Droplet Size Determination Research Articles

Development of stable castor oil-based isocyanate emulsion via Hw-Ho-NCO structural model: Towards crosslinking agent for waterborne wood adhesive

Water-based materials are important to mitigate the concern on solvent-based products. Incorporation of reactive isocyanate-based crosslinking agents is key to improve material performance, while intense, nonhomogeneous reaction causes short operation duration and uncontrollable product quality. Herein, this study proposes a Hw-Ho-NCO (hydrophilic part-hydrophobic segment-NCO group) structural model to overcome such issue by forming water-compatible isocyanate emulsions via self-emulsification of castor oil-modified water-dispersible isocyanate (WDI). The properties of WDI and obtained emulsions were analyzed through visual appearance, titration of -NCO content, droplet size determination, microstructure, etc. Aggregation and sedimentation of the isocyanate emulsions upon storage occur owing to lack of hydrophilic groups on droplet surface, while sodium dodecyl sulfate (SDS)-assisted secondary emulsification improves the emulsion stability. The emulsions are used as crosslinking agents to formulate composite waterborne adhesives with the white latex (EVA-102), reaching maximal pot life of 8 h. The plywood specimens manufactured using the composite adhesive show enhanced adhesion performances, particularly for wet strength I and II, exceeding the Chinese national standard (GB/T 9846–2015). This study confirms the capability of using the structural model to create stable isocyanate emulsions that can target to formulate high-performance waterborne adhesives for clean and green production in wood industry.

Determination of droplet size from wide-angle light scattering image data using convolutional neural networks

Wide-angle light scattering (WALS) offers the possibility of a highly temporally and spatially resolved measurement of droplets in spray-based methods for nanoparticle synthesis. The size of these droplets is a critical variable affecting the final properties of synthesized materials such as hetero-aggregates. However, conventional methods for determining droplet sizes from WALS image data are labor-intensive and may introduce biases, particularly when applied to complex systems like spray flame synthesis. To address these challenges, we introduce a fully automatic machine learning-based approach that employs convolutional neural networks (CNNs) in order to streamline the droplet sizing process. This CNN-based methodology offers further advantages: it requires few manual labels and can utilize transfer learning, making it a promising alternative to conventional methods, specifically with respect to efficiency. To evaluate the performance of our machine learning models, we consider WALS data from an ethanol spray flame process at various heights above burner surface, where the models are trained and cross-validated on a large dataset comprising nearly 35000 WALS images.

The impact of actuator nozzle and surroundings condition on drug delivery using pressurized-metered dose inhalers.

The most commonly used method to deliver aerosolized drugs to the lung is with pressurized metered-dose inhalers (pMDIs). The spray actuator is a critical component of pMDI, since it controls the atomization process by forming aerosol plumes and determining droplet size distribution. Through computational fluid dynamics (CFD) simulations, this study investigated the effect of two different nozzle types (single conventional and twin nozzles) on drug deposition in the mouth-throat (MT) region. We also studied the behavior of aerosol plumes in both an open-air environment and the MT geometry. Our study revealed that spray aerosol generated in an unconfined, open-air environment with no airflow behaves distinctly from spray introduced into the MT geometry in the presence of airflow. In addition, the actuator structure significantly impacts the device's efficacy. In the real MTmodel, we found that the twin nozzle increases drug deposition in the MT region, and its higher aerosol velocity negatively affects its efficiency.

Mask R-CNN based droplet detection in liquid–liquid systems, Part 2: Methodology for determining training and image processing parameter values improving droplet detection accuracy

