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Article Tier 2 Food & Water Policy & Risk Sign in to save

Towards online monitoring of water pollutants: an optofluidic chip for characterizing microplastics in water

2024

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Researchers developed a miniaturized, low-cost optofluidic chip for online monitoring and characterization of microplastics in drinking water, enabling real-time detection without sample pre-concentration. The smart chip design integrated optical and microfluidic components to identify and size microplastic particles, demonstrating feasibility for continuous water quality surveillance.

Polymers
Study Type Environmental

Online monitoring of water pollutants is of great importance for the early detection of contaminants and improving the quality of drinking water. We showcase a smart design of a miniaturized, low-cost, versatile, and handheld optofluidic chip for characterizing microplastics (MPs) in water, which are a potential threat to our environment. The chip encompasses all the required optics for guiding the light to/from the microfluidics, all sandwiched together as a unique miniaturized system. Size and concentration of MPs are characterized by measuring the static light scattering (SLS) signal at two different angles: 0 and 40 degrees. In fact, the concentration of MPs is obtained by observing the SLS signal only at one angle, while for the size of MPs one needs to calculate the variation of signal at two concentrations. In a next step, the performance of the optofluidic chip is benchmarked against a commercial bulky system. The latter works based on a technique called “Goniophotometry”, capable of measuring the SLS signal at a broad range of scattering angles between - 90 and +90 degrees. Chemometric algorithms like Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are used to extract the size and concentration of MPs in water using the bulky system. The different sizes and concentrations of MPs are prepared using commercial Polystyrene (PS) beads. It is shown that the developed optofluidic microsystem provides a comparable performance to the commercial bulky machine and is thus a significant step towards the online monitoring of water pollutants, like MPs, in drinking water.

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