High-Resolution Fluorescence Microscopy-Based 3D Encoding Using Polarity-Sensitive Dyes for Rapid Screening of...

Microplastics (MPs), as emerging pollutants of global concern, urgently require rapid monitoring techniques for effective ecological risk management. Fluorescence microscopy is widely utilized for capturing the morphology of MPs but remains limited in polymer-type discrimination and differentiation from environmental matrices. Herein, we present a novel fluorescence microscopy-based three-dimensional (3D) encoding strategy employing three polarity-sensitive dyes (DNAS, DCM, and MONS) for rapid screening of MPs in complex environmental matrices. Owing to differences in the surface polarity of MPs, the adsorbed polarity-sensitive dyes undergo intramolecular charge transfer (ICT). The polarity-dependent stabilization of the excited charge-transfer state alters the emission energy, resulting in distinct fluorescence colors on different MPs. The three dyes also exhibited varied ICT responses due to hydrogen-bonding and dipole-dipole interactions between the surface groups of MPs and the dyes, facilitating encoding-based discrimination. Stained images were captured with a self-constructed portable fluorescence microscope. The images were converted from RGB values into CIE L*a*b* coordinates to construct a 3D encoding library, where triangular or linear pattern encoding greatly enhanced the spatial separation of MPs and sample matrices. This method enabled rapid identification of 12 common MP types and clear differentiation from ten natural nonplastic matrices. The CIE L*a*b* coordinates exhibited good repeatability, with RSD values of 0.69-4.99% (n = 10). Both "known-as-unknown" spiked sample validation and the analysis of real environmental samples demonstrate that the proposed workflow can rapidly identify polymer types in complex samples, with the results agreeing well with those obtained by FTIR. This low-cost, portable, and spectrometer-free strategy offers a practical tool for rapid screening of MPs in complex environmental samples.