Super-resolution Raman imaging towards visualisation of nanoplastics

Abstract

Confocal Raman imaging can potentially identify and visualise microplastics and nanoplastics, but the imaging lateral resolution is hampered by the diffraction of the laser, making it difficult to analyse nanoplastics that are smaller than the laser spot and the lateral resolution limit (λ/2NA). Fortunately, once a nanoplastic is scanned to collect the spectrum via a position/pixel array as a spectrum matrix, akin to a hyperspectral matrix, the nanoplastic can be imaged by mapping the spectrum intensity as a pattern that is transcended axially and can be fitted as a 2D Gaussian surface. The Gaussian fitting and image re-construction by deconvolution can precisely predict the nanoplastic's position and approximate size, and potentially enhance the signal intensity. Several algorithms are also employed to decode the spectrum matrix, to improve the Raman images before the subsequent image re-construction. Overall, general confocal microscopy can also break through the diffraction limit of the excitation light by using algorithms, resulting in super-resolution Raman imaging to capture nanoplastics.