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License: CC BY NC SA
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Sensors and Actuators B Chemical
Article . 2018 . Peer-reviewed
License: Elsevier TDM
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Numerical prototyping of lateral flow biosensors

Authors: Schaumburg, Federico; Kler, Pablo Alejandro; Berli, Claudio Luis Alberto;

Numerical prototyping of lateral flow biosensors

Abstract

Abstract Lateral flow biosensors (LFB) have become a hot topic in the scientific literature in association with the rapid growing of paper-based microfluidics. Improving the existing LFB technology is a challenging task that demands large experimental efforts. Thus computer simulations are practical tools to assist the development of novel devices, since running virtual experiments considerably reduces costs and time in the path from design to real LFB prototypes. We present a computational tool for 3D numerical prototyping of LFB, which accounts for the fluid dynamics (including capillary-driven flow) in the heterogeneous porous materials, the transport of reactive components, and all the biochemical reactions involved. Mathematical modeling was carried out in the framework of continuum transport phenomena, and numerical calculations were implemented by using the finite element method. This numerical prototyping allows developers to explore arbitrary architectures, materials, and assay formats, which is demonstrated here by discussing different real-world examples. The advantages of the proposed numerical model are also discussed in relation to up-to-date reported methods.

Country
Argentina
Keywords

Lateral flow biosensor, Paper-based microfluidics, Lateral flow immunoassay, Numerical prototype, https://purl.org/becyt/ford/2.11, https://purl.org/becyt/ford/2

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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    28
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
28
Top 10%
Top 10%
Top 10%
Green