Droplet Collection Research Articles

A rapid prediction method for water droplet collection coefficients of multiple airfoils based on incremental learning and multi-modal dynamic fusion

The calculation of the water droplet collection coefficient (WDCC) is a crucial step in the numerical study of aircraft icing and the iterative design of anti-icing and deicing systems. Rapid and efficient methods for predicting WDCC are essential for enhancing the efficiency of icing numerical calculations and accelerating the design cycle of these systems. The existing prediction methods are inefficient and fail to meet the real-time requirements of engineering applications. This paper proposes a rapid prediction method for the WDCC for multiple airfoils utilizing deep learning techniques. The method takes enhanced airfoil section images and icing condition parameters as inputs and WDCC as output. A deep neural network prediction model, IncDynamicFusion, for sustainable learning is established by integrating a multimodal dynamic fusion method with an improved iCaRL method (incremental classifier and representation learning). Numerical experimental results demonstrate that the proposed model can quickly and effectively predict the WDCC of multiple airfoils.

Water collection through a directional leaf vein pattern by fast laser marker ablation of stainless-steel

Inspired by the natural water harvesting mechanisms of desert beetles, cactus thorns, and leaf veins, we designed a heterogeneous wettability surface with superhydrophilic pattern integrating leaf vein as the directional water transport main channel, attached capillary triangles as auxiliary channel plus a deep rough desorption channel on an overall superhydrophobic surface for an efficient water collection. A superhydrophilic surface was initially fabricated on the stainless steel disc by laser marker ablation allowing 1 μL droplet to spread completely to 0° within 0.12 seconds, followed by fluorine-containing coating transforming superhydrophilic surface to superhydrophobic one. Directional water transport patterns were then etched on the superhydrophobic surfaces by the secondary laser marker. The surface energy gradient and Laplace pressure induced by the pattern facilitated directional fast transport and efficient desorption of droplets, thus improving water collection efficiency. The enhancement mechanism of the water harvesting behavior for such surfaces was analyzed, with one focus on enhancing collection in hydrophobic regions with capillaries to reduce bouncing off loss and the other on improving balanced cycling of the collection process. At a fog flow rate of 1500ml/h and 20cm away from the fog outlet, the directional leaf vein-patterned 19.625cm2 sized surface demonstrated a fog water collection rate (WCR) of 5.6 Kg·m-2·h-1 and first drop collection at the 49th s, an impressively short time rarely reported. Compared to the superhydrophobic, superhydrophilic samples, and the reference, WCR increased by 180%, 62%, and 59%, respectively, and the first droplet collection time decreased by 73%, 46%, and 62%, respectively. This efficient water collection method has huge potential in arid regions.

Thermoresponsive nanofiber yarns for water harvesting enhanced by harp system

The escalating global water crisis necessitates innovative approaches to developing sustainable water resources. Fog water collectors with variable surface wettability offer controlled fog harvesting in water-scarce regions. This study develops thermoresponsive fog collecting materials by electrospinning poly(N-isopropylacrylamide)-polyvinylidene fluoride (PNIPAm-PVDF) into yarns that are transformed into harp-like structures for enhanced water harvesting rate. Both meshes and harps using electrospun membranes exhibit the remarkable ability to transition between hydrophilic and hydrophobic wetting states at temperatures below the lower critical solution temperature (LCST). Hydrophilic and hydrophobic surfaces play distinct roles in fog water collection. Hydrophilic surfaces have a high affinity for water and enables droplet capture. Hydrophobic surfaces help the removal of aggregated water droplet and fog water collection. The highest water collection rate obtained with the electrospun PNIPAm-PVDF harp was 1415 ± 7.0 mg·cm−2 h−1. The water harvesting system based on the electrospun PNIPAm-PVDF harps exhibits a 485 % increase in water collection compared to the standard meshes made from the same material, emphasizing their potential for significantly improving the overall rate in fog water harvesting applications.

Porous Spindle-Knot Fiber by Fiber-Microfluidic Phase Separation for Water Collection and Nanopatterning.

