Predictive model for the size of bubbles and droplets created in microfluidic T-junctions

Area of Science:

• Fluid dynamics
• Microfluidics
• Physical chemistry

Background:

• Microfluidic devices are widely used for generating bubbles and droplets.
• Existing models lack a physically sound, predictive expression for bubble and droplet size.
• Precise control over bubble and droplet dimensions is crucial for many applications.

Purpose of the Study:

• To develop a closed-form expression for predicting bubble and droplet size in T-junctions.
• To provide a theoretical model that explains the influence of T-junction geometry on droplet/bubble size.
• To enable tuning of T-junction shape for desired bubble and droplet dimensions.

Main Methods:

• Development of a theoretical model based on continuity, geometry, and pinch-off mechanisms.
• Derivation of a closed-form expression for bubble and droplet size prediction.
• Experimental validation using various T-junction shapes and multiphase microfluidic conditions.

Main Results:

• A novel, fitting-free closed-form expression for predicting bubble and droplet size was derived.
• The model successfully explains the strong dependence of size on T-junction shape.
• Experimental validation confirmed the model's accuracy for both gas bubbles and liquid droplets.

Conclusions:

• The presented theoretical model offers a simple yet effective method for predicting bubble and droplet size in T-junctions.
• T-junction geometry can be intentionally designed to control the size of generated bubbles and droplets.
• This work provides a valuable tool for optimizing microfluidic applications requiring precise droplet and bubble generation.