Multiphase systems occur in many technical processes, e.g., crystallization, gas–liquid reaction, and liquid–liquid extraction. Operating such processes requires knowledge of fluid dynamics, mass transfer, and reaction kinetics that depend on the phase interface. The particle size distribution quantifies the phase interface of multiphase systems. Multiphase systems can contain solid particles, gas bubbles, or liquid droplets. Our previous work presented an automated and publicly accessible image processing method to determine droplet size distributions (DSD) in liquid–liquid systems based on Mask Region-Based Convolutional Neural Networks (MRCNN). In this work, we developed a methodology to determine training and image processing parameter values that improve the droplet detection accuracy of our MRCNN implementation with a low computational effort. Our methodology combines a sensitivity analysis to reduce the dimensions of training parameters of interest with a systematic final model selection approach based on characteristic training and image processing rating metrics. Applying our methodology to a database of four different image qualities results in a highly improved droplet detection accuracy over the entire droplet diameter range of a DSD. In comparison to the MRCNN models trained on the default hyperparameter values, the average relative error in characteristic DSD properties: minimum diameter, maximum diameter, and the number of detected droplets could be reduced from 6% to 3%, from 7% to 2%, and from 7% to 2%, respectively, keeping the relative error in the Sauter mean diameter constant at 3%. The presented methodology can be universally applied to individual image qualities improving the droplet detection accuracy of our MRCNN implementation. Thus, combining our methodology with the MRCNN implementation increases the reliability of process analysis and process control in liquid–liquid systems. Moreover, our MRCNN implementation and methodology can likely be easily transferred to several applications in which particle detection plays a significant role, e.g., crystallization (solid particles) and gas–liquid reaction (bubbles).

An experimental workflow to assess the applicability of microemulsions for conformance improvement in oil-bearing reservoir

A comprehensive workflow approach is necessary to link multiple experimental tasks and identify microemulsion (ME) formulations with ‘optimal’ stability, displacement behavior and technical feasibility in the petroleum industry. In this paper, a systematic approach is described with the aid of a case study which involves the formulation of an anionic sodium dodecyl sulfate-based microemulsion. The design of such ME systems requires a proper methodology, substantial laboratory work, and functional assessment from research/industrial viewpoints. The surfactant has been screened in terms of its micellization potential, followed by phase behavior analysis and Winsor classification of prepared microemulsions. The desired composition(s) are characterized via several tools to determine droplet size, morphology, oil/water solubilization potentials and salinity scan results. The suitability of the microemulsion system for conformance improvement technology (CIT) is proposed to be assessed via physicochemical evaluation studies encompassing two attributes: rheology and stability. For a favorable ‘conforming’ drive, the microemulsion must exhibit phase stability, sufficient injectivity, and moderate-to-high viscosity under shear. Technical assessment by the industry and research team must also include factors related to cost, availability of chemicals, environmental degradation, and reservoir considerations. The article demonstrates a comprehensive all-inclusive workflow methodology to design and formulate surfactant-stabilized microemulsions via case study analysis for application in CIT. This represents a sound approach to identifying efficient, cost-effective injection fluid systems and provides a framework to identify useful parameters for ME formulation design and employ the proposed (effective) strategy for conformance control.

Stabilization of a Pickering Emulsion by Nanoparticles of Eudragit RSPO and Pol-epsilon Caprolactone: Contact Angle Measurement and Surface Tension Studies

The use of colloidal particles to prepare and stabilize emulsions, known as "Pickering emulsions “, has aroused growing interest in recent years. Pickering and Ramsden demonstrated at the beginning of the last century the feasibility of surfactant-free emulsions, in presence of these emulsions is called "Pickering Emulsions". This concept of emulsions stabilized by solid particles is experiencing renewed interest nowadays given the many advantages it offers good stability, environmental protection, user safety, and particle varieties.
 The first part is devoted to the synthesis of Eudragit RSPO and pol epsilon-caprolactone nanoparticles and their characterization. The characterization of the nanoparticles is performed by dynamic light scattering and geometry. The understanding of the interfacial behavior of these nanoparticles and their associated stabilization mechanisms for emulsions was carried out. The second part of the study investigated the formulation and stabilization of the emulsion using the washed suspension containing the nanoparticles as the only stabilizer. The objective of this part is to stabilize and characterize the formulated emulsions. Droplet size determination and microscopy were performed using a Zeiss optical microscope. The direction of the formulated emulsions was determined by conductimetry. In conclusion, Pickering emulsions stabilized solely by Eudragit RSPO and Poly-epsilon Caprolactone nanoparticles appear to be highly effective innovative drug carriers, opening new doors as potential drug delivery systems.

