4.7 Article

Raman imaging for the identification of Teflon microplastics and nanoplastics released from non-stick cookware

期刊

SCIENCE OF THE TOTAL ENVIRONMENT
卷 851, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.scitotenv.2022.158293

关键词

Raman spectroscopy; Spectrum matrix; Polytetrafluoroethylene; Principal component analysis; Signal-to-noise ratio; Background

资金

  1. CRC CARE
  2. University of Newcastle Australia
  3. South Australian node of Microscopy Australia (formerly known as AMMRF) at Flinders University, South Australia

向作者/读者索取更多资源

This study employs Raman imaging to scan the surfaces of non-stick pots and develop algorithms for the extraction and merging of Teflon microplastics and nanoplastics images. With the help of SEM, it is estimated that a large number of Teflon microplastics and nanoplastics may be released during cooking processes. Therefore, it is recommended to combine Raman imaging with signal recognition algorithms and SEM for the characterisation and quantification of microplastics and nanoplastics.
The characterisation of microplastics is still difficult, and the challenge is even greater for nanoplastics. A possible source of these particles is the scratched surface of a non-stick cooking pot that is mainly coated with Teflon. Herein we employ Raman imaging to scan the surfaces of different non-stick pots and collect spectra as spectrum matrices, akin to a hyperspectral imaging process. We adjust and optimise different algorithms and create a new hybrid algorithm to extract the extremely weak signal of Teflon microplastics and particularly nanoplastics. We use multiple characteristic peaks of Teflon to create several images, and merge them to one, using a logic-based algorithm (i), in order to cross-check them and to increase the signal-noise ratio. To differentiate the varied peak heights towards image merging, an algebra-based algorithm (ii) is developed to process different images with weighting factors. To map the images via the whole set of the spectrum (not just from the individual characteristic peaks), a principal component analysis (PCA)-based algorithm (iii) is employed to orthogonally decode the spectrum matrix to the PCA spectrum and PCA intensity image. To effectively extract the Teflon spectrum information, a new hybrid algorithm is developed to justify the PCA spectra and merge the PCA intensity images with the algebra-based algorithm (PCA/algebra-based algorithm) (iv). Based on these developments and with the help of SEM, we estimate that thousands to millions of Teflon microplastics and nanoplastics might be released during a mimic cooking process. Overall, it is recommended that Raman imaging, along with the signal recognition algorithms, be combined with SEM to characterise and quantify microplastics and nanoplastics.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据