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Updated: Apr 29, 2026

Double Emulsion Generation Using a Polydimethylsiloxane PDMS Co-axial Flow Focus Device

Double Emulsion Generation Using a Polydimethylsiloxane PDMS Co-axial Flow Focus Device

Published on: December 25, 2015

Commensurability-driven structural defects in double emulsions produced with two-step microfluidic techniques.

Alexandre Schmit¹, Louis Salkin, Laurent Courbin

¹IPR, UMR CNRS 6251, Campus Beaulieu, Université Rennes 1, 35042 Rennes, France. laurent.courbin@univ-rennes1.fr pascal.panizza@univ-rennes1.fr.

|May 24, 2014

Summary

This summary is machine-generated.

Researchers studied droplet encapsulation in microfluidics, finding complex dynamics and patterns. A simple model accurately predicts these arrangements based on production timescales, validated by experiments.

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Last Updated: Apr 29, 2026

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Area of Science:

Fluid dynamics
Microfluidics
Materials science

Background:

Double emulsions and fluid-based materials are fabricated using combined drop makers like flow focusing or T-junctions.
Understanding droplet encapsulation is crucial for controlling these fabrication processes.

Purpose of the Study:

To investigate the complex physics governing the encapsulation of small droplets within larger drops.
To develop a predictive model for the patterns and arrangements observed during sequential droplet encapsulation.

Main Methods:

Observing and analyzing the number of encapsulated droplets over time in consecutive drop sequences.
Developing a discrete mathematical model based on droplet and drop production timescales.
Validating the model's predictions through experimental results.

Main Results:

Complex dynamics were observed, characterized by a sequence of distinct patterns and defects.
The discrete model successfully predicted the nature of these patterns.
The arrangement scheme of patterns in a sequence was accurately predicted as a function of timescale ratios.

Conclusions:

The study elucidates the complex physics of droplet encapsulation in microfluidic systems.
A simple discrete model effectively predicts observed encapsulation patterns based on timescale ratios.
Experimental validation confirms the model's accuracy, offering insights into controlling emulsion fabrication.