Abstract
Biological sources are renewable fundamental resources that may be utilised for various reasons, including developing green materials to remove heavy metal ions. In this study, cellulose nanocrystals (CNCs) obtained by acid hydrolysis of waste papers were modified with Ethylenediaminetetraacetic acid to increase their adsorption capacity. The BBD and ANN were used to optimise the removal process. The FTIR analysis confirmed successful CNC modification, with the key peaks observed at 1705 cm-1 to confirm C=O stretching and at 1551 cm-1 to confirm carboxylate stretching. This indicates the successful incorporation of EDTA functional groups that improve copper binding. The research also examined how other variables affected the adsorption process, including pH, initial concentration, and adsorbent dose. The process was optimised using the Box-Behnken Design, and the optimal parameters for the highest possible removal efficiency of Cu (II) were determined. The ideal parameters were ideal for an initial pH of 5.5, a contact time of 118 min, an initial concentration of 125 mg/L, and a sorbent dose of 5.5 g/200 mL. The results demonstrate the potential of the developed CNCs using BBD and ANN approach for removing Cu (II) from wastewater. The ANN models' outputs were evaluated against the real data using the R² and MSE. The ideal artificial neural network (ANN) model produced both accurate and dependable findings, with R² values of 0.997 and error of
