Fang Cheng, Luo Yunlong, Naidu Ravi
Global Centre for Environmental Remediation (GCER), University of Newcastle, Callaghan, NSW, 2308, Australia; Cooperative Research Centre for Contamination Assessment and Remediation of the Environment (CRC CARE), University of Newcastle, Callaghan, NSW, 2308, Australia.
Global Centre for Environmental Remediation (GCER), University of Newcastle, Callaghan, NSW, 2308, Australia.
Anal Chim Acta. 2024 Feb 15;1290:342069. doi: 10.1016/j.aca.2023.342069. Epub 2023 Dec 4.
While the concept of microplastic (<5 mm) is well-established, emergence of nanoplastics (<1000 nm) as a new contaminant presents a recent and evolving challenge. The field of nanoplastic research remains in its early stages, and its progress is contingent upon the development of reliable and practical analytical methods, which are currently lacking. This review aims to address the intricacies of nanoplastic analysis by providing a comprehensive overview on the application of advanced imaging techniques, with a particular focus on Raman imaging, for nanoplastic identification and simultaneous visualisation towards quantification.
Although Raman imaging via hyper spectrum is a potentially powerful tool to analyse nanoplastics, several challenges should be overcome. The first challenge lies in the weak Raman signal of nanoplastics. To address this, effective sample preparation and signal enhancement techniques can be implemented, such as by analysing the hyper spectrum that contains hundred-to-thousand spectra, rather than a single spectrum. Second challenge is the complexity of Raman hyperspectral matrix with dataset size at megabyte (MB) or even bigger, which can be adopted using different algorithms ranging from image merging to multivariate analysis of chemometrics. Third challenge is the laser size that hinders the visualisation of small nanoplastics due to the laser diffraction (λ/2NA, ∼300 nm), which can be solved with involving the use of super-resolution. Signal processing, such as colour off-setting, Gaussian fitting (via deconvolution), and re-focus or image re-construction, are reviewed herein, which show a great promise for breaking through the diffraction limit.
Overall, current studies along with further validation are imperative to refine these approaches and enhance the reliability, not only for nanoplastics research but also for broader investigations in the realm of nanomaterials.
虽然微塑料（<5毫米）的概念已得到充分确立，但纳米塑料（<1000纳米）作为一种新的污染物的出现带来了新的且不断演变的挑战。纳米塑料研究领域仍处于早期阶段，其进展取决于可靠且实用的分析方法的开发，而目前这类方法尚缺。本综述旨在通过全面概述先进成像技术的应用，特别是拉曼成像，来解决纳米塑料分析的复杂性问题，重点关注纳米塑料的识别以及用于定量的同步可视化。
尽管通过高光谱进行拉曼成像可能是分析纳米塑料的有力工具，但仍需克服若干挑战。第一个挑战在于纳米塑料的拉曼信号较弱。为解决这一问题，可以采用有效的样品制备和信号增强技术，例如分析包含数百至数千个光谱的高光谱，而非单个光谱。第二个挑战是拉曼高光谱矩阵的复杂性，其数据集大小可达兆字节（MB）甚至更大，可使用从图像合并到化学计量学多变量分析等不同算法来处理。第三个挑战是激光尺寸，由于激光衍射（λ/2NA，约300纳米），它会阻碍小纳米塑料的可视化，这可以通过使用超分辨率来解决。本文还综述了信号处理方法，如颜色偏移、高斯拟合（通过去卷积）以及重新聚焦或图像重建，这些方法在突破衍射极限方面显示出巨大潜力。
总体而言，当前的研究以及进一步的验证对于完善这些方法并提高可靠性至关重要，这不仅对于纳米塑料研究，而且对于纳米材料领域更广泛的研究都是如此。
