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KMID : 1094720230280030459
Biotechnology and Bioprocess Engineering
2023 Volume.28 No. 3 p.459 ~ p.466
Real-time, Economical Identification of Microplastics Using Impedance-based Interdigital Array Microelectrodes and k-Nearest Neighbor Model
Congo Tak Shing Ching

Pei-Yuan Lee
Nguyen Van Hieu
Hsin-Hung Chou
Fiona Yan-Dong Yao
Sha-Yen Cheng
Yung-Kai Lin
Thien Luan Phan
Abstract
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 ¥ìm and 150 ¥ìm, 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 7 MHz and 8.9 MHz, Z¡Çf=7 MHz/Z¡Çf=8.9 MHz. 3-kNN classifier built with the ratio Z¡Çf=7 MHz/Z¡Çf=8.9 MHz, and Z¡Çf=8 MHz/Z¡Çf=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.
KEYWORD
microplastics, impedance, micro interdigitated electrode
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