Analysis of the Diffusion Process by pH Indicator in Microfluidic Chips for Liposome Production

Area of Science:

• Nanotechnology and Materials Science
• Chemical Engineering
• Biomedical Engineering

Background:

• Microfluidic methods are highly effective for producing nanoparticles, particularly liposomes, for drug delivery due to precise control over size, dispersity, and encapsulation efficiency.
• Liposome formation in microfluidics is driven by the diffusive mass transfer of chemical species at solvent-non-solvent interfaces, typically alcohol and water.
• Accurate characterization of mixing processes is essential for optimizing liposome production and ensuring the quality of drug delivery systems.

Purpose of the Study:

• To develop and demonstrate a new method for analyzing mixing processes within microfluidic devices.
• To characterize the transfer of ethanol and water in different microfluidic architectures using the developed method.
• To provide an experimental approach for validating numerical models of microfluidic mixing.

Main Methods:

• A novel approach utilizing a pH indicator was developed to analyze mixing dynamics in microfluidic systems.
• The method was applied to characterize the diffusion and advection of ethanol and water.
• Two distinct microfluidic device architectures were employed to assess the method's versatility.

Main Results:

• The pH indicator method successfully characterized mixing processes, including the transfer of ethanol and water, in the studied microfluidic devices.
• The experimental results provided insights into diffusion and advection phenomena governing microfluidic mixing.
• The study demonstrated the utility of the pH indicator approach for analyzing microfluidic systems.

Conclusions:

• The developed pH indicator-based method offers an effective experimental route to characterize diffusion and advection in microfluidics.
• This approach is valuable for understanding and optimizing the formation of vesicular and micellar systems, such as liposomes.
• The method can serve as a tool for validating computational fluid dynamics (CFD) models used in microfluidic research.