Modeling and optimization of methylene blue adsorption from aqueous media via natural clay: Response surface methodology, artificial neural network, and Monte Carlo molecular studies

This study examines the adsorption behavior of Methylene Blue (MB) dye onto natural Moroccan muscovite–kaolinite (Mu–K) clay to assess its potential as an eco-friendly and cost-effective adsorbent. The clay was characterized using XRF, FTIR, XRD, SEM–EDX, and pHpzc analyses, confirming muscovite, kaolinite, and quartz as the dominant mineral phases. Batch adsorption experiments were conducted to evaluate the effects of pH, contact time, temperature, and initial dye concentration on adsorption efficiency. Kinetic modeling indicated that the pseudo-second-order model best described the adsorption mechanism, while the Langmuir isotherm provided the best equilibrium fit, suggesting monolayer adsorption with a maximum capacity of 70.93 mg g⁻¹ at 25 °C. Thermodynamic analysis revealed that the process was spontaneous and endothermic. To optimize and predict adsorption performance, response surface methodology (RSM) and artificial neural network (ANN) models were applied, both demonstrating strong agreement with experimental results. Monte Carlo simulations further elucidated the adsorption mechanism, identifying hydrogen bonding and electrostatic interactions as key driving forces. These findings confirm Mu–K clay as an efficient natural material for dye removal and environmental remediation