Literature DB >> 18352282

Droplet traffic in microfluidic networks: a simple model for understanding and designing.

Michael Schindler1, Armand Ajdari.   

Abstract

We propose a simple model to analyze the traffic of droplets in microfluidic "dual networks." Such functional networks which consist of two types of channels, namely, those accessible or forbidden to droplets, often display a complex behavior characteristic of dynamical systems. By focusing on three recently proposed configurations, we offer an explanation for their remarkable behavior. Additionally, the model allows us to predict the behavior in different parameter regimes. A verification will clarify fundamental issues, such as the network symmetry, the role of the driving conditions, and of the occurrence of reversible behavior. The model lends itself to a fast numerical implementation, thus can help designing devices, identifying parameter windows where the behavior is sufficiently robust for a device to be practically useful, and exploring new functionalities.

Year:  2008        PMID: 18352282     DOI: 10.1103/PhysRevLett.100.044501

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  9 in total

1.  Extracting the hydrodynamic resistance of droplets from their behavior in microchannel networks.

Authors:  Vincent Labrot; Michael Schindler; Pierre Guillot; Annie Colin; Mathieu Joanicot
Journal:  Biomicrofluidics       Date:  2009-03-30       Impact factor: 2.800

2.  Coalescing drops in microfluidic parking networks: A multifunctional platform for drop-based microfluidics.

Authors:  Swastika S Bithi; William S Wang; Meng Sun; Jerzy Blawzdziewicz; Siva A Vanapalli
Journal:  Biomicrofluidics       Date:  2014-06-25       Impact factor: 2.800

3.  Millifluidics as a simple tool to optimize droplet networks: Case study on drop traffic in a bifurcated loop.

Authors:  William S Wang; Siva A Vanapalli
Journal:  Biomicrofluidics       Date:  2014-12-01       Impact factor: 2.800

4.  Bistability in droplet traffic at asymmetric microfluidic junctions.

Authors:  Pravien Parthiban; Saif A Khan
Journal:  Biomicrofluidics       Date:  2013-08-23       Impact factor: 2.800

5.  Agent-based simulations of complex droplet pattern formation in a two-branch microfluidic network.

Authors:  Bradford J Smith; Donald P Gaver
Journal:  Lab Chip       Date:  2009-11-27       Impact factor: 6.799

Review 6.  Droplets formation and merging in two-phase flow microfluidics.

Authors:  Hao Gu; Michel H G Duits; Frieder Mugele
Journal:  Int J Mol Sci       Date:  2011-04-15       Impact factor: 5.923

7.  Non-Newtonian droplet-based microfluidics logic gates.

Authors:  Elmira Asghari; Ali Moosavi; Siamak Kazemzadeh Hannani
Journal:  Sci Rep       Date:  2020-06-09       Impact factor: 4.379

8.  Simulation before fabrication: a case study on the utilization of simulators for the design of droplet microfluidic networks.

Authors:  Andreas Grimmer; Xiaoming Chen; Medina Hamidović; Werner Haselmayr; Carolyn L Ren; Robert Wille
Journal:  RSC Adv       Date:  2018-10-10       Impact factor: 3.361

9.  Optimal occlusion uniformly partitions red blood cells fluxes within a microvascular network.

Authors:  Shyr-Shea Chang; Shenyinying Tu; Kyung In Baek; Andrew Pietersen; Yu-Hsiu Liu; Van M Savage; Sheng-Ping L Hwang; Tzung K Hsiai; Marcus Roper
Journal:  PLoS Comput Biol       Date:  2017-12-15       Impact factor: 4.475

  9 in total

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