O/W Pickering emulsion stabilized by magnesium carbonate particles for drug delivery systems

This study investigates the formulation of surfactant-free Pickering emulsions that release a drug at a specific pH to improve its oral bioavailability. The stabilizing particles composed of magnesium carbonate particles. Pickering oil-in-water emulsions stabilized with magnesium carbonate particles and encapsulating a hydrophobic drug model (ibuprofen) were formulated using a high-energy process with rotor-stator turbo mixer (IKA® T25 digital ultra-Turrax). The experimental approach explored the impact of all formulation parameters, dispersed phase and amount of magnesium carbonate particles on the physicochemical properties of Pickering emulsions. The O/W Pickering emulsion was characterized by a methylene blue test, pH and conductivity measurements, and droplet size determination. In addition, Pickering emulsions stabilized by magnesium carbonate particles have the advantage of being destabilized in acidic medium leading to the release of the active principle via the droplets. The acidic medium release study (pH equal to 1.2) showed ibuprofen release as a function of initial droplet loading and saturation concentration. In the simulated intestinal medium at pH equal to 6.8, we found a better release of ibuprofen from emulsions that already had saturation in an acid medium. Thus, the interest of these Pickering emulsions lies on the fact that their non-toxicity and magnesium carbonate particles allow destabilization of the emulsions and release of the drug. These emulsions not only protect patients from the side effects of acid-based drugs, but also contribute to increase the bioavailability of these acidic drugs.
 Keywords: emulsion -Pickering-magnesium carbonate- ibuprofen-oral bioavailability

Droplet size from Venturi air induction spray nozzles

Sprays are of great importance for many applications, with drop size being a crucial parameter. Especially in agriculture applications, simple flat fan spray nozzles are often supplemented by a Venturi component to achieve larger drop sizes and hence, prevent unwanted spray drift of the smallest droplets. The general believe is that these larger drops are usually attributed to the fact that the liquid sheet produced by the nozzle breaks up more easily due to the pre-existing ’holes’ formed by the induced air bubbles. Here, we extend descriptions of how nozzle and fluid parameters determine droplet size distributions from Venturi nozzles. We show that the mean droplet size is determined by the nozzle’s orifice area as is the case for ordinary flat fan nozzles, but that the additional pressure drop over the Venturi chamber needs to be taken into account. Using this parameter, relations that were derived for flat fan nozzles can be re-used. This allows to show that the increase in droplet size compared to conventional nozzles is due to the additional pressure drop in the Venturi chamber, and not to a change in breakup mechanism due to the presence of air bubbles in the liquid sheet.

Cenosphere Formation and Combustion Characteristics of Single Droplets of Vacuum Residual Oils

ABSTRACT The ignition, combustion characteristics, and cenosphere formation of single droplets combustion of four vacuum residues (VRs) from different refineries with various asphaltene contents were studied experimentally. The single droplets of VRs were suspended at the tip of a silicon carbide fiber and heated in air at temperatures of 973 and 1023 K, respectively, in an electrically heated tube furnace. The ignition and combustion behavior of the VRs were recorded using a CCD camera, which enabled the determination of droplet size, ignition delay time, flame duration, and cenosphere size. The effect of initial droplet size, gas temperature, and asphaltene content on the ignition delay time, flame duration, cenosphere morphology, and particle size were investigated. The whole ignition and combustion process of single droplets of the VRs consisted of five stages in succession: (1) pre-ignition, mainly involving the evaporation of highly volatile components from the droplet surface; (2) steady combustion of fuel vapors evaporated from the droplet surface; (3) splashing combustion of fuel vapors evaporated from droplet interior; (4) disruptive combustion due to thermal decomposition of asphaltene; and (5) solid residue ignition and combustion. A visible and sooty flame was formed upon ignition and lasted during stages 2–4. The droplet size increased sharply in the stage 4 due to the thermal decomposition of asphaltene, which was more profound for VRs with higher asphaltene content and at higher gas temperatures. The ignition delay time increased with increasing initial droplet size and gas temperature but varied little as the asphaltene content in the VRs increased, suggesting that the ignition process of VRs was controlled by the vaporization of high volatile components on the droplet surface. The thermal decomposition of asphaltene produced solid residue, which was in the form of a cenosphere with the shell thickness being ca. 20 μm and a number of blowholes presented in the shell. The VRs with higher asphaltene content had more and bigger blowholes. The ratio of cenosphere particle size to initial droplet size is independent of the initial droplet size but almost increased linearly with the asphaltene content in the VRs.

