Actual Droplet Research Articles

Atmospheric icing meteorological parameter study using field experiments and simulation

AbstractAtmospheric icing on ground structures is a concern from design, operation, and safety perspectives. Supercooled water droplets size and liquid water content (LWC) are important weather parameters to better understand the ice accretion physics on ground structures. Most existing studies are based on measurements at high altitude. The study is based on the field results of a specific event (from 9:30 to 22:27 h on October 29, 2022) in Arctic region of northern Norway. The data from this event are presented and used for analytical validation and simulation. Field measurements of different meteorological weather parameters including the droplet size and LWC are carried out leading to recording of resultant atmospheric ice load and intensity. A comprehensive study is also carried out to validate droplet collision efficiency and ice load using the existing analytical model ISO‐12494 and computational fluid dynamics (CFD)–based numerical simulations. Furthermore, the differences in icing simulation using parameters such as median volume diameter (MVD), Langmuir B –J as alternatives to the actual droplet size distribution (DSD) spectrum are also analyzed. The results show that under natural meteorological conditions, the characteristics of water DSD change in real time. Using MVD alone to calculate the water droplet collision efficiency on circular cylinders can lead to significant errors. Accurately selecting the Langmuir distribution as a substitute for the actual DSD can reduce simulation errors to within 5%. Compared to the analytical model, the numerical simulations result better reflects the collision characteristics of water droplets of different sizes on the cylindrical object.

The Effect of Internal Combustion Engine Nozzle Needle Profile on Fuel Atomization Quality

This article presents the results of research on the impact of changing the cross-section of an atomizer’s flow channel, which is caused by changing the flow geometry of the passive part of the needle on the drop diameter distribution of the fuel spray. A three-hole type H1LMK, 148/1 atomizer with hole diameters, dN, equal to 0.34 mm, is analyzed. A nozzle with a standard (i.e., unmodified) needle and three nozzles using needles with a modified profile in the flow part of the needle, marked by the code signatures 1L, 2L, and 3L, are tested. An increasing level of fuel turbulence characterizes the needles during the flow along their flow part due to the use of one (1L), two (2L), and three (3L) de Laval toroidal nozzles, respectively, obtained by mechanically shaping the outer surface of the flow part of the spray needle. The spray produced is tested using the Malvern Spraytec STP 500 device cooperating with the dedicated Malvern version 4.0. During the tests, measurements and an analysis of the spray droplet size distribution over the entire injection duration, equal to 7 ± 2 ms, are made for each nozzle. The experiment makes it possible to determine the effect of the nozzle needles’ profiles on the time distribution of the actual droplet diameters; the time distribution of the Sauter mean droplet diameters, D[3,2]; the percentile shares of the droplet diameters Dv (10), Dv (50), and Dv (90); the distribution span during the development of the spray stream; and the time distribution of the shares of the droplets with diameters belonging to selected diameter classes D[x1−x2] in the spray. The results of the measurements of the drop diameter distribution indicate that using atomizers with a modification to the flow channel allows for an increase in the share of droplets with smaller diameters compared to the standard atomizer.

Optimization and verification of droplet infiltration model in contact line theory

In order to improve the theory of contact line density, the contact angle model of rectangular convex structure with anisotropy was established, and the integral method and cyclic assignment method were used to solve the droplet volume. Then, the characteristic dimensions of FKM (fluorine rubber) surface prepared by template method were collected by visual recognition technology. In addition, the gravity, surface tension and micro-droplet height of the droplet in the antenna model were verified. Finally, the error of theoretical droplet height and actual droplet height in the solution of droplet gravity and surface tension was calculated by regression model. It is shown that the empirical correction coefficient of the contact angle model is 0.04–0.112 when the droplet gravity and surface tension are equal. Moreover, the reliability of theoretical gravity and theoretical surface tension of droplets instead of actual values is 96.3% and 99.4% respectively. States of droplets on six FKM surfaces are all in accordance with Wenzel-Cassie transition state model. Optimizing the theory of contact line density is conducive to designing accurate and anisotropic rough structures.

