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Detection of microplastics based on spatial heterodyne Raman spectroscopy

Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy 2022 23 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 40 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Qingsheng Xue, Nan Wang, Hui Ying Yang, Jingyao Yang, Haoxuan Bai

Summary

Researchers developed a spatial heterodyne Raman spectroscopy method for detecting microplastics, offering advantages over existing techniques by reducing detection time, lowering false detection rates, and using more affordable equipment.

As a new type of pollutant, microplastics have attracted extensive attention due to its characteristics such as small size and degradation difficulty under natural circumstance. Though there are many detection methods nowadays, there are still some limitations like long detection time, high false detection rate and expensive detection equipment, which make the detection of microplastics exists in natural environment hard to carry out. To improve the environmental conditions, rapid, efficient, and accurate detection methods for microplastics are needed urgently. In this paper, a method combined the Spatial heterodyne technology and Raman spectroscopy was proposed to detect the microplastics. A spatial heterodyne spectrometer (SHS) was built, and the algorithms used to process the spectrum data were introduced. An optical system used to collect the Raman signal of the sample was built and connected with the SHS. Four different kinds of microplastic samples were detected by the complete system and identification can be achieved according to the Raman spectrum. The samples were also detected by using a normal spectrometer for comparison. A comparison of Raman spectrum using conventional dispersion spectrometer was carried out and the result shows that SHS is of higher signal-to-noise ratio. The results indicate that SHRS technology has good performance and development prospects in the field of microplastics detection.

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