and external flow structures of the droplets and their interactions are investigated. The influence of temperature-dependent physical properties on the evaporation dynamics is analyzed, and the effect of the forced convection intensity on the exclusion distance and Marangoni instability is explored. Our findings reveal that, during the stable flow stage, a single vortex flow pattern prevails, characterized by a circulating zone with low ethanol concentration within the droplets. However, in the Marangoni instability-driven flow (MIF) stage, a complex multi-vortex flow appears inside the droplets, with a heterogeneous ethanol distribution. Under the action of the Stefan flow, external forced convection cannot directly affect the flow inside the droplets through viscous shear but indirectly impacts the internal flow through heat and mass transfer. The temperature-dependence of physical properties significantly influences the internal flow and delays the onset of the MIF stage. Forced convection affects the heat and mass transfer by changing the thickness of the thermal and concentration boundary layers. Compared with BMD evaporation under natural convection, the heat and mass transfer rate are significantly higher under forced convection, particularly in the MIF stage.

Measurement of Fugitive Particulate Matter Emission: Current State and Trends

Fugitive particulate matter (FPM) refers to a mixture of solid particles and liquid droplets that are released into the air without passing through confined flow equipment. These emissions of FPM can originate from natural processes and anthropogenic activities. FPM emissions are an important source of PM2.5. Precisely measuring the size, concentration, and other properties of such particulate matter is crucial for effectively controlling emission sources and improving air quality. However, compared with particulate matter emission from stationary sources, it is difficult to monitor the FPM effectively owing to its dispersive and irregular emissions. Traditional measuring methods for FPM are based on sampling, which is a point monitoring approach and can be time-consuming. In recent years, several new techniques based on optical principles, image-based processes and low-cost sensors have been developed and applied for FPM measurement, with the advantages of spatial and time resolutions. The current state and future development of FPM measurements are reviewed in this paper.

Development of a multi-stage model for freezing of a suspended binary solution droplet

The importance of developing spray freeze-drying technology for extending the shelf life of biological and pharmaceutical materials has never been greater, given the increasing food shortage and the strong demand for pharma processes. In particular, the optimal thermal design and application of spray freeze-drying technologies now depend on the estimation of nucleation behavior for droplet solidification (especially the droplets of binary mixtures). Although earlier nucleation models could estimate the nucleation rate and temperature of solidifying droplets, few considered extreme environmental factors, such as extremely low ambient temperatures below −60C∘. To ensure the preservation and storage of biological and pharmaceutical products, such as vaccines and protein drugs, these conditions are essential. Hence, developing an accurate and trustworthy mathematical framework for simulating nucleation is paramount. In this study, a multi-stage, hybrid analytical-numerical model for droplet solidification is developed while coupled with a gradient-based optimization algorithm. Specifically, the five-stage solidification of binary mixtures is simulated (including supercooling of liquid, nucleation, recalescence, equilibrium freezing, and subcooling of solid), which captures the dynamic behaviors of temperature and composition or solute concentration during phase change. The heterogeneous nucleation of a binary-mixture droplet in a frigid environment is predicted and validated against a series of experiments on single suspended droplets at a wide range of ambient temperatures between −20 and −160C∘. The freezing curves of different solute concentrations are also validated against experimental data. It is found that significant variations in interfacial tension lead to abrupt changes in nucleation temperature for extremely cold environments. Further, the effects of the concentration, contact angle, droplet size, and heat transfer coefficient are investigated.

Study of a Thermal Detonation Wave in a Mixture of Water Droplets and Molten Lead

Study of a Thermal Detonation Wave in a Mixture of Water Droplets and Molten Lead

Drying of sessile droplets of binary colloidal aqueous mixtures of carbon nanotubes and platelets of Laponite®

Drying of sessile droplets of binary colloidal aqueous mixtures of carbon nanotubes (CNT) and platelets of Laponite® (Lap) has been studied. The concentration of CNT was fixed at CCNT= 0.01% wt., and the relative concentration of Lap and CNT, was varied within x = CLap/CCNT= 0–2. Formation of the three different zones related to formation of the almost transparent round "enlightenment" in the center, outer “gray” ring, and thin “coffer” ring at the external boundary was detected. Observed effects were explained accounting for the effects of Lap on the facilitation of dispersion of CNT in aqueous systems.

