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Strategies and Challenges of Identifying Nanoplastics in Environment by Surface-Enhanced Raman Spectroscopy

Environmental Science & Technology 2022 170 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
Lifang Xie, Kedong Gong, Yangyang Liu, Liwu Zhang

Summary

Researchers reviewed the use of surface-enhanced Raman spectroscopy (SERS) as a tool for detecting nanoplastics, which are plastic particles smaller than one micrometer. The study found that SERS offers high sensitivity for identifying individual nanoparticles, but significant challenges remain in applying this technique to complex environmental samples. The review outlines strategies for improving SERS-based nanoplastic detection to better assess environmental and health risks.

Nanoplastics (<1000 nm) have been evidenced to be universal in a variety of environmental media. They pose a potential cytotoxicity and health risk due to their tiny size, which allows them to easily penetrate biological barriers and enter cells. Here, we briefly review the various prevalent analytical techniques or tools for identifying nanoplastics, and further move to focus on their advantages and disadvantages. Surface-enhanced Raman spectroscopy (SERS) has been implemented for the identification of individual nanoparticles because of its high sensitivity to molecules and ease of rapid characterization. Therefore, we introduce the SERS technique in the following aspects, (1) principles of SERS; (2) strategies and advances in SERS detection of nanoplastics; and (3) applying SERS to real environmental samples. We put our effort into the summarization of efficient SERS substrates that essentially enable the better detection of nanoplastics, and extend to discuss how the reported nanoplastics pretreatment methodologies can bring SERS analysis to practical applications. A further step moving forward is to investigate the problems and challenges of currently applied SERS detection methods and to look at future research needs in nanoplastics detection employing SERS analysis.

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