Computational fluid dynamic study of polycaprolactone nanoparticles precipitation in a co‐flow capillary micro‐tube

AbstractPolycaprolactone nanoparticles (NPs) were produced in the co‐flow glass capillary device with tip dimension. NPs size was 990 nm for continuous phase velocity, and and 426 nm for . The droplet formation process in the co‐flow microchannel was also simulated using computational fluid dynamic (CFD). Employing a digital image analysis technique, a cut‐off value of 0.81 for the dispersed phase volume fraction was proposed for the determination of droplet size. A scenario was expressed for NP formation from micro‐droplets. Moreover, after conducting 27 CFD simulations, a dimensionless exponential form correlation was proposed for droplet size estimation. In this generalized map, there were three distinct regions based on the relative capillary numbers of continuous to dispersed phases. It was revealed that at a constant dispersed phase velocity, by increasing the continuous phase velocity, more small NPs are formed. The results show that the ratio of micro‐droplets to NPs size was between 735 and 755.

Evaluation of spray characteristics of aviation biofuels and Jet A-1 from a hybrid airblast atomizer

Studies on the atomization characteristics of sustainable aviation fuels (SAF) such as drop-in aviation biofuels from aircraft engine atomizers are essential to counter the rise in aviation-caused CO2 emissions in the atmosphere. The present study analyses the drop size characteristics of fuel sprays of camelina- and jatropha-derived drop-in aviation biofuels from a hybrid airblast atomizer (HAA) used in aircraft engines. To begin with salient details of hybrid atomization are studied through experiments using water at different liquid and air flow rates. The spray characterization work of four different drop-in aviation biofuels, derived through the blending of camelina/jatropha HRJ biofuels and Jet A-1, from the HAA is done subsequently. The fuel spray experiments are carried out at six test conditions. The mean drop size (Sauter mean diameter, SMD) variations of the HAA spray are compared with predictions obtained from correlations reported in the literature. Likewise, the SMD trends of the hybrid atomization are compared with that of the simplex swirl atomization. Using the current data of the HAA spray of six experimental fluids, a new correlation for non-dimensionalized SMD in terms of liquid and air Weber numbers and Ohnesorge number is proposed, which facilitates the determination of mean droplet size of futuristic alternative aviation fuel sprays from the hybrid airblast atomizers.

Improvement of emulsifying properties of potato starch via complexation with nanoliposomes for stabilizing Pickering emulsion

The complexation between nanoliposomes (NL) and potato starch (PS) was investigated to evaluate the improvement of PS ability to stabilize the Pickering emulsion. The visual appearances and emulsification index values showed that a milky white and uniform appearance of NLPS-stabilized Pickering emulsions (NPPE) was formed, and the stability of NPPE significantly increased compared with that of PS-stabilized emulsions. Droplet size determination of emulsions displayed that the droplet size D (4, 3) of NPPE was smaller than that of PS-stabilized emulsions, and the droplet size distribution of NPPE was more uniform. CLSM results presented that NLPS was inclined to adsorb on the oil-water interfaces for NPPE stability. Furthermore, TEM and SEM images manifested that NLPS was irregular and could form a gel network, and NLPS mainly ranged between 50 nm and 500 nm in size. Interfacial characteristics and three-phase contact angle results indicated that the hydrophobicity and the amphiphilicity of PS enhanced after complexation with NL, and the surface tensions and interfacial tensions of NLPS significantly decreased. FTIR and Zeta-potential analysis of NLPS demonstrated that hydrogen bonds and electrostatic forces played a vital role in the interactions between NL and PS. The present study suggests that the complexation between NL and PS can be an effective strategy for improving the ability of PS to stabilize Pickering emulsions.

Effects of the degree of oral processing on the properties of saliva-participating emulsions: using stewed pork with brown sauce as the model

This work investigated the changes in properties of saliva-participating emulsions during different oral processing stages (the whole process from intake to swallowing was divided into five stages, i.e., 20 %, 40 %, 60 %, 80 % and 100 % stage). The stewed pork with brown sauce was masticated and the emulsion was collected for the determination of emulsion stability, droplet size, ζ-potential, interfacial tension, and microstructure. The results showed that the emulsion stability increased gradually during the oral processing and reached the highest level near the swallowing point. The droplet size of emulsion showed a significant downward trend (P < 0.05). Microstructure observations also found different degrees of reduction in fat droplets size at different stages of oral processing. In addition, the ζ-potential of food boluses emulsion was decreased from −16.4 mV to −41.2 mV and the interfacial tension decreased by 52.6 % before and after oral progressing. In conclusion, the oral processing of stewed pork with brown sauce was essentially a process in which fat was constantly emulsified, and saliva might act as an emulsifier. This study provides new insights on understanding the oral processing process and sensory changes of fat.

