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Bio-inspired uniform flow microfluidic sensor platform for multi-analyte sensing: a simulation-based outflow and injection study
P. Gharpure, S. Veeralingam,
Published in Springer Science and Business Media Deutschland GmbH
2021
Volume: 25
   
Issue: 10
Abstract
Inspirations from nature coupled with engineering have proven to be extremely beneficial in developing microfluidic platforms that have an edge over other sensing methods owing to their sensitivity, low chemical hazard risk and suitability to simulation-based studies due to the laminar nature of microflows. This work depicts a bio-inspired microfluidic platform comprising of multichannel network that mimics tentacled bio-species both in morphology and their functionality wherein each channel is designed to perform a unique sensing operation. The design is improvised geometrically based on the requirement of a streamlined flow pattern, with a uniform velocity profile in all the tentacles, along with a uniform outflow for an effective and sensitive real time applicability. The simulations are performed by adopting the Finite Volume Method (FVM) using ANSYS Fluent, under the 3-Dimensional, incompressible, Newtonian flow assumption. The laminar, biphasic approach is adopted for the modelling. The flow pattern, parameters of interest and the response of the sensor are also studied based on the possible injection methods applied, to provide an insight into the role of injection in the functionality and to analyze the suitability of the sensor in bio-analytical applications. The bio-inspired platform paves way for developing similar suitable novel architectures for handling multiple sensing operations simultaneously, in an integrated manner, which can lead to the development of efficient, integrated sensing platforms. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
About the journal
JournalData powered by TypesetMicrofluidics and Nanofluidics
PublisherData powered by TypesetSpringer Science and Business Media Deutschland GmbH
ISSN16134982
Open AccessNo