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A practical approach based on FT-IR spectroscopy for identification of semi-synthetic and natural celluloses in microplastic investigation
The Science of The Total Environment2019
137 citations
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Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
Score: 40
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0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Researchers developed a practical FT-IR spectroscopy protocol to distinguish semi-synthetic celluloses such as rayon from natural celluloses in microplastic investigations, addressing a longstanding misidentification problem by characterizing spectral differences among eight semi-synthetic and four natural cellulose materials.
In previous studies of marine debris or microplastics (<5 mm), various types of semi-synthetic celluloses (e.g. rayon) are ubiquitous in some field investigations. However, it is hard to distinguish semi-synthetic and natural celluloses clearly even using the spectroscopic method. In this study, 8 semi-synthetic and 4 natural celluloses were employed as the test materials to simulate the environmentally relevant samples. Our results showed that these original commercial products exhibited obvious physical (e.g., color) and chemical (e.g., spectra) changes after UV weathering and agent (HO and KOH) digestion treatments. The changes of 4 characteristic bands (1735, 1425/1419, 1105, 1060-1053/1030-1027 cm) were evaluated. We found that the band at 1105 cm which is assigned to the CO antisymmetric in plane stretching band only existed in natural fibers even after the weathering and digestion treatments. The mixture of semi-synthetic and natural fibers from the real field samples was also easily distinguished using the characteristic band at 1105 cm. Our results suggest that the characteristic band at 1105 cm could be an ideal reference to distinguish natural and semi-synthetic fibers in field microplastic investigations. We also proposed a practical method to enhance the library of polymer spectra and improve the accuracy of semi-synthetic microplastic identification.