Abstract
The sources of microplastics and nanoplastics can be found almost everywhere, including being released from the activities of our daily lives. Unfortunately, the process for determining the sources of microplastics and nanoplastics is hampered by the limited techniques available for characterisation. Herewith, we advance Raman imaging by combining it with logic-based, algebra-based, PCA-based algorithms and their hybrid, which can significantly increase the signal-noise ratio and the imaging certainty, to enable the characterisation of microplastics. Consequently, we can capture and identify the microplastics carried by our smartphones. That is because, due to the friction and fragmentation etc., our clothes and the decoration trinkets that might be made of plastic fibres can release microplastics. The released microplastics stick on the phone surface, or are trapped in the charging port, speaker ports etc., towards accumulation. We estimate hundreds or thousands of microplastics can be captured and carried by a smartphone, depending on the clothing materials, pocketing styles, user habits etc. Due to the complexity of the samples (which shields the weak signals emitted from nanoplastics), further methodological improvements are required, such as optimisation of sample preparation (for better isolation of nano-sized plastics), refinement of data processing algorithms and combined use of Raman microscopy and scanning electron microscopy (SEM).
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