Artificial neural network modeling of dye adsorption kinetics and thermodynamics with magnetic nanoparticle-activated carbon from Allium cepa peels

Abstract

Industrial wastewater contamination with poisonous dyes such as Methylene Blue (MB) and Congo Red (CR) causes significant environmental and health risks. Classical removal methods are frequently expensive to execute inadequate, and yield additional waste. The current research proposes a sustainable solution based on onion peel-derived activated carbon infused with magnetic nanoparticles (OMNPs), which provides great adsorption efficiency while repurposing agricultural waste. SEM analysis highlights the surface morphology, whereas XRD confirms the material's amorphous characteristics. OMNPs with a pore size of 2.193 nm have clearance rates of 96.25% for MB and 93.11% for CR dyes under optimal conditions. The Freundlich isotherm model best describes the multilayer adsorption mechanism, with high correlation coefficients (R² = 0.9945 for MB and 0.9878 for CR), while pseudo-second-order kinetics confirm chemisorption as the dominant mechanism. With overall R values of 0.993 and 0.984 obtained from experimental results, novel insights from artificial neural network (ANN) simulations proved to be reliable in predicting adsorption behavior. This innovative composite material delivers high removal rates and offers a scalable and reusability of OMNPs for wastewater treatment, showcasing its potential for industrial implementation.

Graphical Abstract