Porous spindle-knot structures have been found in many creatures, such as spider silk and the root of the soybean plant, which show interesting functions such as droplet collection or biotransformation. However, continuous fabrication of precisely controlled porous spindle-knots presents a big challenge, particularly in striking a balance among good structural controllability, low-cost, and functions. Here, we propose a concept of a fiber-microfluidics phase separation (FMF-PS) strategy to address the above challenge. This FMF-PS combines the advantages of a microchannel regulated Rayleigh instability of polymer solution coated onto a fiber with the nonsolvent-induced phase separation of the polymer solution, which enables continuous and cost-effective production of porous spindle-knot fiber (PSKF) with well-controlled size and porous structures. The critical factors controlling the geometry and the porous structures of the spindle-knot by FMF-PS have been systematically investigated. For applications, the PSKF exhibited faster water droplet nucleation, growth, and maximum water collection capability, compared to the control samples, as revealed by in situ water collection growth curves. Furthermore, high-level fabrics of the PSKFs, including a two-dimensional network and three-dimensional architecture, have been demonstrated for both large-scale water collection and art performance. Finally, the PSKF is demonstrated as a programmable building block for surface nanopatterning.

Improving supercooled liquid water representation in the microphysical scheme ICE3

AbstractMost numerical weather prediction (NWP) models have a significant bias in predicting supercooled liquid water (SLW). For this reason, icing risk diagnostic tools do not use supercooled liquid water forecast by the models as an input parameter, but rather temperature and humidity, which are forecast better than SLW. The main objective of this study is to improve the SLW representation in the microphysical scheme ICE3 (Three Ice categories) used in the operational Applications de la Recherche à l'Opérationnel à Méso‐Echelle (AROME) model. For this purpose, several parametrizations of the microphysical processes were evaluated to find a better representation of SLW in the Mesoscale Non‐Hydrostatic model (MESO‐NH), which also uses ICE3. Elements of the microphysical scheme of the HARMONIE‐AROME model and work carried out by the Centre National de Recherches Météorologiques (CNRM) have been tested and compared with the current scheme. After a preliminary study, three parametrizations of the microphysical scheme were selected, in which the processes of ice initiation, snow and graupel collection of cloud droplets, condensation, Bergeron–Findeisen, and saturation adjustment were modified. Then, MESO‐NH simulations were performed and compared with observations from the In‐Cloud ICing and Large‐drop Experiment (ICICLE) airborne campaign. Three case studies were used with different icing weather conditions such as freezing rain, freezing drizzle, lake effect, etc. The results show a better representation of SLW with a greater presence of cloud droplets for colder temperatures up to 30 C. However, the liquid water content remains underestimated and the ice mass is overestimated. The ice initiation and cloud droplet collection by snow and graupel play a major role in the SLW representation. Parametrizations with restrictive ice initiation criteria reduce cloud droplet consumption and provide better agreement with observations. The results are promising and need to be investigated further with more cases and in the operational model AROME.

Testing the performance of tubular solar still with flat basin, cords wick basin, and various angle of inclinations

Freshwater scarcity is a growing concern due to population expansion and industrial development. Solar stills offer a solution for generating potable water, although production volumes are limited. This research aims to address this challenge by improving the yield, thermal efficiency, and cost-effectiveness of freshwater production in tubular solar stills (TSS). We propose a novel approach that incorporates wick materials within the TSS design. This method involves creating a specific number of cuts (cracks) in a secondary basin liner positioned 2.5 cm above the original liner within the still. The upper liner is extended with wick, and wicking cords are suspended from edges and openings of this liner. These cords continuously remove saltwater, ensuring a consistently moist wick surface. The design of the wick cords optimizes water utilization and minimizes energy waste. The cords extract precisely the amount of saline water needed for evaporation, eliminating the loss or overflow of hot water. This approach maximizes wick efficiency without sacrificing freshwater production. The study investigates the performance of the TSS using 32 wick cords in conjunction with jute wick material. This modification to the conventional TSS offers a simple and cost-effective method to enhance productivity. Additionally, the glass cover of the still is tilted at an angle to facilitate the collection of distilled water droplets. ICWTSS was used as a code name for the modified TSS. After that, three distinct inclination angles (2°, 4°, and 6°) were examined, and the effectiveness of ICWTSS at each angle was contrasted with that of CSS. With a 6° angle of inclination, the ICWTSS showed a 67 % thermal efficiency and a 257 % increase in production over CSS.