Simplified Model Predicts Binder Behavior in Sand Mold Printing

Binder jetting is a crucial process in additive manufacturing (AM) and is widely used in sand mold casting. This study explores the challenges of simulating binder droplets in ANSYS Fluent, including complexity and computational time. To overcome these challenges, we propose a geometric approach that models the binder droplet as a circular shape instead of an actual droplet. Additionally, the dynamic mesh feature is employed to transform the initial boundary condition into a wall condition at a specified time interval (Δt). This simplified approach eliminates the need to simulate actual droplets, leading to significant computational resource and time savings. By adopting this geometric approach, we can accurately predict the diffusion and penetration behavior of binder droplets with varying materials and volumes in porous media with different porosities. Through data analysis, it was found that the main variables affecting the diffusion diameter and penetration depth are binder volume and porosity. The successful implementation of this simplified model enables researchers and engineers to expedite the simulation of binder behavior, facilitating process optimization and enhancing the understanding of binder jetting technology in the field of additive manufacturing.

Limitations of Atomistic Molecular Dynamics to Reveal Ejection of Proteins from Charged Nanodroplets.

Atomistic molecular dynamics (MD) is frequently used to unravel the mechanisms of macroion release from electrosprayed droplets. However, atomistic MD is currently feasible for only the smallest window of droplet sizes appearing at the end steps of a droplet's lifetime. The relevance of the observations made to the actual droplet evolution, which is much longer than the simulated sizes, has not been addressed yet in the literature. Here, we perform a systematic study of the desolvation mechanisms of poly(ethylene glycol) (PEG), protonated peptides of different compositions, and proteins, to (a) obtain insight into the charging mechanism of macromolecules in larger droplets than those that are currently amenable to atomistic MD and (b) examine whether currently used atomistic MD modeling can establish the extrusion mechanism of proteins from droplets. To mimic larger droplets that are not amenable to MD modeling, we scale down the systems, by simulating a large droplet size relative to the macromolecule. MD of PEG charging reveals that, above a critical droplet size, ions are available near the backbone of the macromolecule, but charging occurs only transiently by transfer of ions from the solvent to the macroion, while below the critical size, the capture of the ion from PEG has a lifetime sufficiently long for the extrusion of a charged PEG from the aqueous droplet. This is the first report of the role of droplet curvature in the relation between macroion conformation and charging. Simulations of protonated peptides with a high degree of hydrophobicity show that partial extrusion of a peptide from the droplet surface is rare relative to desolvation by drying-out. Different from what has been presented in the literature, we argue that atomistic MD simulations have not sufficiently established the extrusion mechanism of proteins from droplets and their charging mechanism. We also argue that release of highly charged proteins can occur at an earlier stage of a droplet's lifetime than predicted by atomistic MD. In this earlier stage, we emphasize the key role of jets emanating from a droplet at the point of charge-induced instability in the release of proteins.

Study on Performance and Operation Mechanism of a Separation Equipment for a PWR Steam Generator

Computational fluid dynamics (CFD) is adopted to calculate and analyze the performance and separation mechanism of a steam-water separation equipment for a pressurized water reactor (PWR) steam generator. The steam-water two-phase flow is simulated by the Euler two-fluid model, and several representative water droplet diameters are selected among 50 to 400 μm. The influence mechanism of water droplet diameter on the performance is investigated by analyzing the flow parameters such as phase volume fraction, velocity, and turbulent kinetic energy. The results show that the integrated calculation and analysis of the separation equipment can more truly reflect the flow state between the separators, improving the reliability of the performance prediction and mechanism analysis. With the increase in water droplet diameter, the separation efficiency of the separation equipment and each separator gradually increases, the outlet wetness gradually decreases, and the pressure loss first decreases and then stabilizes. When 400 μm is taken as the characteristic value of the actual droplet diameter distribution at the inlet of the separation equipment, the performance prediction is more accurate, the pressure loss of each separator is relatively close, and the pressure loss of the primary separator is less affected by the droplet diameter and smaller than that of the swirl-vane primary separator, which is conducive to achieving a higher circulation ratio (CR). Re-entrainment occurs at the perforations of the primary separator and the outlet of the secondary separator, and the corresponding structure is suggested to be optimized to further improve separation efficiency of the separation equipment.

