Identification of Water-Soluble Polymers through Machine Learning of Fluorescence Signals from Multiple Peptide Sensors

利用机器学习技术分析多个肽传感器的荧光信号来识别水溶性聚合物

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Abstract

Recently, there has been growing concern about the discharge of water-soluble polymers (especially synthetic polymers) into the environment. Therefore, the identification of water-soluble polymers in water samples is becoming increasingly crucial. In this study, a chemical tongue system to simply and precisely identify water-soluble polymers using multiple fluorescently responsive peptide sensors was demonstrated. Fluorescence spectra obtained from the mixture of each peptide sensor and water-soluble polymer were changed depending on the combination of the polymer species and peptide sensors. Water-soluble polymers were successfully identified through the supervised or unsupervised machine learning of multidimensional fluorescence signals from the peptide sensors.

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