Atenolol adsorption onto multi-walled carbon nanotubes modified by NaOCl and ultrasonic treatment; kinetic, isotherm, thermodynamic, and artificial neural network modeling.

The removal of pharmaceutical pollutants from the aqueous environment is a great environmental concern, mainly due to their diversity, high consumption, and sustainability. In the current study, we aimed to investigate the ability of multi-walled carbon nanotubes (MWCNTs) modified by sodium hypochlorite (NaOCl) and ultrasonic treatment in refining wastewaters contaminated with Atenolol β-blocker drug (ATN). The physical and structural characteristics of the raw MWCNTs and modified MWCNTs (M-MWCNTs) were analyzed using SEM, TEM, Raman spectroscopy, TGA, and FT-IR techniques. The effects of different parameters, including pH, initial concentration, contact time, and temperature were studied and optimized. Subsequently, the adsorption data were analyzed by several kinetic and equilibrium isotherm equations and modeled by artificial neural network (ANN). Highest ATN removal (87.89%) ((qe,exp = 46.03 mg g-1)) occurred on the adsorbent activated within 10 s of ultrasonication time and NaOCl 30%. Moreover, adsorbent modification significantly improved the ATN removal, so that the removal rate on the raw MWCNTs was about 58%, but in the same conditions, M-MWCNTs removed more than 92% of the adsorbate. The adsorption process reached equilibrium after 90 min under the optimized pH of 6. According to ANN modeling, approximately the whole values dispersed around the 45°line, indicating a good compatibility between the trial results and ANN-predicted data. The modification of MWCNTs in proper ultrasonic power via appropriate concentration of NaOCl solution removed many of the impurities and significantly improved the adsorption performance of MWCNTs.