Elsayed Ahmed A, Erfan Mazen, Sabry Yasser M, Dris Rachid, Gaspéri Johnny, Barbier Jean-Sébastien, Marty Frédéric, Bouanis Fatima, Luo Shaobo, Nguyen Binh T T, Liu Ai-Qun, Tassin Bruno, Bourouina Tarik
ESYCOM, CNRS UMR 9007, Univ. Gustave Eiffel, ESIEE Paris, 93162, Noisy-le-Grand, France.
ECE Department, Faculty of Engineering, Ain Shams University, 1 El-Sarayat St, Cairo, 11517, Egypt.
Sci Rep. 2021 May 18;11(1):10533. doi: 10.1038/s41598-021-89960-4.
Microplastics contaminating drinking water is a growing issue that has been the focus of a few recent studies, where a major bottleneck is the time-consuming analysis. In this work, a micro-optofluidic platform is proposed for fast quantification of microplastic particles, the identification of their chemical nature and size, especially in the 1-100 µm size range. Micro-reservoirs ahead of micro-filters are designed to accumulate all trapped solid particles in an ultra-compact area, which enables fast imaging and optical spectroscopy to determine the plastic nature and type. Furthermore, passive size sorting is implemented for splitting the particles according to their size range in different reservoirs. Besides, flow cytometry is used as a reference method for retrieving the size distribution of samples, where chemical nature information is lost. The proof of concept of the micro-optofluidic platform is validated using model samples where standard plastic particles of different size and chemical nature are mixed.
微塑料污染饮用水是一个日益严重的问题，已成为近期一些研究的焦点，其中一个主要瓶颈是耗时的分析。在这项工作中，提出了一种微流控光学平台，用于快速定量微塑料颗粒，识别其化学性质和尺寸，特别是在1-100微米尺寸范围内。微滤器前方的微储液器设计用于将所有捕获的固体颗粒聚集在一个超紧凑区域，这使得能够进行快速成像和光谱分析以确定塑料的性质和类型。此外，还实施了被动尺寸分选，以便根据颗粒的尺寸范围在不同储液器中进行分离。此外，流式细胞术用作参考方法来获取样品的尺寸分布，但会丢失化学性质信息。使用混合了不同尺寸和化学性质的标准塑料颗粒的模型样品验证了微流控光学平台的概念验证。