Influence of air flow field computation on an ice accretion simulation of airfoils

Ice accretion simulation is an important research technology for aircraft icing problems. Air flow field prediction of an iced aircraft is an essential step of ice accretion simulation. However, commonly used turbulence models have difficulty predicting the large flow separation of the iced aircraft, which makes air flow field calculation insufficiently accurate and further affects the ice accretion simulation. In this paper, the influence of air flow field computation on ice accretion simulation of airfoils is numerically studied. Several different turbulence models are applied to predict air flow fields of iced airfoils. Then, the Eulerian method of water droplets, integral boundary layer method and Myers model are used to simulate ice accretion. Different airfoils with several icing conditions, including glaze ice and rime ice cases, are numerically tested and compared with experimental data. The results show that the separating shear layer fixed k−ω model is more accurate than other turbulence models in predicting the pressure distribution of the iced airfoil, especially the leading-edge suction peak. Thus, a more reasonable droplet collection efficiency distribution and convective heat transfer distribution can be obtained, yielding a more consistent ice height compared with the experimental data.

Droplet collection efficiencies inferred from satellite retrievals constrain effective radiative forcing of aerosol–cloud interactions

Abstract. Process-oriented observational constraints for the anthropogenic effective radiative forcing due to aerosol–cloud interactions (ERFaci) are highly desirable because the uncertainty associated with ERFaci poses a significant challenge to climate prediction. The contoured frequency by optical depth diagram (CFODD) analysis supports the evaluation of model representation of cloud liquid-to-rain conversion processes because the slope of a CFODD, generated from joint MODerate Resolution Imaging Spectroradiometer (MODIS)-CloudSat cloud retrievals, provides an estimate of cloud droplet collection efficiency in single-layer warm liquid clouds. Here, we present an updated CFODD analysis as an observational constraint on the ERFaci due to warm rain processes and apply it to the U.S. Department of Energy's Energy Exascale Earth System Model version 2 (E3SMv2). A series of sensitivity experiments shows that E3SMv2 droplet collection efficiencies and ERFaci are highly sensitive to autoconversion, i.e., the rate of mass transfer from cloud liquid to rain, yielding a strong correlation between the CFODD slope and the shortwave component of ERFaci (ERFaciSW; Pearson's R=-0.91). E3SMv2's CFODD slope (0.20 ± 0.04) is in agreement with observations (0.20 ± 0.03). The strong sensitivity of ERFaciSW to the CFODD slope provides a useful constraint on highly uncertain warm rain processes, whereby ERFaciSW, constrained by MODIS-CloudSat, is estimated by calculating the intercept of the linear association between the ERFaciSW and the CFODD slopes, using the MODIS-CloudSat CFODD slope as a reference.

Research on icing scaling technology for large civil aircraft icing wind tunnel test

This article explores the icing scaling technology for large civil aircraft icing wind tunnel tests. Based on the typical critical icing conditions of large civil aircraft and the calibration of icing wind tunnel, and through the similarity analysis of water droplet trajectories, water collection, and energy balance, four similar parameters, namely modified inertia parameter, drop energy transfer parameter, stagnation freezing coefficient, and accumulation parameter, were selected as similarity criteria for icing scaling. Based on this criteria, icing scaling was conducted on the critical icing conditions of large civil aircraft, and the scaling results were evaluated by icing code. The results show that the water droplet collection and the ice shape before and after the scaling are in good agreement, and the similarity criteria used are appropriate. Finally, icing wind tunnel test was conducted in 3m × 2m test section using scaled icing conditions. The test results show that the main characteristics of the experimental ice shape are in good agreement with the calculated ice shape, and the calculated ice shape is more critical. The calculated ice shape can be used as a critical ice for aerodynamic wind tunnel tests and flight tests with simulated ice.

