4.4 Article

Design and validation of microfluidic parameters of a microfluidic chip using fluid dynamics

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AIP ADVANCES
卷 11, 期 7, 页码 -

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AIP Publishing
DOI: 10.1063/5.0056597

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Analysis of internal fluidic parameters in microfluidic channels is essential for solving microfluidic problems involving thermal analysis, chemical reactivity, velocity, pressure drop, etc., crucial for developing high-quality chemical and biological products. Highly integrated simulation tools can help guide researchers in designing numerical prototypes of highly integrated devices to overcome the challenges of complex internal structures and kinetics in microfluidic channels.
The internal fluidic parameters of microfluidic channels must be analyzed to solve fundamental microfluidic problems, including microscale transport problems involving thermal analysis, chemical reactivity, velocity, pressure drop, etc., for developing good-quality chemical and biological products. Therefore, the characterization and optimization of the interaction of chemical and biological solutions through microfluidic channels are vital for fluid flow design and engineering for quality assurance in microfluidic platforms. As the internal structures and kinetics of microfluidic channels are becoming increasingly complex, experiments involving optimal fluidic and transport designs are challenging to perform with high accuracy. However, highly integrated simulation tools can guide researchers without specialized computational fluid backgrounds to design numerical prototypes of highly integrated devices. In this study, a microfluidic chip with two inlet wells and one outlet well was fabricated from polydimethylsiloxane following which simulations were performed using an ANSYS Fluent tool influenced by computational fluid dynamics at a nearly identical scale. The pressure drop and velocity profiles of the interaction of two pH buffer solutions (pH 4 and 10) through the designed microfluidic chip were qualitatively estimated from experimental data analysis and validated with the simulation results obtained from the CFD-influenced ANSYS Fluent tool. (c) 2021 Author(s).

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