Mesoscale modelling of droplets' self-assembly in microfluidic channels

Area of Science:

• Fluid dynamics
• Soft matter physics
• Computational modeling

Background:

• Understanding the formation and clustering of soft flowing crystals in microfluidic channels is crucial for controlling emulsion properties.
• Existing models may not fully capture the interplay between short-scale hydrodynamics and large-scale structure formation.

Purpose of the Study:

• To investigate the early stage formation and clustering statistics of soft flowing crystals using a mesoscale simulation approach.
• To validate the mesoscale model against experimental observations of droplet pattern formation.
• To quantitatively assess the device-scale clustering efficiency of crystal formation.

Main Methods:

• Mesoscale simulation of multicomponent flows with near-contact interactions.
• Reproduction of triangular and hexagonal droplet pattern formation mechanisms.
• Introduction of a novel orientational order parameter based on Delaunay triangulation and Voronoi diagrams analysis.

Main Results:

• The mesoscale model accurately reproduces key mechanisms of droplet pattern formation (triangular and hexagonal).
• Quantitative evaluation of device-scale clustering efficiency was achieved using the new order parameter.
• The study provides insights into the transition from short-scale hydrodynamics to global structure formation.

Conclusions:

• The employed mesoscale computational approach is an efficient tool for studying dense emulsions.
• This method sheds light on the complex dynamics governing soft flowing crystal formation and clustering.
• The findings contribute to a better understanding of structure formation in microfluidic systems.