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

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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Bibliographic Details
Main Authors: Taimur Khan, Teh Sabariah Binti Abd Manan, Mohamed Hasnain Isa, Abdulnoor A.J. Ghanim, Salmia Beddu, Hisyam Jusoh, Muhammad Shahid Iqbal, Gebiaw T Ayele, Mohammed Saedi Jami
Format: Article
Language:English
Published: MDPI AG 2020-07-01
Series:Molecules
Subjects:
adsorption
artificial neural network
heavy metal removal
rice husk char
Online Access:https://www.mdpi.com/1420-3049/25/14/3263

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