傅里叶变换红外光谱
微塑料
傅里叶变换
稳健性(进化)
化学成像
光谱学
红外线的
滤波器(信号处理)
环境科学
计算机科学
分析化学(期刊)
鉴定(生物学)
生物系统
材料科学
化学
环境化学
人工智能
光学
物理
高光谱成像
计算机视觉
生物
基因
生物化学
植物
量子力学
作者
Yiyang Chen,Dishi Wen,Jianchuan Pei,Yufan Fei,Da Ouyang,Haibo Zhang,Yongming Luo
标识
DOI:10.1016/j.coesh.2020.05.004
摘要
Fourier-transform infrared (FTIR) spectroscopy is the most popular approach currently using for identification and quantification of microplastics (MPs). Recent advancements in micro-FTIR (μ-FTIR) imaging have enabled automatic identification of MPs concentrated on the filter membrane without presorting. Focal plane array–based μ-FTIR imaging provided a considerable reduction in analysis time and increased the accuracy of the results by impartial measurement of the whole filter surfaces. The algorithmic development of automated spectra evaluation incorporated of multivariate statistics and machine learning dramatically increase the efficiency and robustness of the identification and quantification for MPs. This makes it possible to fast automatic analysis of MPs from environmental compartments based on massive FTIR spectra. Research priorities were proposed regarding FTIR spectroscopy application in microplastics/nanoplastics, which include the formation of standardized protocol for routine analysis of MPs automatically, exploration of more chemical information in combination with other advanced techniques, and characterization of environmental nanoplastics using hybrid atomic force microscopy infraredspectroscopy.
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