Isfahan University of Medical Sciences

Science Communicator Platform

Stay connected! Follow us on X network (Twitter):
Share this content! On (X network) By
Atenolol Adsorption Onto Multi-Walled Carbon Nanotubes Modified by Naocl and Ultrasonic Treatment; Kinetic, Isotherm, Thermodynamic, and Artificial Neural Network Modeling Publisher



Dehdashti B1, 2 ; Amin MM2, 3 ; Gholizadeh A4 ; Miri M5 ; Rafati L6
Authors
Show Affiliations
Authors Affiliations
  1. 1. Stud. Research Committee, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
  2. 2. Department of Environmental Health Engineering, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
  3. 3. Environment Research Center, Research Institute for Primordial Prevention of Non-communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran
  4. 4. Esfarayen Faculty of Medical Sciences, Esfarayen, Iran
  5. 5. Department of Environmental Health, School of Public Health, Sabzevar University of Medical Sciences, Sabzevar, Iran
  6. 6. Deputy of Health, Hamadan University of Medical Sciences, Hamadan, Iran

Source: Journal of Environmental Health Science and Engineering Published:2019


Abstract

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. © 2019 Springer Nature Switzerland AG.
Other Related Docs
9. Ethylbenzene Removal by Carbon Nanotubes From Aqueous Solution, Journal of Environmental and Public Health (2012)
10. Benzene and Toluene Removal by Carbon Nanotubes Fromaqueous Solution, Archives of Environmental Protection (2012)
40. Decolorization of Synthetic Wastewaters by Nickel Oxide Nanoparticle, International Journal of Environmental Health Engineering (2012)
46. Survey on the Efficiency of Ultrasonic Waves in Phenol Removal From Synthetic Wastewater, Journal of Knowledge and Health in Basic Medical Sciences (2019)