A recently proposed mesoscale approach for the simulation of multicomponent flows with near-contact interactions is employed to investigate the early stage formation and clustering statistics of soft flowing crystals in microfluidic channels. Specifically, we first demonstrate the ability of the aforementioned mesoscale model to accurately reproduce main mechanisms leading to the formation of two basic droplet patterns (triangular and hexagonal), in close agreement with experimental evidence. Next, we quantitatively evaluate the device-scale clustering efficiency of the crystal formation process by introducing a new orientational order parameter, based on the Delaunay triangulation and Voronoi diagrams analysis of the droplet patterns. The mesoscale computational approach employed in this work proves to be an efficient tool to shed new light on the complex dynamics of dense emulsions, from short-scale thin-film hydrodynamics, all the way up to global structure formation and statistics of the resulting droplets ensembles.

Montessori, A., Tiribocchi, A., Lauricella, M., Bonaccorso, F., & Succi, S. (2021). Mesoscale modelling of droplets’ self-assembly in microfluidic channels. SOFT MATTER, 17(9), 2374-2383 [10.1039/d0sm02047h].

Mesoscale modelling of droplets’ self-assembly in microfluidic channels

Montessori A.;
2021

Abstract

A recently proposed mesoscale approach for the simulation of multicomponent flows with near-contact interactions is employed to investigate the early stage formation and clustering statistics of soft flowing crystals in microfluidic channels. Specifically, we first demonstrate the ability of the aforementioned mesoscale model to accurately reproduce main mechanisms leading to the formation of two basic droplet patterns (triangular and hexagonal), in close agreement with experimental evidence. Next, we quantitatively evaluate the device-scale clustering efficiency of the crystal formation process by introducing a new orientational order parameter, based on the Delaunay triangulation and Voronoi diagrams analysis of the droplet patterns. The mesoscale computational approach employed in this work proves to be an efficient tool to shed new light on the complex dynamics of dense emulsions, from short-scale thin-film hydrodynamics, all the way up to global structure formation and statistics of the resulting droplets ensembles.
Montessori, A., Tiribocchi, A., Lauricella, M., Bonaccorso, F., & Succi, S. (2021). Mesoscale modelling of droplets’ self-assembly in microfluidic channels. SOFT MATTER, 17(9), 2374-2383 [10.1039/d0sm02047h].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11590/400490
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