Predicting adsorption capacity of pharmaceuticals and personal care products on long-term aged microplastics using machine learning.

Yao, Jingjing; Li, Haipu; Yang, Hui Ying

Yao, Jingjing; Li, Haipu; Yang, Hui Ying.

Afiliación

Yao J; Center for Environment and Water Resources, College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, PR China; Key Laboratory of Hunan Province for Water Environment and Agriculture Product Safety, Changsha 410083, PR China; Pillar of Engineering Product Development, Singapore University of Technology and Design, 8 Somapah Road, 487372, Singapore. Electronic address: yaojj0412@163.com.
Li H; Center for Environment and Water Resources, College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, PR China; Key Laboratory of Hunan Province for Water Environment and Agriculture Product Safety, Changsha 410083, PR China. Electronic address: lihaipu@csu.edu.cn.
Yang HY; Pillar of Engineering Product Development, Singapore University of Technology and Design, 8 Somapah Road, 487372, Singapore. Electronic address: yanghuiying@sutd.edu.sg.

J Hazard Mater ; 458: 131963, 2023 09 15.

Article en En | MEDLINE | ID: mdl-37406525

Asunto(s)

Cosméticos; Contaminantes Químicos del Agua; Microplásticos; Plásticos; Adsorción; Contaminantes Químicos del Agua/química; Aprendizaje Automático; Preparaciones Farmacéuticas

Palabras clave

Adsorption capacity; Fourier transform infrared spectroscopy; Long-term aged Microplastics; Machine learning; Pharmaceuticals and personal care products

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Contaminantes Químicos del Agua / Cosméticos Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Hazard Mater Asunto de la revista: SAUDE AMBIENTAL Año: 2023 Tipo del documento: Article Pais de publicación: Países Bajos

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