Numerical simulations of wall contact angle effects on droplet size during step emulsification

Optimizing the Production of Hydrogel Microspheres Using Microfluidic Chips: The Influence of Surface Treatment on Droplet Formation Mechanism

Microfluidic chips have been widely applied in biology and medical research for stably generating uniform droplets that can be solidified into hydrogel microspheres. However, issues such as low microsphere yield, lengthy experimental processes, and susceptibility to environmental interference need to be addressed. In this work, a simple and effective method was developed to modify microfluidic chips at room temperature to improve the production performance of hydrogel microspheres. Numerical simulation-assisted experiments were conducted to comprehensively understand the effect of solution viscosity, hydrophilicity, and flow rate ratio on droplet formation during microsphere production. Chitosan was selected as the main component and combined with poly(ethylene glycol) diacrylate to prepare photocurable hydrogel microspheres as a demonstration. As a result, grafting fluoro-silane (FOTS) increased the contact angle of the channel from 90 to approximately 110°, which led to a 12.2% increase in droplet yield. Additionally, FOTS-modification attenuated the impact of the flow rate ratio on droplet yield by 19.1%. Alternatively, depositing dopamine decreased the channel's contact angle from 90 to 60°, resulting in a 21.4% increase in particle size and enabling the chip to adjust droplet size over a wider range. Further study demonstrates that the obtained hydrogel microspheres can be modified with layers of aldehyde, which can potentially be used for controlled drug release. Overall, this study proposed a facile method for adjusting the yield and droplet size through surface treatment of microfluidic chips while also enhancing the understanding of the synergistic effects of multiple factors in microfluidics-based microsphere production.

Near-Infrared Spectroscopy Coupled with Chemometrics and Artificial Neural Network Modeling for Prediction of Emulsion Droplet Diameters

There is increased interest in the food industry for emulsions as delivery systems to preserve the stability of sensitive biocompounds with the aim of improving their bioavailability, solubility, and stability; maintaining their texture; and controlling their release. Emulsification in continuously operated microscale devices enables the production of emulsions of controllable droplet sizes and reduces the amount of emulsifier and time consumption, while NIR, as a nondestructive, noninvasive, fast, and efficient technique, represents an interesting aspect for emulsion investigation. The aim of this work was to predict the average Feret droplet diameter of oil-in-water and oil-in-aqueous mint extract emulsions prepared in a continuously operated microfluidic device with different emulsifiers (PEG 1500, PEG 6000, and PEG 20,000) based on the combination of near-infrared (NIR) spectra with chemometrics (principal component analysis (PCA) and partial least-squares (PLS) regression) and artificial neural network (ANN) modeling. PCA score plots for average preprocessed NIR spectra show the specific grouping of the samples into three groups according to the emulsifier used, while the PCA analysis of the emulsion samples with different emulsifiers showed the specific grouping of the samples based on the amount of emulsifier used. The developed PLS models had higher R² values for oil-in-water emulsions, ranging from 0.6863 to 0.9692 for calibration, 0.5617 to 0.8740 for validation, and 0.4618 to 0.8692 for prediction, than oil-in-aqueous mint extract emulsions, with R² values that were in range of 0.8109-0.8934 for calibration, 0.5017-0.6620, for validation and 0.5587-0.7234 for prediction. Better results were obtained for the developed nonlinear ANN models, which showed R² values in the range of 0.9428-0.9917 for training, 0.8515-0.9294 for testing, and 0.7377-0.8533 for the validation of oil-in-water emulsions, while for oil-in-aqueous mint extract emulsions R² values were higher, in the range of 0.9516-0.9996 for training, 0.9311-0.9994 for testing, and 0.8113-0.9995 for validation.

Rheological Properties and Drag Reduction Performance of Puffer Epidermal Mucus

Most species of fish are covered with mucus, which provides the effect of reduction in swimming drag. In this paper, three concentrations of puffer epidermal mucus were obtained from the epidermal mucosa of puffer. The rheological properties and the drag reduction performance of the puffer epidermal mucus were characterized via a rheometer experimental and numerical simulation method. The relationship between the rheological properties and the drag reduction performance was analyzed and discussed, and the drag reduction mechanism of the puffer epidermal mucus was further explored. The results showed that the best drag reduction rate was 6.2% when the inflow velocity and concentration of puffer epidermal mucus were 0.1 m/s and 18.2 g/L, respectively. The rheological properties of puffer epidermal mucus are viscoelastic, and the mucus forms a sliding surface, which reduces the frictional drag of the fluid. In conclusion, this paper may provide a reference for the development of drag-reducing agents and drag-reducing research studies on other fish mucus.

Non-Newtonian Droplet Generation in a Cross-Junction Microfluidic Channel

A two-dimensional CFD model based on volume-of-fluid (VOF) is introduced to examine droplet generation in a cross-junction microfluidic using an open-source software, OpenFOAM together with an interFoam solver. Non-Newtonian power-law droplets in Newtonian liquid is numerically studied and its effect on droplet size and detachment time in three different regimes, i.e., squeezing, dripping and jetting, are investigated. To understand the droplet formation mechanism, the shear-thinning behaviour was enhanced by increasing the polymer concentrations in the dispersed phase. It is observed that by choosing a shear-dependent fluid, droplet size decreases compared to Newtonian fluids while detachment time increases due to higher apparent viscosity. Moreover, the rheological parameters-n and K in the power-law model-impose a considerable effect on the droplet size and detachment time, especially in the dripping and jetting regimes. Those parameters also have the potential to change the formation regime if the capillary number (Ca) is high enough. This work extends the understanding of non-Newtonian droplet formation in microfluidics to control the droplet characteristics in applications involving shear-thinning polymeric solutions.

Step emulsification in microfluidic droplet generation: mechanisms and structures

Step emulsification for micro- and nano-droplet generation is reviewed in brief, including the emulsion mechanisms and microfluidic devices.

Effects of wall velocity slip on droplet generation in microfluidic T-junctions

The effect of the slip lengths of both continuous and dispersed phases on droplet formation in microfluidic T-junctions is investigated by a volume of fluid method. Results reveal that, in a dripping regime, the droplet size is mainly influenced by the slip length of the continuous phase and increases with it. In a squeezing regime, the droplet size decreases with the slip lengths of both phases. The effects of the slip lengths of both phases on droplet generation are systematically discussed and summarized. The elongation rate of the thread can be decreased with an increase of slip lengths in both dripping and squeezing regimes, which is beneficial to improve droplet monodispersity. The monodispersity of droplets can deteriorate when the slip length of either phase is small and can be improved by increasing the slip length of the other phase.