Exploring the Knowledge Attained by Machine Learning on Ion Transport across Polyamide Membranes Using Explainable Artificial Intelligence.

Jeong, Nohyeong; Epsztein, Razi; Wang, Ruoyu; Park, Shinyun; Lin, Shihong; Tong, Tiezheng

Jeong, Nohyeong; Epsztein, Razi; Wang, Ruoyu; Park, Shinyun; Lin, Shihong; Tong, Tiezheng.

Afiliación

Jeong N; Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, Colorado 80523, United States.
Epsztein R; Department of Civil and Environmental Engineering, Technion - Israel Institute of Technology, Haifa 32000, Israel.
Wang R; Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, Tennessee 37235-1831, United States.
Park S; Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, Colorado 80523, United States.
Lin S; Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, Tennessee 37235-1831, United States.
Tong T; Department of Chemical and Bimolecular Engineering, Vanderbilt University, Nashville, Tennessee 37235-1831, United States.

Environ Sci Technol ; 57(46): 17851-17862, 2023 Nov 21.

Article en En | MEDLINE | ID: mdl-36917705

Asunto(s)

Nylons; Purificación del Agua; Ósmosis; Inteligencia Artificial; Membranas Artificiales; Purificación del Agua/métodos; Aprendizaje Automático; Filtración/métodos; Transporte Iónico

Palabras clave

explainable artificial intelligence; ion transport; machine learning; membrane separation mechanisms; nanofiltration; reverse osmosis

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Purificación del Agua / Nylons Tipo de estudio: Prognostic_studies Idioma: En Revista: Environ Sci Technol Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

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