An Active Strategy Based on Different Droplet Removal Modes on Polydimethylsiloxane Magnetic Microstructures.

The efficient removal of droplets on solid surfaces holds significant importance in the field of fog collection, condensation heat transfer, and so on. However, on current typical surfaces, droplets are characterized by a passive and single removal mode, contingent on the traction force (e.g., capillary force, Laplace pressure, etc.) generated by the surface's physics and chemistry design, posing challenges for enhancing the efficiency of droplet removal. In this paper, an effective active strategy based on different removal modes is demonstrated on magnetic responsive polydimethylsiloxane (PDMS) superhydrophobic microplates (RM-MPSM). By regulating the parameters of microplates and droplet volume, different effective departure modes (top jumping and side departure) can be induced to facilitate the removal of droplets. Moreover, the removal volume of droplets through the side departure mode exhibits a significant reduction compared to that observed in the top jumping mode. The exceptional removal ability of RM-MPSM demonstrates adaptability to diverse functional applications: efficient fog collection, removal of condensation droplets and micro-particles. The efficient modes of droplet removal demonstrated in this work hold significant implications for broadening its application in many fields, such as droplet collection, heat transfer, and anti-icing.

A Lagrangian meshfree model for solidification of liquid thin-films

In this paper, a new method to model solidification of thin liquid films is proposed. This method is targeted at applications like aircraft icing and tablet coating where the formation of liquid films from impinging droplets on a surface form a critical part of the physics of the process. The proposed model takes into account the (i) unsteadiness in temperature distribution, (ii) heat transfer at the interface between the solid and the surface, (iii) volumetric expansion/contraction and (iv) the liquid thin-film behaviour, each of which are either partly or fully ignored in existing models. The liquid thin-film, modelled using the Discrete Droplet Method (DDM), is represented as a collection of discrete droplets that are tracked in a Lagrangian sense. The height of the liquid film is estimated as a summation of Gaussian kernel functions associated with each droplet. At each droplet location, a solid height is also computed. The evolution of the solid height is governed by the Stefan problem. The flow of the liquid thin-film is solved just as in the case of DDM, while also taking into consideration the shape of the solidified region lying beneath the droplet. The results presented in this work show the reliability of the proposed model in simulating solidification of thin-films and its applicability to complex problems such as ice-formation on aircraft wings. The model has been verified for canonical problems that have analytical solutions. For the more complex problems of icing, the results of the model are compared with data from literature, without considering a background air flow. The comparison can be improved by coupling this model with suitable air flow solvers, as shown in the final test case.

Research on enhancing separation of ultra‐fine droplets using turbulators between adjacent demister plates in WFGD systems

AbstractTo enhance the performance of demister applied in wet flue gas desulphurization systems, flow turbulators are equipped between adjacent plates to reconstruct flow field. Both experimental and numerical approaches are employed to investigate the influence of various kinds of turbulator configurations upon removal of droplets within the range of 5–50 μm obeying Rosin‐Rammler distribution. Turbulators including spoiler, square column, concave groove, perforated concave groove, and triangular and cylinder columns are compared, among which spoiler provided the highest overall efficiency while square column yields the best graded efficiency for 5 μm droplets group. Furthermore, moving the spoiler towards the core region of the demister ducts received better performance due to augmented interaction between spoiler and drainage channels, which performed an essential role in droplets collection. Based on this knowledge, spoilers are optimized by changing their angle of attack and size; the result is positive since overall separation efficiency can be improved to 100%, along with graded efficiencies for 10 and 5 μm groups achieving 95.97% and 27.26%, respectively, much higher than those of baseline demister without turbulators. This study indicates that inertial‐based demisters have great potential in separating ultra‐fine droplets through reorganizing turbulence field, thus extra system loss can be avoided by abandoning additional filter components.