Acoustic attenuation in mixtures of air and water droplets

Sound propagation through mixtures of air and water-droplets occurs in many natural systems such as in fogs and clouds, where it has been observed that acoustic waves are attenuated to a greater degree than in the absence of water droplets. This effect has been exploited at space shuttle launches with the sound suppression system, where water sprayed around the shuttle significantly reduces the acoustic power radiated from the rocket engines. Theoretical studies have investigated various mechanisms causing acoustic attenuation in air-water droplet mixtures: heat transfer, mass transfer and momentum transfer. More recent studies have incorporated other mechanisms into analytical models so that they are more representative of sound propagation through fogs or clouds. The aim of this paper is to review the different mechanisms causing attenuation of acoustic waves, and to present a comparison of the different analytical models to illustrate the differences in predicted acoustic attenuation and dispersion. Some limitations of the different models are identified, and proposals for experimental work to validate analytical results are discussed.

Impurities in quasi-one-dimensional droplets of binary Bose mixtures

Impurities in quasi-one-dimensional droplets of binary Bose mixtures

Effect of iso-propanol additive on the impact dynamics of a Leidenfrost water droplet

This paper experimentally investigated the Leidenfrost dynamics of an impacting droplet of water and 2–8 vol% iso-propanol-water solutions in the film boiling regime up to 450 °C. A single millimetric droplet was released from a height of several centimeters to yield different impact velocities. The aim of the present study was to clarify the influence of iso-propanol additive on the dynamic Leidenfrost point temperature, maximum spreading factor and nondimensional residence time, which remains to be verified. Visualization study with high-speed imaging indicated that the droplet impact pattern depends on both surface temperature and iso-propanol additive. It was shown that the dynamic Leidenfrost point temperature increases with impact velocity, and was significantly elevated with a small amount of iso-propanol additive by approximately 40 °C at the same Weber number. Especially, the lowest value of the mixture droplet with the smallest impact momentum (430 °C at 0.44 m/s and We = 6.2–8.3) still surpassed the highest value of the water droplet with the largest impact momentum (410 °C at 1.33 m/s and We = 55.0) within the present test range. Meanwhile, the iso-propanol additive markedly enhanced the droplet spreading ability, which was speculated to be caused by lower surface energy. Results also demonstrated that the nondimensional residence time was highly dependent on the impact velocity, but was not significantly influenced by the iso-propanol additive. Empirical correlations of the maximum spreading factor and nondimensional residence time were proposed with satisfactory predictive accuracy and good universality.

Marangoni instability of an evaporating binary mixture droplet

Evaporation of a binary mixture droplet (BMD) is a common natural phenomenon and widely applied in many industrial fields. For the case of a sessile BMD being the only contact-line pinning throughout an entire evaporation, a theoretical model describing the evaporating dynamics is established when considering the comprehensive effect of evaporative cooling, the thermal Marangoni effect, the solutal Marangoni effect, the convection effect, and the Stefan flow. The dynamics of a binary ethanol–water droplet on a heated substrate is simulated using a cylindrical coordinate system. The reasons for Marangoni instability-driven flow (MIF) are discussed, and the influence of initial ethanol concentration and substrate heating temperature are examined. An evaporating BMD first forms a MIF at the contact line and quickly affects the whole droplet. Under the influence of the Marangoni instability, the BMD presents a complex internal flow structure with multiple-vortex and nonlinear temperature and ethanol concentration distributions. The positive feedback induced by vortices and the nonlinear distribution of concentration and temperature promotes the development of a MIF. At low initial ethanol concentrations, the MIF loses its driving force and turns into a stable counterclockwise single-vortex flow as ethanol evaporates completely. However, at high initial ethanol concentrations, the MIF exists in the entire evaporation. Increasing ethanol concentration and substrate heating temperature can delay the appearance of the MIF; ethanol concentration affects the MIF duration time, and heating temperature alters the MIF intensity. To enhance flow intensity and mass transfer of BMDs, the temperature difference should first be increased, followed by increased ethanol concentration.

