Abstract：
Microplastics have emerged as a global concern due to the increased plastic contamination found in a variety of sources. Herein we unveil microplastics released from plastic zippers that can generally be found in our clothes and textiles. We first employ a scanning electron microscope (SEM) to visualise the scratches developed on the zipper teeth and the derived particles. We then use Raman imaging to identify and simultaneously visualise the plastics from the chemical or molecular spectrum window. Based on hundreds to thousands of spectra, rather than a single spectrum or even a single peak that works as just a pixel in the image, imaging analysis can significantly increase the signal-to-noise ratio. Furthermore, the non-uniform distribution of components or multi-components can also be effectively imaged to avoid the possible bias from the single-spectrum analysis. The challenge to convert the hundreds to thousands of spectra of a hyperspectral matrix to an image is also discussed, and chemometrics is adopted and recommended to further improve the signal-to-noise ratio. The co-ingredient of titanium oxide in the zipper teeth/sewing lines is also effectively identified by Raman imaging. Based on the effective characterisation, we estimate that up to ~410 microplastics could be potentially released during each time of on-off zipping, although the variation can be expected and depends on several other factors. This study reminds us to be aware of the potential contamination derived from similar types of microplastic sources in our daily lives.
摘要：
由于各种来源中发现的塑料污染增加，微塑料已成为全球关注的问题。在这里，我们揭示了从塑料拉链中释放的微塑料，这些塑料通常可以在我们的衣服和纺织品中找到。我们首先使用扫描电子显微镜（SEM）来观察拉链齿和衍生颗粒上形成的划痕。然后，我们使用拉曼成像从化学或分子光谱窗口识别并同时可视化塑料。基于数百到数千个光谱，而不是像图像中的一个像素一样工作的单个光谱甚至单个峰值，成像分析可以显着提高信噪比。此外，非均匀分布的成分或多成分也可以有效地成像，以避免可能的偏差从单频谱分析。还讨论了将高光谱矩阵的数百到数千个光谱转换为图像的挑战，并建议采用化学计量学方法进一步提高信噪比。还通过拉曼成像有效地鉴定拉链齿/缝纫线中的氧化钛的共成分。基于有效的表征，我们估计，在每次开-关拉链的过程中，可能会释放多达410种微塑料，尽管变化是可以预期的，并且取决于其他几个因素。这项研究提醒我们注意日常生活中类似类型的微塑料来源产生的潜在污染。
