Adsorption Kinetics of Congo Red Dye Using Acid Modified Umuahia Clay: Modeling and Optimization Analysis

Congo red dye (CR) effluent is a toxic waste of environmental concern due to its artificial origin and complex molecular structure, which make it non-biodegradable. This research focused on using the physical method to remove CR pollutants (color, dissolved salt (EC), total dissolved solids (TDS), and chemical oxygen demand (COD)) from aqueous solutions by investigating the adsorptive qualities of acid-modified Umuahia clay (AUC). The batch system was applied to evaluate the effect of process-independent variables on the adsorption process. The mechanism of adsorption was investigated using intra-particle diffusion, liquid film, and the Boyd model. The thermodynamic properties ∆S, ∆H, ∆G, and Ea were determined. The optimum removal efficiency of CR was predicted using the artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), and response surface methodology (RSM) models. The activation resulted in an increase in surface area. Maximum color removal of 99.99% was observed at pH 2, adsorbent dosage of 0.5 g, adsorbent particle size of 50 µm, initial dye concentration of 100 mg/l, contact time of 130 min, and a temperature of 333 K. A maximum adsorption capacity of 140.53 mg/g was obtained. The adsorption mechanism was influenced by multiple steps. Thermodynamic results suggested an endothermic, favorable, spontaneous, and physical adsorption process. The ANFIS model, with an R2 of 0.9999, is statistically more significant than the ANN and RSM models. A maximum reusability capacity of 97.2% was achieved after three cycles. The obtained results confirm AUC as a reliable, cost-effective alternative adsorbent for CR removal from effluents.