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Ensemble meta machine learning for predicting the adsorption of anionic and cationic dyes from aqueous solutions using Polymer/graphene/clay/MgFeAl-LTH nanocomposite.
BinMakhashen, Galal M; Bahadi, Salem A; Al-Jamimi, Hamdi A; Onaizi, Sagheer A.
Afiliação
  • BinMakhashen GM; Computer Science and Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31216, Saudi Arabia; Research Excellence, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia.
  • Bahadi SA; Department of Chemical Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31216, Saudi Arabia.
  • Al-Jamimi HA; Computer Science and Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31216, Saudi Arabia; Research Excellence, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia.
  • Onaizi SA; Department of Chemical Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31216, Saudi Arabia; Interdisciplinary Research Center for Hydrogen and Energy Storage, King Fahd University of Petroleum and Minerals, Dhahran 31216, Saudi Arabia. Electronic address: onaizi@kfupm.edu.sa.
Chemosphere ; 349: 140861, 2024 Feb.
Article em En | MEDLINE | ID: mdl-38056713
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Poluentes Químicos da Água / Nanocompostos / Grafite Idioma: En Revista: Chemosphere Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Arábia Saudita
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Poluentes Químicos da Água / Nanocompostos / Grafite Idioma: En Revista: Chemosphere Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Arábia Saudita