Droplet transition from non-axisymmetric to axisymmetric shape: Dynamic role of lubrication film in a rectangular microfluidic channel

In the past 20 years, droplet microfluidics is burgeoning in many chemical and biological applications due to the unique capability of droplets to act as confined containers. Confinement is ensured even in the case of squeezed droplets within microchannels much smaller than droplet volumes due to the presence of a lubrication thin film that prevents contact between droplets and the channel walls. The thickness of the lubrication film depends on the dynamics of the entire microfluidic system, affecting the actual droplet's shape and velocity. Therefore, this film is extensively studied to obtain insight into the dynamics of flowing droplets, especially when confined in small channels. Circular cross section channels are the most studied for their axial symmetry, but practical applications present most likely non-axisymmetric channels, as a result of fabrication processes, such as soft lithographic rectangular channels. The latter showed unique transitional morphological behavior of droplets, which assumes an axisymmetric or non-axisymmetric shape during their flow inside a non-axisymmetric channel, depending on the lubrication film. This work gives a comprehensive experimental characterization of the dynamics of the lubrication film during the droplet shape transition. We settled on a novel approach based on the optical diffraction of a localized light beam provided by two-facing optical waveguides integrated with the microfluidics circuit. The technique allows for studying the dynamics of flowing droplets and their relationship with the lubrication film thickness. Additionally, this experimental system enables a precise definition of two regimes of lubrication film, and the critical capillary number at which the transition occurs.

Numerical and theoretical analysis of fast evaporating sessile droplets with coupled fields

Sessile evaporating droplets are widely encountered in various scientific and industrial fields, therefore, it is of vital importance for accurate prediction of actual droplet evaporation rates. For slow droplet evaporation, the heat and vapor transport of the droplet are diffusion-controlled, the classic isothermal model can predict the droplet evaporation well. However, for fast droplet evaporation, the convection flow, heat and vapor transfer are strongly coupled together, which brings great difficulty for accurate prediction. In this study, both theoretical analysis and numerical simulation are carried out to study the droplet evaporation with coupled flow, heat and vapor transfer fields. The droplet evaporation is investigated under different evaporative cooling numbers, droplet contact angles and substrate superheats. It is found that droplet evaporation can always be deteriorated by the evaporative cooling effect, while it can be enhanced by thermocapillary convection flow inside the droplet and natural convection outside the droplet. It is surprisingly found that the actual evaporation rates can be higher than those in the isothermal model, especially at low contact angle, high substrate superheat and weak evaporative cooling effect. Besides, a correction factor is proposed to quantify the deviation of actual evaporating rates in our fully coupled model from those in the isothermal model, and provides the dependence of the correction factor on evaporative cooling numbers, contact angles and substrate superheats, which can help predict the actual droplet evaporation rates. These findings may be helpful to get insight into the droplet evaporation and guide for its application.

Adaptive Prediction of Water Droplet Infiltration Effectiveness of Sprinkler Irrigation Using Regularized Sparse Autoencoder–Adaptive Network-Based Fuzzy Inference System (RSAE–ANFIS)

