• 文献标题:   Comparative assessment on defluoridation of waste water using chemical and bio-reduced graphene oxide: Batch, thermodynamic, kinetics and optimization using response surface methodology and artificial neural network
  • 文献类型:   Article
  • 作  者:   ROY S, MANNA S, SENGUPTA S, GANGULI A, GOSWAMI S, DAS P
  • 作者关键词:   fluoride, bioreduced graphene oxide, response surface methodology, regeneration study, artificial neural network, tea solution
  • 出版物名称:   PROCESS SAFETY ENVIRONMENTAL PROTECTION
  • ISSN:   0957-5820 EI 1744-3598
  • 通讯作者地址:   Jadavpur Univ
  • 被引频次:   7
  • DOI:   10.1016/j.psep.2017.07.010
  • 出版年:   2017

▎ 摘  要

In this study, reduced graphene oxide was synthesized from tea solution (TPGO) and by hydrazine hydrate and was used for the treatment of fluoride containing waste water. The batch study indicated that bio-reduced graphene oxide (TPGO) showed fluoride removal capacity of 94.22% whereas in case of chemically reduced graphene oxide, the removal was 87.4% at optimized condition. In both cases, the equilibrium data were fitted well with Langmuir adsorption isotherm and the adsorption kinetic data followed the pseudo second order model. The performance of TPGO was further optimized with response surface methodology and artificial neural network (ANN) analysis. The two-level, three-factorial (23) Central Composite Design (CCD) expert software was employed to find the optimum combination of process parameters for maximum fluoride adsorption capacity of TPGO. The exhausted TPGO was also regenerated using 1% sodium hydroxide solution and reused for the removal of fluoride present in solution. (C) 2017 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.