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

(2019) Atenolol adsorption onto multi-walled carbon nanotubes modified by NaOCl and ultrasonic treatment; kinetic, isotherm, thermodynamic, and artificial neural network modeling. Journal of Environmental Health Science and Engineering. pp. 281-293. ISSN 2052-336X

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Official URL: WOS:000472066600026

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 -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) ((q(e,exp)=46.03mgg(-1))) occurred on the adsorbent activated within 10s 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 90min under the optimized pH of 6. According to ANN modeling, approximately the whole values dispersed around the 45 degrees 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.

Item Type: Article
Keywords: Atenolol Wastewater Multi-walled carbon nanotube Artificial neural network nh4cl-induced activated carbon beta-blockers waste-water aqueous-solutions methylene-blue removal pharmaceuticals equilibrium degradation oxidation Engineering Environmental Sciences & Ecology
Subjects: WA Public Health > WA 670-847 Environmental Pollution. Sanitation
Divisions: Faculty of Health > Department of Environmental Health Engineering
Faculty of Health > Student Research Committee
Research Institute for Primordial Prevention of Non-communicable Disease > Environment Research Center
Page Range: pp. 281-293
Journal or Publication Title: Journal of Environmental Health Science and Engineering
Journal Index: ISI
Volume: 17
Number: 1
Identification Number: https://doi.org/10.1007/s40201-019-00347-0
ISSN: 2052-336X
Depositing User: Zahra Otroj
URI: http://eprints.mui.ac.ir/id/eprint/10973

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