Abstract
This paper describes the development of a novel microfluidic platform for multifactorial analysis integrating four label-free detection methods: electrical impedance, refractometry, optical absorption and fluorescence. We present the rationale for the design and the details of the microfabrication of this multifactorial hybrid microfluidic chip. The structure of the platform consists of a three-dimensionally patterned polydimethylsiloxane top part attached to a bottom SU-8 epoxy-based negative photoresist part, where microelectrodes and optical fibers are incorporated to enable impedance and optical analysis. As a proof of concept, the chip functions have been tested and explored, enabling a diversity of applications: (i) impedance-based identification of the size of micro beads, as well as counting and distinguishing of erythrocytes by their volume or membrane properties; (ii) simultaneous determination of the refractive index and optical absorption properties of solutions; and (iii) fluorescence-based bead counting.
Highlights
Miniaturization and portability, increased automation, minimum reagent consumption, high throughput and reduced manufacturing costs are some of the strongest motivations towards the development of microfluidic platforms [1,2]
We describe the steps towards the implementation of a multifactorial analysis microfluidic device capable of such multifactorial analysis
To align the optical fibers, 126 μm × 126 μm grooves were patterned and placed in front of each other being separated by the fluidic channel (~20 μm wide)
Summary
Miniaturization and portability, increased automation, minimum reagent consumption, high throughput and reduced manufacturing costs are some of the strongest motivations towards the development of microfluidic platforms [1,2]. Scaling down very often imposes limitations on the usable detection methods In this regard, the very high sensitivity and intrinsic scalability of some analytical optical methods make them appropriate choices for incorporation in microfluidic sensing platforms [3]. It is recognized that the simultaneous use of multiple techniques to characterize the same sample can provide more complete information and allow better discrimination in a diversity of diagnostic and analytical applications. This is true, for instance, in environmental applications where the ability to handle complex and highly variable sample matrices in microfluidic devices is of paramount importance [2]
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