Circuit-Based Design of Microfluidic Drop Networks.

capillary pressure fluid shear stress hanging-drop network hydraulic-circuit analogy hydrostatic pressure standing-drop network

Journal

Micromachines
ISSN: 2072-666X
Titre abrégé: Micromachines (Basel)
Pays: Switzerland
ID NLM: 101640903

Informations de publication

Date de publication:
16 Jul 2022
Historique:
received: 08 06 2022
revised: 11 07 2022
accepted: 12 07 2022
entrez: 27 7 2022
pubmed: 28 7 2022
medline: 28 7 2022
Statut: epublish

Résumé

Microfluidic-drop networks consist of several stable drops-interconnected through microfluidic channels-in which organ models can be cultured long-term. Drop networks feature a versatile configuration and an air-liquid interface (ALI). This ALI provides ample oxygenation, rapid liquid turnover, passive degassing, and liquid-phase stability through capillary pressure. Mathematical modeling, e.g., by using computational fluid dynamics (CFD), is a powerful tool to design drop-based microfluidic devices and to optimize their operation. Although CFD is the most rigorous technique to model flow, it falls short in terms of computational efficiency. Alternatively, the hydraulic-electric analogy is an efficient "first-pass" method to explore the design and operation parameter space of microfluidic-drop networks. However, there are no direct electric analogs to a drop, due to the nonlinear nature of the capillary pressure of the ALI. Here, we present a circuit-based model of hanging- and standing-drop compartments. We show a phase diagram describing the nonlinearity of the capillary pressure of a hanging drop. This diagram explains how to experimentally ensure drop stability. We present a methodology to find flow rates and pressures within drop networks. Finally, we review several applications, where the method, outlined in this paper, was instrumental in optimizing design and operation.

Identifiants

pubmed: 35888941
pii: mi13071124
doi: 10.3390/mi13071124
pmc: PMC9315978
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Subventions

Organisme : Innosuisse - Swiss Innovation Agency
ID : 38880.1 IP-LS
Organisme : Swiss National Science Foundation
ID : 51NF40_180541
Pays : Switzerland
Organisme : Fonds de Recherche du Québec - Nature et Technologies
ID : 199851
Organisme : Swiss National Science Foundation
ID : 31003A_179337
Pays : Switzerland

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Auteurs

Nassim Rousset (N)

Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, CH-4058 Basel, Switzerland.

Christian Lohasz (C)

Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, CH-4058 Basel, Switzerland.

Julia Alicia Boos (JA)

Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, CH-4058 Basel, Switzerland.

Patrick M Misun (PM)

Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, CH-4058 Basel, Switzerland.

Fernando Cardes (F)

Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, CH-4058 Basel, Switzerland.

Andreas Hierlemann (A)

Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, CH-4058 Basel, Switzerland.

Classifications MeSH