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Modeling and prediction of copper removal from aqueous solutions by nZVI/rGO magnetic nanocomposites using ANN-GA and ANN-PSO

Reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO) magnetic nanocomposites were prepared and then applied in the Cu(II) removal from aqueous solutions. Scanning electron microscopy, transmission electron microscopy, X-ray photoelectron spectroscopy and superconduction quantum int...

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Detalles Bibliográficos
Autores principales:	Fan, Mingyi, Hu, Jiwei, Cao, Rensheng, Xiong, Kangning, Wei, Xionghui
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Nature Publishing Group UK 2017
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5740166/ https://www.ncbi.nlm.nih.gov/pubmed/29269846 http://dx.doi.org/10.1038/s41598-017-18223-y

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Addendum: Shi, X.D.; Ruan, W.Q.; Hu, J.W.; Fan, M.Y.; Cao, R.S.; Wei, X.H. Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an Artificial Neural Network-Genetic Algorithm (ANN-GA). Nanomaterials 2017, 7, 134
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