As the high productive efficiency of sprinkler irrigation is largely based on balanced soil moisture distribution, it is essential to study the exact effectiveness of water droplet infiltration, which provides a theoretical basis for rationally scheduling the circulation efficiency of groundwater in agricultural irrigation performance. This research carried out adaptive prediction of the droplet infiltration effectiveness of sprinkler irrigation by using a novel approach of a regularized sparse autoencoder–adaptive network-based fuzzy inference system (RSAE–ANFIS), for the purpose of quantifying actual water droplet infiltration and effectiveness results of precision irrigation in various environmental conditions. The intelligent prediction experiment we implemented could be phased as: the demonstration of governing equations of droplet infiltration for sprinkler irrigation modeling; the measurement and computation of probability densities in water droplet infiltration; innovative establishment and working analysis of RSAE–ANFIS; and the adaptive prediction of infiltration effectiveness indexes, such as average soil moisture depth increment (θ, mm), irrigation infiltration efficiency (ea, %), irrigation turn duration efficiency (et, mm/min), and the uniformity coefficient of soil moisture infiltration (Cu, %), which were implemented to provide a comprehensive illustration for the effective scheduling of sprinkler irrigation. Result comparisons indicated that when jetting pressure (Pw) was 255.2 kPa, the impinge angle (Wa) was 42.5°, the water flow rate (Fa) was 0.67 kg/min, and continuous irrigation time (Tc) was 32.4 min (error tolerance = ±5%, the same as follows), thereby an optimum and stable effectiveness quality of sprinkler irrigation could be achieved, whereas average soil moisture depth increment (θ) was 57.6 mm, irrigation infiltration efficiency (ea) was 62.5%, irrigation turn duration efficiency (et) was 34.5 mm/min, and the uniformity coefficient of soil moisture infiltration (Cu) was 53.6%, accordingly. It could be concluded that the proposed approach of the regularized sparse autoencoder–adaptive network-based fuzzy inference system has outstanding predictive capability and possesses much better working superiority for infiltration effectiveness in accuracy and efficiency; meanwhile, a high agreement between the adaptive predicted and actual measured values of infiltration effectiveness could be obtained. This novel intelligent prediction system has been promoted constructively to improve the quality uniformity of sprinkler irrigation and, consequently, to facilitate the productive management of sprinkler irrigated agriculture.

Transient Prediction of Nanoparticle-Laden Droplet Drying Patterns through Dynamic Mode Decomposition

Nanoparticle-laden sessile droplet drying has a wide impact on applications. However, the complexity affected by the droplet evaporation dynamics and particle self-assembly behavior leads to challenges in the accurate prediction of the drying patterns. We initiate a data-driven machine learning algorithm by using a single data collection point via a top-view camera to predict the transient drying patterns of aluminum oxide (Al2O3) nanoparticle-laden sessile droplets with three cases according to particle sizes of 5 and 40 nm and Al2O3 concentrations of 0.1 and 0.2 wt %. Dynamic mode decomposition is used as the data-driven learning model to recognize each nanoparticle-laden droplet as an individual system and then apply the transfer learning procedure. Along 270 s of droplet drying experiments, the training period of the first 100 s is selected, and then the rest of the 170 s is predicted with less than a 10% error between the predicted and the actual droplet images. The developed data-driven approach has also achieved the acceptable prediction for the droplet diameter with less than 0.13% error and a coffee-ring thickness over a range of 2.0 to 6.7 μm. Moreover, the proposed machine learning algorithm can recognize the volume of the droplet liquid and the transition of the drying regime from one to another according to the predicted contact line and the droplet height.

Effect of Addition of PVA/PG to Oil-in-Water Nanoemulsion Kojic Monooleate Formulation on Droplet Size: Three-Factors Response Surface Optimization and Characterization

An oil in water (O/W) nanoemulsion formulation containing kojic monooleate (KMO) in thin film system was developed. Response surface methodology (RSM) was used to optimize and analyzed the effect of three variables, namely concentration of polyvinyl alcohol (PVA) (20–30% w/w), concentration of propylene glycol (PG) (1–10% w/w), and shear rate of high shear homogenizer (3000–9000 rpm) on droplet size as a response, while other compositions remained constant such as KMO (10.0% w/w), Tween 80 (3.19% w/w), castor oil (3.74% w/w), xanthan gum (0.70% w/w), and germall plus (0.7% w/w, PG (and) diazolidinyl urea (and) iodopropynyl butylcarbamate). The optimized KMO nanoemulsion formulation with desirable criteria was PVA (27.61% w/w) and PG (1.05% w/w), and shear rate (8656.17 rpm) with a predicted droplet size (110.21 nm) and actual droplet size (105.93 nm) with a residual standard error (RSE) of less than 2.0% was obtained. Analysis of variance (ANOVA) showed that the fitness of the quadratic polynomial fit the experimental data with a F-value of 65.30, p–value of p < 0.0001, and a non-significant lack-of-fit. The optimized KMO formulation shows the desired criteria of the thin film system and the physicochemical properties (Zeta potential −37.37 mV, PDI 0.13, pH 4.74) and stability at four different conditions indicate its suitability for cosmeceutical applications.