Microscopy-Assisted Digital Image Analysis with Trainable Weka Segmentation (TWS) for Emulsion Droplet Size Determination

The size distribution of droplets in emulsions is very important for adjusting the effects of many indices on their quality. In addition to other methods for the determination of the size distribution of droplets, the usage of machine learning during microscopic analyses can enhance the reliability of the measurements and decrease the measurement cost at the same time. Considering its role in emulsion characteristics, in this study, the droplet size distributions of emulsions prepared with different oil/water phase ratios and homogenization times were measured with both a microscopy-assisted digital image analysis technique and a well-known laser diffraction method. The relationships between the droplet size and the physical properties of emulsions (turbidity and viscosity) were also investigated. The results showed that microscopic measurements yielded slightly higher values for the D(90), D[3,2], and D[4,3] of emulsions compared to the laser diffraction method for all oil/water phase ratios. When using this method, the droplet size had a meaningful correlation with the turbidity and viscosity values of emulsions at different oil/water phase ratios. From this point of view, the usage of the optical microscopy method with machine learning can be useful for the determination of the size distribution in emulsions.

Development of a Semi-Empirical Model for Droplet Size Determination of a Three-Channel Spray Nozzle for Pellet Coating Based on the Optical Method Concept

The purpose of this study was to investigate the droplet size obtained with a three-channel spray nozzle typically used in fluid bed devices and to construct a semi-empirical model for prediction of droplet size. With the aid of a custom-made optical method concept, the impact of the type of polymer and solvents used through dispersion properties (viscosity, density, and surface tension), dispersion flow rate, atomization pressure, and microclimate pressure on droplet size was investigated. A semi-empirical model with adequate predictability for calculating the average droplet size (R2 = 0.90, Q2 = 0.73) and its distribution (R2 = 0.84, Q2 = 0.61) was constructed by employing dimensional analysis and design of experiments. Newtonian and non-Newtonian dispersion and process parameters on laboratory and on production scale were included, thereby enabling constant droplet size irrespective of the scale. Based on the model results, it would be possible to scale-up the atomization process (e.g., coating process) from laboratory to production scale in a systematic fashion, regardless of the type of solvent or polymer used. For the system investigated, this can be performed by understanding the dispersion properties, such as viscosity, density, and surface tension, as well as the following process parameters: dispersion flow rate, atomization, and microclimate pressure.

Simultaneous Determination of Droplet Size, pH Value and Concentration to Evaluate the Aging Behavior of Metalworking Fluids.

Metalworking fluids (MWFs) are widely used to cool and lubricate metal workpieces during processing to reduce heat and friction. Extending a MWF’s service life is of importance from both economical and ecological points of view. Knowledge about the effects of processing conditions on the aging behavior and reliable analytical procedures are required to properly characterize the aging phenomena. While so far no quantitative estimations of ageing effects on MWFs have been described in the literature other than univariate ones based on single parameter measurements, in the present study we present a simple spectroscopy-based set-up for the simultaneous monitoring of three quality parameters of MWF and a mathematical model relating them to the most influential process factors relevant during use. For this purpose, the effects of MWF concentration, pH and nitrite concentration on the droplet size during aging were investigated by means of a response surface modelling approach. Systematically varied model MWF fluids were characterized using simultaneous measurements of absorption coefficients µa and effective scattering coefficients µ’s. Droplet size was determined via dynamic light scattering (DLS) measurements. Droplet size showed non-linear dependence on MWF concentration and pH, but the nitrite concentration had no significant effect. pH and MWF concentration showed a strong synergistic effect, which indicates that MWF aging is a rather complex process. The observed effects were similar for the DLS and the µ’s values, which shows the comparability of the methodologies. The correlations of the methods were R2c = 0.928 and R2P = 0.927, as calculated by a partial least squares regression (PLS-R) model. Furthermore, using µa, it was possible to generate a predictive PLS-R model for MWF concentration (R2c = 0.890, R2P = 0.924). Simultaneous determination of the pH based on the µ’s is possible with good accuracy (R²c = 0.803, R²P = 0.732). With prior knowledge of the MWF concentration using the µa-PLS-R model, the predictive capability of the µ’s-PLS-R model for pH was refined (10 wt%: R²c = 0.998, R²p = 0.997). This highlights the relevance of the combined measurement of µa and µ’s. Recognizing the synergistic nature of the effects of MWF concentration and pH on the droplet size is an important prerequisite for extending the service life of an MWF in the metalworking industry. The presented method can be applied as an in-process analytical tool that allows one to compensate for ageing effects during use of the MWF by taking appropriate corrective measures, such as pH correction or adjustment of concentration.

