2023
DOI: 10.1039/d3sd00099k
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Machine learning based microfluidic sensing device for viscosity measurements

Adil Mustafa,
Daniyal Haider,
Arnab Barua
et al.

Abstract: An increase in microsensor deflection with an increase in blood viscosity during coagulation.

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Cited by 3 publications
(3 citation statements)
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“…The important simulation parameters for the microfluidic viscometer include the range of viscosities and flow rates as well as the micropillar and channel dimensions. Following the design parameters utilized in our previous experimental work [21,22], we examined a viscosity range of µ = 5-100 cP, and a flow rate between Q = 15-105 mL/h. For the micropillar and channel dimensions, we set the diameter of the micropillars at D = 300 µm, and varied the pillar aspect ratio ( AR) between 3 and 5, corresponding to a pillar height between H = 900 and 1500 µm.…”
Section: Simulation Parametersmentioning
confidence: 99%
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“…The important simulation parameters for the microfluidic viscometer include the range of viscosities and flow rates as well as the micropillar and channel dimensions. Following the design parameters utilized in our previous experimental work [21,22], we examined a viscosity range of µ = 5-100 cP, and a flow rate between Q = 15-105 mL/h. For the micropillar and channel dimensions, we set the diameter of the micropillars at D = 300 µm, and varied the pillar aspect ratio ( AR) between 3 and 5, corresponding to a pillar height between H = 900 and 1500 µm.…”
Section: Simulation Parametersmentioning
confidence: 99%
“…We have recently developed a novel method for measuring the viscosity of Newtonian and non-Newtonian fluids [21,22]. This method involves fluid-structure interactions and measures the deflection of elastic polydimethylsiloxane (PDMS) micropillars in response to fluid flow to determine the viscosity.…”
Section: Introductionmentioning
confidence: 99%
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