We describe design and miniaturization of a polymeric optical interface for flow monitoring in biomicrofluidics applications based on polydimethylsiloxane technology, providing optical transparency and compatibility with biological tissues. Design and ray tracing simulation are presented as well as device realization and optical analysis of flow dynamics in microscopic blood vessels. Optics characterization of this polymeric microinterface in dynamic experimental conditions provides a proof of concept for the application of the device to two-phase flow monitoring in both in vitro experiments and in vivo microcirculation investigations. This technology supports the study of in vitro and in vivo microfluidic systems. It yields simultaneous optical measurements, allowing for continuous monitoring of flow. This development, integrating a well-known and widely used optical flow monitoring systems, provides a disposable interface between live mammalian tissues and microfluidic devices making them accessible to detection/processing technology, in support or replacing standard intravital microscopy.
A nonlinear analysis method based on the evaluation of d-infinite and largest Lyapunov exponent was used to study the complex dynamics of air bubbles carried by water and flowing in a microfluidic snake channel. A rich variety of nonlinear dynamics and flow patterns was found through the experimental observation of bubbles' motion. The results and their graphical representation show the capability of the proposed set of dimensionless parameters to classify the nonlinearity of the process showing also its sensitivity to input flow variations.
In this experimental study, the effects on twophase flow dynamics in a microfluidic snake channel due to periodic forcing were considered. Time series analysis was exploited to investigate on the obtained bubbles' flow considering two aspects: the role of driven frequency through Fourier analysis and the nonlinear behavior through the evaluation of d-infinite and Largest Lyapunov exponent. Phase diagrams summarize the results: the two nonlinear parameters are plotted versus the air fraction and the frequency of the input flow rates. The identified relation maps allow the classification of the flow dynamics, opening the way for the control of bubble flow through signal analysis.
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