Centrifugal microfluidic chip for multi-stage sorting and detection of microplastics at micron scale

As an emerging contaminant, microplastics(MPs) have been widely detected in the environment, the environmental risks it poses are also becoming more prominent. Among them, micron-sized MPs have relatively higher biotoxicity, necessitating a technique for processing and analysis to separate them by particle size and analyze their composition. The most commonly used MPs separation technology at present is the membrane filtration, which is easily to cause membrane blockage and set error accumulation. Centrifugal microfluidic technology received great attention as a high efficiency, low error and simple operation technology, has great potential for the separation of MPs.

In this paper, we have reported a multi-stage centrifugal microfluidic chip for the separation and detection of MPs (with diameter less than 63 μm). MPs of different diameters ranges were separated under the combination of Centrifugal force and Coriolis force, and orderly captured in four separation chambers according to their sizes. The capture rate of the microfluidic chip for polystyrene microspheres can reach about 87%. We also successfully separated MPs with irregular shapes. Under a rotation speed of 3500-4000 rpm, the maximum Pearson correlation coefficient between the volume equivalent diameters of the irregular MPs and the capture positions was about 0.84. Our proposed separation method was also applicable to MPs mixtures, which were successfully used for the separation of PVC, PC, and PS particles. The separated MPs can be directly identified to determine their chemical composition by Raman detection.

The experimental results demonstrate that our strategy is promising for separating and detecting MPs of different particle sizes in the environment and effectively overcomes the problem of error accumulation in traditional membrane separation methods. Furthermore, the device and methods developed in this study provide a foundational framework for formulating robust environmental risk assessment system.