Synthesis, optimization, and superior efficacy of copper-modified quantum dots for phenol removal

This study evaluates the performance of copper-modified quantum dots (Cu-QDots) as efficient adsorbents for removing phenol from aqueous solutions. Two Cu‑QDot samples containing 10 wt% and 20 wt% copper was synthesized and fully characterized using FTIR, SEM, EDX, and XRD analyses. A design of experiments (DOE) combined with response surface methodology (RSM) was employed to identify the influence of operational parameters and optimize the adsorption process. Increasing adsorbent dosage enhanced phenol removal by providing additional active sites, although the improvement gradually reached a plateau at higher dosages. RSM optimization indicated ideal conditions of 0.168 g of 10% Cu-Qdots, an 18.75 min contact time, and a pH of 9, under which a maximum removal efficiency of 99.98% was experimentally achieved. Adsorption kinetics were examined using pseudo‑first‑order and pseudo‑second‑order models, while equilibrium data were fitted to Langmuir and the Freundlich isotherms. Thermodynamic evaluations further clarified the nature of the adsorption process. Machine learning models were also applied, with ANFIS showing excellent predictive ability (R2 = 0.996). Overall, the results highlight the high adsorption efficiency of Cu‑modified quantum dots, with the 10% Cu‑QDot sample exhibiting superior performance and strong potential for advanced wastewater treatment applications.