Evidence map›Paper›PMID 35888941›Full record

ReviewMicromachines2022

Circuit-Based Design of Microfluidic Drop Networks.

Nassim Rousset, Christian Lohasz, Julia Alicia Boos, Patrick M Misun, Fernando Cardes, Andreas Hierlemann

Abstract readReview
In one paragraph

Review in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Periodic Flows in Microfluidics.Small (Weinheim an der Bergstrasse, Germany) · 2024
    Review
  4. Article
  5. Article
  6. Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Nassim RoussetBioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, CH-4058 Basel, Switzerland.ORCID 0000-0001-6739-4065
Christian LohaszBioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, CH-4058 Basel, Switzerland.ORCID 0000-0001-8575-7392
Julia Alicia BoosBioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, CH-4058 Basel, Switzerland.
Patrick M MisunBioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, CH-4058 Basel, Switzerland.
Fernando CardesBioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, CH-4058 Basel, Switzerland.ORCID 0000-0003-1880-6734
Andreas HierlemannBioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, CH-4058 Basel, Switzerland.ORCID 0000-0002-3838-2468

Funding

Fonds de Recherche du Québec - Nature et Technologies 199851Innosuisse - Swiss Innovation Agency 38880.1 IP-LSSwiss National Science Foundation 31003A_179337Swiss National Science Foundation 51NF40_180541
6 · The paper itself

Abstract

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.

Indexed as

capillary pressurefluid shear stresshanging-drop networkhydraulic-circuit analogyhydrostatic pressurestanding-drop network

Identifiers

PMID35888941
PMCPMC9315978

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.