Surface plasmon resonance imaging for analyzing the local variation of evaporation flux of multiple binary mixture droplets

This study investigates the local variation of concentration and selective evaporation flux affected by the droplet-to-droplet distance during the evaporation of multiple-binary mixture droplets (M-BMDs). Surface plasmon resonance imaging (SPRi) is used to measure the local liquid concentration of the binary mixture droplets and to analyze the spatial distributions of liquid concentration with the estimated local changes of surface tension during evaporation. In addition, we conduct three-dimensional numerical simulations to predict the ethanol vapor distributions and the local ethanol evaporation flux for single- and multiple-binary mixture droplets. It was found that the total evaporation time of M-BMDs is delayed due to vapor accumulation in the region adjacent to the neighboring droplets for M-BMDs, which significantly reduces the local evaporation flux. Also, the local liquid concentration of M-BMDs was found to vary, showing a lower ethanol concentration far away from the adjacent region due to vapor shielding and selective evaporation. Moreover, the scaled lifetime, which is the ratio of evaporation time between multiple droplets and a single droplet, shows good agreement with the previously reported experiments and theoretical models.

Characteristic and function of the dynamic Al-AlN core-shell structure in Al-Al2O3 composite at elevated temperature

An Al-AlN core-shell structure with spatial confinement effect is set up in Al-Al2O3 composite by pre-nitriding at 580 °C in flowing nitrogen. Its detailed characteristic and function evolution was examined over the temperature range from 600 °C to 1500 °C. With the temperature increase, the as formed Al-AlN core-shell structure in the composite undergoes two typical stages. First, from 660 °C to 900 °C, AlN shell is intact and serves as an “eggshell” to localize the molten Al core inside. When the temperature rises above 900 °C, AlN shell begins to crack under thermal stress, and the micronized Al cluster (mixture of droplets and vapor) was extracted out gradually. In this period, AlN shell serves as a slowly-released structure to control the gradual exposure of Al core and their conversion to highly-reactive micronized Al(l) and Al(g). On this basis, the controllable synthesis of AlN-based reinforcements can be realized by adjusting the nitriding path of Al with different states and scales. The detailed analysis of the dynamic Al-AlN core-shell structure at elevated temperature contributes to the better phase and morphology control of the Al-Al2O3 composite for metallurgy.

Selective evaporation and contact line motions of evaporating ethylene glycol–water mixture droplets

The evaporation of sessile binary mixture droplets with different volatile liquids is essential in various applications such as ink-jet printing, evaporators, fuel combustion, and medical diagnosis. The present study examined the evaporating characteristics of ethylene glycol–water binary mixture droplets (EGWBMDs) used for patterning the functional materials in inkjet printing. In particular, the study focused on selective evaporation and dynamic contact line motion. To this end, surface plasmon resonance and shadowgraph imaging methods were employed to measure the temporal ethylene glycol concentrations and droplet shapes, respectively. The results revealed that EGWBMDs evaporated in the depinning mode following the constant contact radius mode. The ethylene glycol concentrations increased with time; evaporation of water was dominant throughout concentration measurement, showing selective evaporation. In addition, there was a non-linear change in the volume of EGWBMDs due to the different volatility of each component. In particular, the volume variation changed rapidly at the initial stage. Next, the evaporation rates of water and ethylene glycol were quantitatively calculated based on the ethylene glycol concentration and droplet shape measurement. The evaporation rate obtained from the experiment was found to be consistent with the predictions obtained using a diffusion model, with maximum and average error rates of 6.14 and 2.56%, respectively.