Parameterizing Raindrop Formation Using Machine Learning

Abstract Raindrop formation processes in warm clouds mainly consist of condensation and collision–coalescence of small cloud droplets. Once raindrops form, they can continue growing through collection of cloud droplets and self-collection. In this study, we develop novel emulators to represent raindrop formation as a function of various physical or background environmental conditions by using a sophisticated aerosol–cloud model containing 300 droplet size bins and machine learning methods. The emulators are then implemented in two microphysics schemes in the Weather Research and Forecasting Model and tested in two idealized cases. The simulations of shallow convection with the emulators show a clear enhancement of raindrop formation compared to the original simulations, regardless of the scheme in which they were embedded. On the other hand, the simulations of deep convection show a more complex response to the implementation of the emulators, in terms of the changes in the amount of rainfall, due to the larger number of microphysical processes involved in the cloud system (i.e., ice-phase processes). Our results suggest the potential of emulators to replace the conventional parameterizations, which may allow us to improve the representation of physical processes at an affordable computational expense. Significance Statement Formation of raindrops marks a critical stage in cloud evolution. Accurate representations of raindrop formation processes require detailed calculations of cloud droplet growth processes. These calculations are often not affordable in weather and climate models as they are computationally expensive due to their complex dependence on cloud droplet size distributions and dynamical conditions. As a result, simplified parameterizations are more frequently used. In our study we trained machine learning models to learn raindrop formation rates from detailed calculations of cloud droplet evolutions in 1000 parcel-model simulations. The implementation of the developed models or the emulators in a weather forecasting model shows a change in the total rainfall and cloud characteristics, indicating the potential improvement of cloud representations in models if these emulators replace the conventional parameterizations.

Research on the Methods for Obtaining Droplet Impingement Characteristics in the Lagrangian Framework

The impact of supercooled water droplets is the cause of aircraft icing, and the acquisition of impingement characteristics is the key to icing prediction and the design of ice protection systems. The introduction of water droplet collection efficiency is required to obtain the characteristics for the Lagrangian method. In this work, a traditional flow tube method, a local flow tube method, and a statistical method are established to calculate the local collection efficiency, based on Lagrangian droplet trajectories. Through the numerical simulations of the air–droplet flow field around an NACA 0012 airfoil, the accuracies of the three methods in regard to collection efficiency are verified. Then, these three methods are applied to obtain the results for water droplet trajectories and the collection efficiency of an S-shaped duct, a 2D engine cone section and an icing wind tunnel. The results show that the distributions of water droplet collection efficiency obtained by the three methods are consistent and the three methods are all feasible when the water droplets do not overlap or cross before hitting the aircraft surfaces. When the water droplets are shadowed by upstream surfaces or blown by air injection, the droplet trajectories might overlap or even cross, and the local collection efficiencies obtained by the traditional flow tube method, local flow tube method, and statistical method might differ. The statistical method is relatively accurate. However, not all the droplet impingement characteristics obtained by the three methods are different due to these effects, and the non-crossing of the droplet trajectories is not a necessary condition for the use of the flow tube method. The effects of trajectory crossings are analyzed and discussed in detail in different situations for the three methods. This work is helpful for understanding and accurately calculating the droplet impingement characteristics and is of great significance for simulations of the aircraft icing process and anti/de-icing range.

A Preliminary Approach towards Rotor Icing Modeling Using the Unsteady Vortex Lattice Method

