Three-factor response surface optimization of nano-emulsion formation using a microfluidizer

Area of Science:

• Food Science and Technology
• Colloid and Surface Science
• Chemical Engineering

Background:

• Nano-emulsions offer enhanced delivery and stability for various applications.
• Microfluidization is a key technique for producing nano-emulsions.
• Understanding process parameter effects is crucial for optimizing nano-emulsion fabrication.

Purpose of the Study:

• To optimize sunflower oil-in-water nano-emulsion fabrication using microfluidization.
• To investigate the influence of pressure, oil content, and number of passes on emulsion characteristics.
• To model and predict Sauter mean diameter (SMD) and Polydispersity Index (PdI) using Response Surface Methodology (RSM).

Main Methods:

• Utilized microfluidization for sunflower oil-in-water emulsification.
• Employed Response Surface Methodology (RSM) with a Central Composite Design (CCD).
• Analyzed the effects of pressure (408-952 bar), oil content (5-13 vol%), and passes (2-4 cycles) on SMD and PdI.

Main Results:

• Optimal SMD and PdI were achieved within specific pressure ranges; excessive pressure increased both.
• Increased number of passes (2 to 4 cycles) consistently improved both SMD and PdI.
• Oil content had a minor direct effect but significant interactions with other parameters.
• Laminar elongational flow identified as a disruption mechanism alongside turbulent flow.

Conclusions:

• RSM models accurately predicted nano-emulsion characteristics (SMD, PdI).
• Microfluidization parameters, particularly pressure and passes, significantly influence nano-emulsion quality.
• The study provides insights into optimizing nano-emulsion production for enhanced stability and functionality.