• 文献标题:   Optimization and modelling of synthetic azo dye wastewater treatment using Graphene oxide nanoplatelets: Characterization toxicity evaluation and optimization using Artificial Neural Network
  • 文献类型:   Article
  • 作  者:   BANERJEE P, SAU S, DAS P, MUKHOPADHAYAY A
  • 作者关键词:   graphene oxide, nanoplatelet, artificial neural network, toxicity, oxidative stres, adsorption
  • 出版物名称:   ECOTOXICOLOGY ENVIRONMENTAL SAFETY
  • ISSN:   0147-6513 EI 1090-2414
  • 通讯作者地址:   Jadavpur Univ
  • 被引频次:   37
  • DOI:   10.1016/j.ecoenv.2015.04.022
  • 出版年:   2015

▎ 摘  要

Azo dyes pose a major threat to current civilization by appearing in almost all streams of wastewater. The present investigation was carried out to examine the potential of Graphene oxide (GO) nanoplatelets as an efficient, cost-effective and non-toxic azo dye adsorbent for efficient wastewater treatment. The treatment process was optimized using Artificial Neural Network for maximum percentage dye removal and evaluated in terms of varying operational parameters, process kinetics and thermodynamics. A brief toxicity assay was also designed using fresh water snail Bellamya benghalensis to analyze the quality of the treated solution. 97.78% removal of safranin dye was obtained using GO as adsorbent. Characterization of GO nanoplatelets (using SEM, TEM, AFM and FTIR) reported the changes in its structure as well as surface morphology before and after use and explained its prospective as a good and environmentally benign adsorbent in very low quantities. The data recorded when subjected to different isotherms best fitted the Temkin isotherm. Further analysis revealed the process to be endothermic and chemisorption in nature. The verdict of the toxicity assay rendered the treated permeate as biologically safe for discharge or reuse in industrial and domestic purposes. (C) 2015 Elsevier Inc. All rights reserved.