Modeling of Cu(II) adsorption from an aqueous solution using an Artificial Neural Network (ANN)

• Main Authors: Khan, T., Manan, T.S.B., Isa, M.H., Ghanim, A.A.J., Beddu, S., Jusoh, H., Iqbal, M.S., Ayele, G.T., Jami, M.S.
• Format: Article
• Published: MDPI AG 2020
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088679425&doi=10.3390%2fmolecules25143263&partnerID=40&md5=c2fea54fb167ec8dec531894b22f8991; http://eprints.utp.edu.my/32398/

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...