UAV rotors are at a high risk of ice accumulation during their operations in icing conditions. Thermal ice protection systems (IPSs) are being employed as a means of protecting rotor blades from ice, yet designing the appropriate IPS with the required heating density remains a challenge. In this work, a reduced-order modeling technique based on the Unsteady Vortex Lattice Method (UVLM) is proposed as a way to predicting rotor icing and to calculate the required anti-icing heat loads. The UVLM is gaining recent popularity for aircraft and rotor modeling. This method is flexible enough to model difficult aerodynamic problems, computationally efficient compared to higher-order CFD methods and accurate enough for conceptual design problems. A previously developed implementation of the UVLM for 3D rotor aerodynamic modeling is extended to incorporate a simplified steady-state icing thermodynamic model on the stagnation line of the blade. A viscous coupling algorithm based on a modified α-method incorporates viscous data into the originally inviscid calculations of the UVLM. The algorithm also predicts the effective angle of attack at each blade radial station (r/R), which is, in turn, used to calculate the convective heat transfer for each r/R using a CFD-based correlation for airfoils. The droplet collection efficiency at the stagnation line is calculated using a popular correlation from the literature. The icing mass and heat transfer balance includes terms for evaporation, sublimation, radiation, convection, water impingement, kinetic heating, and aerodynamic heating, as well as an anti-icing heat flux. The proposed UVLM-icing coupling technique is tested by replicating the experimental results for ice accretion and anti-icing of the 4-blade rotor of the APT70 drone. Aerodynamic predictions of the UVLM for the Figure of Merit, thrust, and torque coefficients agree within 10% of the experimental measurements. For icing conditions at −5 °C, the proposed approach overestimates the required anti-icing flux by around 50%, although it sufficiently predicts the effect of aerodynamic heating on the lack of ice formation near the blade tips. At −12 °C, visualizations of ice formation at different anti-icing heating powers agree well with UVLM predictions. However, a large discrepancy was found when predicting the required anti-icing heat load. Discrepancies between the numerical and experimental data are largely owed to the unaccounted transient and 3D effects related to the icing process on the rotating blades, which have been planned for in future work.

Experimental study and modeling of water film thickness in aero-engine under air–water mist flow

The water film not only plays an important role in the mass, momentum, and energy transfer between the air–water-surface but also determines the on-wing washing effect of the aero-engine. In view of this, air–water mist flow visualization experiments have been conducted at different gas velocities and water-to-air ratios in a compressor cascade, and the microscopic water film images have been analyzed to extract the transient water film thickness data by the Matlab code. It was found that the transient water film thickness fluctuation has no obvious association with the gas velocity, and the water film fluctuation is more affected by the water-to-air ratio. As the water-to-air ratio increases, the fluctuation magnitude of the water film thickness increases. The average water film thickness has been studied in relation to gas velocity and water flow rate, i.e., the average thickness of water film decreases with increasing gas velocity and increase with the increasing water flow rate. On the basis of the water film flow equation and taking the droplet collection efficiency into account, i.e., from the perspective of the physical mechanism of water film formed, a new model for predicting the water film thickness of a compressor blade surface under the air–water mist flow condition was proposed and validated. This model predicted, with a root mean square error and the mean absolute percentage error of 11.6% and 9.15%, respectively, under the present experimental flow conditions.

Numerical evaluation of respiratory droplet removal by an ionic wind-driven electrostatic device in an indoor environment

A novel method by utilizing self-pumped electrostatic droplet collectors is proposed to remove respiratory droplets in a room. The ionic wind flow pattern and droplet migration and removal process in a room were numerically predicted by the Eulerian-Lagrangian method. The coupling between the corona discharge, air flow and droplet migration processes was realized in the numerical model. Results demonstrate that a circulation flow pattern across the whole room is generated with a velocity magnitude of 1 m s−1. The droplet removal time is mainly governed by the migration of droplets from a specific position to the inlet of the electrostatic droplet collector. The turbulent dispersion of droplets greatly enhances the droplet migration and reduces the droplet removal time by 70 % for droplets with an initial diameter of 20 μm. More than 99 % droplets suspended in the room with a characteristic size of 5 m can be removed in 200 s with a power consumption of about 150 W. Compared with the droplet free deposition, the electrostatic droplet collection method reduces the droplet removal time by more than 90 %.

