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Congo Tak Shing Ching,Pei-Yuan Lee,Nguyen Van Hieu,Hsin-Hung Chou,Fiona Yan-Dong Yao,Cheng Sha-Yen,Lin Yung-Kai,Thien Luan Phan 한국생물공학회 2023 Biotechnology and Bioprocess Engineering Vol.28 No.3
Microplastic, being a direct carrier of many pollutants, has caused grave concern and become a public issue. This gives rise to the need of a quick method for quantifying and identifying microplastics in the environment. This study uses impedance spectroscopy, particularly the imaginary part of impedance, for detection and identification of sample microplastics. Two type of common microplastic contaminants, Polyethylene and Polystyrene, diameter 20 m and 150 m, were chosen for this study. The results confirm accurate identification of microplastic material in question, by using self-normalized ratio between two characteristic frequencies of 7MHz and 8.9 MHz, Zf = 7 MHz / Zf = 8.9 MHz. 3-kNN classifier built with the ratio Zf = 7 MHz / Zf = 8.9 MHz, and Zf = 8 MHz /Zf = 8.9 MHz, demonstrates accuracy upto 90% for the identification of single or both microplastic types in samples. These results confirm impedance spectroscopy, permitting rapid identification of microplastic without labeling and skillful techniques, as a potential rapid sensor.