The forming process of polymer melt droplet deposition three‐dimensional printing

AbstractThe polymer droplet deposition technology is a rapidly developing three‐dimensional (3D) printing technology, and is becoming a research hotspot. In this study, the qualitative relationship between the temperature‐field distribution and the forming quality was determined by using the finite‐element analysis, that is, the “birth and death of element” technology, the ANSYS parametric design language command. We obtained the relationship between process parameters and droplet size and droplet spacing through orthogonal experiments, and the theoretically optimal process parameters for droplet formation and arrangement were determined. We studied the relationship between the 3D spacing (Wx, Wy, and Wz) in the droplets and the product forming quality. We further optimized the theoretically optimal process parameters in the actual droplet deposition experiment, and finally determined the actual optimal droplet deposition process parameters as follows: the jet frequency is 14 Hz, the screw rotation speed is 10 rpm, the printing speed is 30 mm/s, and the printing distance is 1 mm. This article theoretically analyzed the influence of the polymer droplet deposition process on the forming quality from thermodynamic simulation and experiments that provide a theoretical basis for further improving the forming quality of the process.

Atomic-level insights into nano-salt droplets wetting on the MgO surface using molecular dynamics simulations

The effects of NaCl solution concentrations on the water wettability of the MgO surface have been studied using molecular dynamics simulations. We find that ion hydration has a strong ability to dominate the structure of water network in the hydration layer. It can transform the orientation of water OH bonds, and reconstruct an ordered water network in the first layer, which in turn reduces the density of inter-layer hydrogen bonds. This further results in weak interactions between the first hydration layer and the actual droplet above the hydration layer, eventually increasing the hydrophobicity of the MgO(001) surface and corrosion resistance.

Predicting inkjet dot spreading and print through from liquid penetration- and picoliter contact angle measurement

AbstractIn this study we have evaluated the suitability of laboratory testing methods to predict inkjet printing results. We have developed and used testing liquids that are spanning the operational window of industrial High Speed Inkjet (HSI) printers while still covering the maximum possible range of viscosity and surface tension. First we correlated liquid penetration measured with ultrasound (ULP) and direct absorption (ASA) to print through from HSI prints. The best correlation (R2≈0.7{R^{2}}\approx 0.7) was found for the sized paper. For papers with increasing liquid penetration speed we found a decreasing ability of both testing methods to predict print through, for the strong absorbing paper the correlation drops toR2≈0.2{R^{2}}\approx 0.2. Second we correlated contact angle and drop diameter to the dot area from HSI prints. Contact angle turned out to be a better predictor for printed dot area than drop diameter. Evaluating the change in contact angle over time we found the highest correlation to the dot area in the print when measuring the contact angle as soon as possible, in our case 1 ms after deposition of the drop on the paper. We also compared contact angle with microliter drops to picoliter drops, which are in the size scale of the actual inkjet droplet. To our great surprise correlations for microliter drops were equal or better than for picoliter drops, particularly for highly absorbing papers. Thus in order to predict dot spreading on paper our results suggest to measure the contact angle with microliter drops. Overall we found that, using laboratory testing methods, print through and dot spreading for HSI printing can be quite well predicted for slow absorbing papers but not very well for fast absorbing papers.