Determination of Spray Droplet Size by Wavelet Analysis of Interferometric Images

Determination of Spray Droplet Size by Wavelet Analysis of Interferometric Images

Formulation and Evaluation of Solid Self Nano Emulsifying drug delivery System of Olanzapine to Enhance Aqueous Solubility and Dissolution Rate

Present research work was aimed to enhance aqueous solubility and dissolution rate of olanzapine by solid self nano emulsifying drug delivery system(S-SNEDDS). Olanzapine is a BCS class II drug having 65% oral bioavailability; it is used in the treatment of psychosis, depression and mania conditions. Oils, Surfactants, Co surfactants were selected depending upon the saturated solubility of olanzapine in those components; excipients were screened depending on olanzapine solubility in various oils, surfactants and co surfactants. Surfactant: co surfactant {Smix} ratios i.e., 3:1 and 4:1 were prepared to determine nano emulsion regions and also to formulate liquid self nano emulsifying drug delivery system (L-SNEDDS). Pseudo ternary phase diagram were plotted by using Triplot version 4.1.2 software, nano emulsion region was determined and evaluated. Formulations were designed based on saturated solubility of olanzapine and Pseudo ternary phase diagram using various ratios of oils [Capryol 90], surfactants [Kolliphor EL], co surfactants [Lauroglycol 90] depending on its solubility and nano emulsion formation four formulations were developed which are further selected for characterisation of L-SNEDDS like robustness to dilution, self emulsification, determination of droplet size, PDI, Drug loading efficacy, zeta potential and also Invitro drug release. Among those four formulations, F1 (SB184J 4:6) was optimum because compared to other three formulations F3 gave best results in terms of droplet size (66nm) with PDI (0.24), Invitro drug release, dissolution rate of F1 SNEDDS having (88.201± 0.25%). Invitro drug release of F1 formulation was compared with that of Olanzapine [API] (45.281± 0.52%) the results indicating that there is a increase in solubility and dissolution rate of olanzapine by 2.2 times more compared to pure olanzapine (API). F1 (SB184J 4:6) were converted into S-SNEDDS by adsorption process by addition porous carriers (Aerosil 200). Formulated S-SNEDDS were undergone various evaluation parameters and also reconstitution parameters to determine Droplet size and Invitro drug release of solid F1 (SB184J4:6) formulation. The results of present study demonstrates that olanzapine SNEDDS has an ability and potential to enhance solubility and dissolution rate.

Measuring Droplets Expelled During Endoscopy to Investigate COVID-19 Transmission Risk

Measuring Droplets Expelled During Endoscopy to Investigate COVID-19 Transmission Risk

Formulation and Evaluation of Self Nano Emulsifying Drug Delivery System of Raloxifene Hydrochloride

Raloxifene hydrochloride (RLX) is a selective Estrogen-receptor modulator used to treat osteoporosis as well as breast and endometrial cancer prevention. The bioavailability of RLX is only 2% due to substantial pre-systemic clearance. The goal of this research was to customise and characterise RLX-loaded self-nanoemulsifying drug-delivery systems (SNEDDS) by using bioactive excipients that impact drug metabolism. The droplet size, zeta potential and drug content determination of optimized formulation (F-06) was found to be 147.5 nm, -28.8, 99.67% respectively. The drug release study from the nano formulation was studied in Phosphate buffer 6.8 for all the formulations F1,F2,F3,F4,F5,F6 and F7. The optimized formulation was found to be F6&#x0D; Keywords: Raloxifene hydrochloride, nanoemulsion, SNEDDS