DOI: https://doi.org/10.29363/nanoge.eimc.2021.021
Publication date: 5th July 2021
Absorbance measurement is a useful analytical tool that can be used along with colorimetric assays to measure a wide range of analytes. However, since sensitivity is directly proportional to path length, sensitive measurements in microfluidic channels are inherently challenging. This is especially true for droplet microfluidics where the lensing at the droplet/carrier interface further constrains path length. Conventional sensitivity enhancement approaches such as extended path length geometries and cavity-enhanced systems could still suffer from the lensing effect, high cost optics and high power consumption.[1, 2] This limits their applicability in low resources settings such as in-the-field or point-of-care analysis. Hence there is an urgent need to design low cost flow cells that can deliver enhanced measurement sensitivities but at lower power consumption.
In this study, we developed multipass flow cells assembled with squared PTFE tube with parallel mirrors on both sides, laser diode and detector. The devices were integrated with T-junction droplet microfluidic chip for in-line droplet absorbance spectroscopy, where reagents and samples were introduced into droplets for quantifying phosphate level via phosphomolybdeum blue reaction. They featured affordable low power components, and was made using simple fabrication techniques making it accessible to a wide range of researchers. In testing they allowed multiple reflections of light in the detection chambers, which significantly increased the optical path length by 8 times and reached low limit of detection of phosphate at around 0.52 uM.
The optimised flow cell was used to determine phosphate concentrations in water samples collected from a tidal chalk river which could not be measured with a simple single-pass flow cell. We envision this flow cell design to be broadly applied for detection of trace species on droplet microfluidics to achieve high sensitivity and low limit of detection, especially for environmental and biomedical monitoring.
We thank the UK’s Natural Environment Research Council for funding (NE/R013578/1, NE/S013458/1, NE/T010584/1).
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