ANDeS: An automated nanoliter droplet selection and collection device

The Droplet Microarray (DMA) has emerged as a tool for high-throughput biological and chemical applications by enabling miniaturization and parallelization of experimental processes. Due to its ability to hold hundreds of nanoliter droplets, the DMA enables simple screening and analysis of samples such as cells and biomolecules. However, handling of nanoliter volumes poses a challenge, as manual recovery of nanoliter volumes is not feasible, and traditional laboratory equipment is not suited to work with such low volumes, and small array formats. To tackle this challenge, we developed the Automated Nanoliter Droplet Selection device (ANDeS), a robotic system for automated collection and transfer of nanoliter samples from DMA.ANDeS can automatically collect volumes from 50 to 350 nL from the flat surface of DMA with a movement accuracy of ±30 µm using fused silica capillaries. The system can automatically collect and transfer the droplets from DMA chip into other platforms, such as microtiter plates, conical tubes or another DMA. In addition, to ensure high throughput and multiple droplet collection, the uptake of multiple droplets within a single capillary, separated by air gaps to avoid mixing of the samples within the capillary, was optimized and demonstrated.This study shows the potential of ANDeS in laboratory applications by using it for the collection and transfer of biological samples, contained in nanoliter droplets, for subsequent analysis. The experimental results demonstrate the ability of ANDeS to increase the versatility of the DMA platform by allowing for automated retrieval of nanoliter samples from DMA, which was not possible manually on the level of individual droplets. Therefore, it widens the variety of analytical techniques that can be used for the analysis of content of individual droplets and experiments performed using DMA. Thus, ANDeS opens up opportunities to expand the development of miniaturized assays in such fields as cell screening, omics analysis and combinatorial chemistry.

Design and fabrication of nepenthes alata-inspired sweat collection patch using wettability patterning method

Sweat-based wearable devices are attracting attention for non-invasive monitoring of various biomarkers present in sweat. However, the problem of inadequate sweat volume remains prevalent in sweat testing. To overcome this challenge, we present an integrated flexible platform that incorporates open microfluidic tracks, specifically designed for efficient sweat collection. The construction of these tracks involves employing a simple wettability patterning method using PDMS-TiO2 nanocomposite as a coating surface. Additionally, a thorough characterization study is conducted to analyze the synthesized composite material comprehensively. Furthermore, we propose a novel curvilinear wedge track design, inspired by the teeth structure of Nepenthes alata, to enhance droplet collection, achieving an improvement in collection efficiency in the range 86–94%. The physics of droplet transport is explained through simulations. To demonstrate the feasibility of our approach, we fabricated and tested a patch embedded with a wedge track and a screen printed three-electrode system, showcasing successful sweat collection. The novelty of this work lies in the development of a fabricated patch that minimizes sample volume requirements when integrated with the electrode system. Additionally, its orientation-independent design makes it suitable for wearable applications.

Numerical analysis of impingement characteristics of supercooled large droplets on the surface of a rotating hood

The authors of this study numerically analyze the characteristics of impingement of supercooled large droplets on the surface of the rotating hood of an aircraft. We use the secondary development function of Fluent software to first compare the prevalent models of impinging supercooled large droplets and then develop a modified model to numerically simulate their characteristics of impingement on the surface of a rotating hood in order to examine the effects of the diameter of the droplets, the speed of rotation, and the corresponding velocity of inflow on them. The results showed that the efficiency of the loss of mass of the droplets caused by their splashing and rebounding was low on the top of the cone, while the efficiency of local droplet collection was the highest. The efficiency of mass loss quickly increased, while that of droplet collection sharply decreased in the area of transition from the top to the side. The efficiencies of mass loss and droplet collection were nearly constant on the side of the cone, while that of the latter decreased to zero on the tail of the cone. When the median volumetric diameter of the droplets was increased from 79 to 250 µm, the efficiency of the loss of mass increased by about 15% on the side of the cone, but that of local droplet collection changed only slightly. The efficiency of the loss of mass decreased by about 20%, while that of local droplet collection increased by about 2.6% on the top of the cone under this condition. When the speed of rotation was increased from 1200 to 4300 r/min and the corresponding velocity of inflow was increased from 30 to 140 m/s, the efficiency of mass loss increased by about 15% on the side of the cone, while that of local droplet collection changed little. The efficiency of mass loss on the top of the cone decreased by about 37.5%, while that of local droplet collection increased by about 8% in this case.