Stagnation-point polydisperse spray flame ignition

A theory of stagnation-point flow polydisperse spray flame ignition by an isothermal hot surface is presented for the first time. The configuration investigated consists of a mixture of fuel droplets and air flowing against an isothermal hot surface (such as a hot ignition probe). The polydisperse spray of droplets is modelled using the sectional approach. A single global chemical reaction is assumed for the case when ignition occurs. The mathematical analysis makes use of a small parameter that is exploited for an asymptotic approach. An analytical criterion for ignition is derived which includes effects of the flow field, the reactants and all the fuel spray-related parameters, including the initial size distribution of the spray's droplets. Numerical calculations disclose how the actual droplet size distribution impacts on the critical stagnation point temperature necessary to promote ignition. Additionally, the analytical estimates are compared with predictions of a numerical finite difference code with very satisfactory agreement.

Design of Plant Protection UAV Variable Spray System Based on Neural Networks.

Recently, unmanned aerial vehicles (UAVs) have rapidly emerged as a new technology in the fields of plant protection and pest control in China. Based on existing variable spray research, a plant protection UAV variable spray system integrating neural network based decision making is designed. Using the existing data on plant protection UAV operations, combined with artificial neural network (ANN) technology, an error back propagation (BP) neural network model between the factors affecting droplet deposition is trained. The factors affecting droplet deposition include ambient temperature, ambient humidity, wind speed, flight speed, flight altitude, propeller pitch, nozzles pitch and prescription value. Subsequently, the BP neural network model is combined with variable rate spray control for plant protection UAVs, and real-time information is collected by multi-sensor. The deposition rate is determined by the neural network model, and the flow rate of the spray system is regulated according to the predicted deposition amount. The amount of droplet deposition can meet the prescription requirement. The results show that the training variance of the ANN is 0.003, and thus, the model is stable and reliable. The outdoor tests show that the error between the predicted droplet deposition and actual droplet deposition is less than 20%. The ratio of droplet deposition to prescription value in each unit is approximately equal, and a variable spray operation under different conditions is realized.

Depinning force of a receding droplet on pillared superhydrophobic surfaces: Analytical models

It was experimentally shown that a depinning force of a receding droplet on a micropillared superhydrophobic surface has an apparently linear correlation with the maximal three-phase contact line attainable along an actual droplet boundary. However, the experimental observation has not yet been supported by any theoretical basis or analysis. This study establishes an analytical model that theoretically supports the experimental observation on the basis of the dynamics of a contact line. The depinning force of a receding droplet was experimentally measured in evaporation on micropillared superhydrophobic surfaces with varying structure pitches but a fixed size. The analytical model was established by considering the energy dissipated by the displacement of a microscopic contact line on pillar tops and the energy consumed for the distortion of a liquid-gas interface between pillar tops. The model shows that the depinning force can theoretically be estimated by the physical dimensions of pillars and the intrinsic hydrophobicity of the surface, showing excellent agreement with the experimental results. Especially, the model indicates that the depinning force is fundamentally determined and practically controllable by the normalized maximal contact line at the droplet boundary, which can effectively be represented as the ratio of the pillar top perimeter to pitch.

Design and Experiment of a Variable Spray System for Unmanned Aerial Vehicles Based on PID and PWM Control

Unmanned aerial vehicle (UAV) variable-rate spraying technology, as the development direction of aviation for plant protection in the future, has been developed rapidly in recent years. In the actual agricultural production, the severity of plant diseases and insect pests varies in different locations. In order to reduce the waste of pesticides, pesticides should be applied according to the severity of pests, insects and weeds. On the basis of explaining the plant diseases and insect pests map in the target area, a pulse width modulation variable spray system is designed. Moreover, the STMicroelectronics-32 (STM32) chip is invoked as the core of the control system. The system combines with sensor technology to get the prescription value through real-time interpretation of prescription diagram in operation. Then, a pulse square wave with variable duty cycles is generated to adjust the flow rate. A closed-loop Proportional-Integral-Derivative (PID) control algorithm is used to shorten the time of system reaching steady state. The results indicate that the deviation between volume and target traffic is stable, which is within 2.16%. When the duty cycle of the square wave is within the range of 40% to 100%, the flow range of the single nozzle varies from 0.16 L/min to 0.54 L/min. Variable spray operation under different spray requirements is achieved. The outdoor tests of variable spray system show that the variable spray system can adjust the flow rapidly according to the prescription value set in the prescription map. The proportion of actual droplet deposition and deposition density in the operation unit is consistent with the prescription value, which proves the effectiveness of the designed variable spray system.

