Effect of surfactant addition and viscosity of the continuous phase on flow fields and kinetics of drop formation in a flow-focusing microfluidic device

High efficiency of biosurfactants in stabilizing oil micro-droplets within the aging time scale of milliseconds: a microfluidic study

Rapid adsorption of surfactants onto a freshly formed interface is vital for emulsification because emulsification is a competitive process occurring between the very short time span of interface formation and surfactant mass transport. The biosurfactant surfactin has been previously reported to reach adsorption equilibrium at the hydrophobic/hydrophilic interface within hundreds of milliseconds and rapidly reduce the interfacial tension compared to chemically synthesized surfactants. According to a prior study, surfactin is expected to exhibit good performance in stabilizing micro-droplets of oil within the aging time scale of milliseconds. Herein, the stabilities of micro-droplets of n-hexadecane in the presence of a biosurfactant, surfactin (C15-SFT), and a chemically synthesized surfactant, sodium cetyl benzene sulfonate (8-SCBS), were investigated using a microfluidic method. The coalescence frequency of micro-droplets, the evolution of micro-droplet size, and the coalescence time of micro-droplets were evaluated. The results indicated that C15-SFT exhibited superiority over 8-SCBS in stabilizing the micro-droplets of n-hexadecane. Biosurfactant C15-SFT effectively reduced the fusion probability between oil droplets and elongated the coalescence time compared to 8-SCBS, and these phenomena were obvious at a shorter aging time (150 ms) and lower surfactant concentration (0.1 × critical micelle concentration). The stabilities of micro-droplets increased with aging time and the bulk concentration of surfactants. Stable micro-droplets of n-hexadecane were formed in 1 × 10-4 mol L-1 C15-SFT solution at 600 ms aging time, and the bulk concentration was 1 × 10-3 mol L-1 in the case of 8-SCBS. The micro-droplets rarely coalesced in the presence of 1 × 10-4 mol L-1 C15-SFT after 600 ms aging time, but the micro-droplets in 1 × 10-4 mol L-1 8-SCBS coalesced frequently in the midstream and downstream of the coalescence chamber, and big droplets were dominant in the emulsion. The coalescence time of micro-droplets stabilized by C15-SFT was obviously longer than that of those stabilized by 8-SCBS under the same condition, indicating that the interfacial film formed by C15-SFT has much strength to resist coalescence during collisions. This work is helpful for understanding the activity of lipopeptides in the very short early stage of the emulsification process, laying the foundation for biosurfactant research in the fields of enhanced oil recovery, bioremediation of contaminated water or soil, etc.

Review of the role of surfactant dynamics in drop microfluidics

Surfactants are employed in microfluidic systems not just for drop stabilisation, but also to study local phenomena in industrial processes. On the scale of a single drop, these include foaming, emulsification and stability of foams and emulsions using statistically significant ensembles of bubbles or drops respectively. In addition, surfactants are often a part of a formulation in microfluidic drop reactors. In all these applications, surfactant dynamics play a crucial role and need to be accounted for. In this review, the effect of surfactant dynamics is considered on the level of standard microfluidic operations: drop formation, movement in channels and coalescence, but also on a more general level, considering the mechanisms controlling surfactant adsorption on time- and length-scales characteristic of microfluidics. Some examples of relevant calculations are provided. The advantages and challenges of the use of microfluidics to measure dynamic interfacial tension at short time-scales are discussed.

Surfactant-laden droplet size prediction in a flow-focusing microchannel: a data-driven approach

The control of droplet formation and size using microfluidic devices is a critical operation for both laboratory and industrial applications, e.g. in micro-dosage. Surfactants can be added to improve the stability and control the size of the droplets by modifying their interfacial properties. In this study, a large-scale data set of droplet size was obtained from high-speed imaging experiments conducted on a flow-focusing microchannel where aqueous surfactant-laden droplets were generated in silicone oil. Three types of surfactants were used including anionic, cationic and non-ionic at concentrations below and above the critical micelle concentration (CMC). To predict the final droplet size as a function of flow rates, surfactant type and concentration of surfactant, two data-driven models were built. Using a Bayesian regularised artificial neural network and XGBoost, these models were initially based on four inputs (flow rates of the two phases, interfacial tension at equilibrium and the normalised surfactant concentration). The mean absolute percentage errors (MAPE) show that data-driven models are more accurate (MAPE = 3.9%) compared to semi-empirical models (MAPE = 11.4%). To overcome experimental difficulties in acquiring accurate interfacial tension values under some conditions, both models were also trained with reduced inputs by removing the interfacial tension. The results show again a very good prediction of the droplet diameter. Finally, over 10 000 synthetic data were generated, based on the initial data set, with a Variational Autoencoder (VAE). The high-fidelity of the extended synthetic data set highlights that this method can be a quick and low-cost alternative to study microdroplet formation in future lab on a chip applications, where experimental data may not be readily available.

Surface behaviors of droplet manipulation in microfluidics devices

In recent years, the rapid development of microfluidic technology has caused a revolutionary impact in the fields of chemistry, medicine, and life sciences. Also, droplet control is one of the most important technologies in the field of microfluidics. In order to achieve different degrees of droplet transport, the dynamic balance of the competing processes of droplet driving force and fluid resistance should be controlled to achieve good selectivity of droplet transport. Here, we focus on the principles of droplet transport in microfluidic devices, including the driving forces for droplet transport in fluids and the effects of transport properties on droplet transport. After that, the effects of external fields on the directional transport of droplets and the advantages and disadvantages of each external field in droplet transport are discussed in detail. Finally, the applications and challenges of droplet microfluidics in chemical, biomedical, and mechanical systems are comprehensively introduced.