Muscovite clay for methylene blue removal: advanced optimization and Al-guided breakthroughs-an independent...

This study evaluates the efficacy of muscovite mineral clay as an adsorbent for removing Methylene Blue (MB) from water-based solutions. The research examined the impact of initial MB concentration, adsorbent mass, and time on the MB removal process. Two modeling techniques, namely Box-Behnken design with response surface methodology (BBD-RSM) and Artificial Neural Network (ANN), were employed to accurately predict the MB removal efficiency. The RSM and ANN models yielded satisfactory results in estimating MB removal efficiency. To further enhance the optimization process, conventional and techno-economic methods were implemented. The conventional method aimed to maximize dye removal efficiency (R), while the techno-economic approach incorporated multiple objectives. The comparative analysis demonstrated that the techno-economic optimization method outperformed the conventional method. This study emphasizes the significance of considering multiple objectives and integrating techno-economic factors in optimizing clay adsorption processes. The successful application of the techno-economic optimization approach highlights its potential as a robust optimization method, particularly in the field of wastewater treatment. The findings provide valuable insights for optimizing adsorption and advancing environmental remediation practices.