Remediation of anionic dye from aqueous solution through adsorption on polyaniline/FO nanocomposite-modelling by artificial neural network (ANN)

The present study emphasized on performance of Polyaniline (PANI)/magnetic oxide (FO) nanocomposite for remediation of methyl orange (MO) from aqueous solution through adsorption. The influence of various adsorption parameters were studied and were also optimized by artificial neural network model (ANN). The synthesized nanocomposite were characterized by FTIR, XRD, SEM/TEM, EDX, BET, and VSM analysis. Remarkably, the nanocomposite shows excellent performance for removal of anionic dye with monolayer adsorption capacity of 361.78 mg/g and maintain more than70% of removal efficiency till 7th cycle of adsorption and desorption, indicating good adsorption capability and reusability. The adsorption kinetics follows pseudo-second order and intra particle diffusion model, while adsorption isotherm follows Langmuir model. Further, FTIR analysis and effect of parameters indicates that pi-pi interaction and electrostatic attraction are primary mechanism in MO adsorption. Moreover, ANN model with structure of 5-9-1 was able to predict good results and proved that ANN model could predict the behaviour of adsorption of MO on PANI/FO nanocomposite. (C) 2022 Elsevier B.V. All rights reserved.

Automated summary

The present study focused on the performance of a Polyaniline (PANI)/magnetic oxide (FO) nanocomposite for removing methyl orange (MO) from aqueous solutions through adsorption. Various adsorption parameters were studied and optimized using an artificial neural network model (ANN). The synthesized nanocomposite was characterized using various techniques and showed excellent adsorption capability and reusability.