Mesoscale modelling of droplets’ self-assembly in microfluidic channels,Soft Matter

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Mesoscale modelling of droplets’ self-assembly in microfluidic channels
Soft Matter ( IF 2.9 ) Pub Date : 2021-1-25 , DOI: 10.1039/d0sm02047h
Andrea Montessori _{1,

2,

3} , Adriano Tiribocchi _{1,

2,

3,

4,

5} , Marco Lauricella _{1,

2,

3} , Fabio Bonaccorso _{1,

2,

3,

4,

5} , Sauro Succi _{1,

2,

3,

4,

5}

Affiliation

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.

中文翻译：

微流控通道中液滴自组装的中尺度建模

最近提出了一种中尺度方法，用于模拟具有近接触相互作用的多组分流动，以研究微流体通道中软流动晶体的早期形成和聚类统计。具体而言，我们首先证明了上述中尺度模型能够准确重现导致形成两个基本液滴模式（三角形和六边形）的主要机制的能力，与实验证据非常吻合。接下来，我们基于液滴图案的Delaunay三角剖分和Voronoi图分析，通过引入新的取向有序参数，定量评估晶体形成过程的器件级聚集效率。

更新日期：2021-02-16

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