Application of neural network in metal adsorption using biomaterials (BMs): a review
Amrita Nighojkar, Karl Zimmermann, Mohamed Ateia, Benoît Barbeau, Madjid Mohseni, Satheesh Krishnamurthy, Fuhar Dixit, Balasubramanian Kandasubramanian
Abstract
adsorption. Although implementing the adsorption procedure using BMs seems simple, the conjugate effects of adsorbent properties and process attributes implicate complex nonlinear interactions. As a result, artificial neural networks (ANN) have gained traction in the quest to understand the complex metal adsorption processes on biomaterials, with applications in environmental remediation and water reuse. This review discusses recent progress using ANN frameworks for metal adsorption using modified biomaterials. Subsequently, the paper comprehensively evaluates the development of a hybrid-ANN system to estimate isothermal, kinetic and thermodynamic parameters in multicomponent adsorption systems.