Development of a kojic monooleate-enriched oil-in-water nanoemulsion as a potential carrier for hyperpigmentation treatment

IntroductionKojic monooleate (KMO) is an ester derived from a fungal metabolite of kojic acid with monounsaturated fatty acid, oleic acid, which contains tyrosinase inhibitor to treat skin disorders such as hyperpigmentation. In this study, KMO was formulated in an oil-in-water nanoemulsion as a carrier for better penetration into the skin.MethodsThe nanoemulsion was prepared by using high and low energy emulsification technique. D-optimal mixture experimental design was generated as a tool for optimizing the composition of nanoemulsions suitable for topical delivery systems. Effects of formulation variables including KMO (2.0%–10.0% w/w), mixture of castor oil (CO):lemon essential oil (LO; 9:1) (1.0%–5.0% w/w), Tween 80 (1.0%–4.0% w/w), xanthan gum (0.5%–1.5% w/w), and deionized water (78.8%–94.8% w/w), on droplet size as a response were determined.ResultsAnalysis of variance showed that the fitness of the quadratic polynomial fits the experimental data with F-value (2,479.87), a low P-value (P<0.0001), and a nonsignificant lack of fit. The optimized formulation of KMO-enriched nanoemulsion with desirable criteria was KMO (10.0% w/w), Tween 80 (3.19% w/w), CO:LO (3.74% w/w), xanthan gum (0.70% w/w), and deionized water (81.68% w/w). This optimum formulation showed good agreement between the actual droplet size (110.01 nm) and the predicted droplet size (111.73 nm) with a residual standard error <2.0%. The optimized formulation with pH values (6.28) showed high conductivity (1,492.00 µScm−1) and remained stable under accelerated stability study during storage at 4°C, 25°C, and 45°C for 90 days, centrifugal force as well as freeze–thaw cycles. Rheology measurement justified that the optimized formulation was more elastic (shear thinning and pseudo-plastic properties) rather than demonstrating viscous characteristics. In vitro cytotoxicity of the optimized KMO formulation and KMO oil showed that IC50 (50% inhibition of cell viability) value was >100 µg/mL.ConclusionThe survival rate of 3T3 cell on KMO formulation (54.76%) was found to be higher compared to KMO oil (53.37%) without any toxicity sign. This proved that the KMO formulation was less toxic and can be applied for cosmeceutical applications.

A Novel Approach to Droplet's 3D Shape Recovery Based on Mask R-CNN and Improved Lambert⁻Phong Model.

Aiming at the demand for extracting the three-dimensional shapes of droplets in microelectronic packaging, life science, and some related fields, as well as the problems of complex calculation and slow running speed of conventional shape from shading (SFS) illumination reflection models, this paper proposes a Lambert–Phong hybrid model algorithm to recover the 3D shapes of micro-droplets based on the mask regions with convolutional neural network features (R-CNN) method to extract the highlight region of the droplet surface. This method fully integrates the advantages of the Lambertian model’s fast running speed and the Phong model’s high accuracy for reconstruction of the highlight region. First, the Mask R-CNN network is used to realize the segmentation of the highlight region of the droplet and obtain its coordinate information. Then, different reflection models are constructed for the different reflection regions of the droplet, and the Taylor expansion and Newton iteration method are used for the reflection model to get the final height of all positions. Finally, a three-dimensional reconstruction experimental platform is built to analyze the accuracy and speed of the algorithm on the synthesized hemisphere image and the actual droplet image. The experimental results show that the proposed algorithm based on mask R-CNN had better precision and shorter running time. Hence, this paper provides a new approach for real-time measurement of 3D droplet shape in the dispensing state.