Modeling of Cu(II) Adsorption from an Aqueous Solution Using an Artificial Neural Network (ANN)

This research optimized the adsorption performance of rice husk char (RHC4) for copper (Cu(II)) from an aqueous solution. Various physicochemical analyses such as Fourier transform infrared spectroscopy (FTIR), field-emission scanning electron microscopy (FESEM), carbon, hydrogen, nitrogen, and sulf...

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Detalles Bibliográficos
Autores principales: Khan, Taimur, Binti Abd Manan, Teh Sabariah, Isa, Mohamed Hasnain, Ghanim, Abdulnoor A.J., Beddu, Salmia, Jusoh, Hisyam, Iqbal, Muhammad Shahid, Ayele, Gebiaw T, Jami, Mohammed Saedi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7397182/
https://www.ncbi.nlm.nih.gov/pubmed/32708928
http://dx.doi.org/10.3390/molecules25143263

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7397182/
https://www.ncbi.nlm.nih.gov/pubmed/32708928
http://dx.doi.org/10.3390/molecules25143263

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