Journal
PHYSICS OF FLUIDS
Volume 34, Issue 10, Pages -Publisher
AIP Publishing
DOI: 10.1063/5.0117073
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Funding
- Scientific and Technological Research Council of T_urkiye (TUBITAK) [121N238]
- Iranian Ministry of Science, Research and Technology (MSRT)
- University of Tabriz [IRTU-2-1419]
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This study aims to simulate the high-throughput formation of nanoscale liposomes using an active electrohydrodynamic-based micromixer. The presence of an electrical field inside the microchannel generates chaotic advection, leading to an increase in the formation of liposomes. The Taguchi method is used to optimize the experimental design, resulting in a 5.3% error between the predicted and simulated results.
Liposomes are one of the most attractive particles in different industries, especially pharmaceutical applications. The main reasons for such a desire for liposomes are nontoxicity, small size, the ability to encapsulate and carry biological components, and finally biocompatibility and biodegradability. The present study aims to simulate the active electrohydrodynamic-based micromixer for the high-throughput formation of nanoscale liposomes. The micromixer consists of two inlets for de-ionized water and one inlet for ethanol with lipid particles. Two configurations of asymmetric electrodes, namely, longitudinal and the array of electrodes, were introduced and examined. Electrodes were placed at the bottom of the mixer, and a direct current electrical field was applied to them. Generated chaotic advection inside the microchannel by the electrical field and, consequently, increasing surface-to-volume ratio is the main reason for the increase in the formation of liposomes. These configurations of electrodes cause the liposome formation occurs at very low voltages, which is the most advantage of the proposed micromixer. The Taguchi method as a statistical method of design of experiment (DOE) was utilized to reduce the number of required simulations. The simulations showed that case 6 had the best mixing index of 0.586 among the studied models. Also, according to the DOE results, the best possible design was found and simulated and a mixing index of 0.743, which has a 5.3% error in comparison to the predicted results.
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