• 文献标题:   Predictive models for adsorption of organic compounds by Graphene nanosheets: comparison with carbon nanotubes
  • 文献类型:   Article
  • 作  者:   ERSAN G, APUL OG, KARANFIL T
  • 作者关键词:   lser, predictive modeling, graphene nanosheet, carbon nanotube, organic compound
  • 出版物名称:   SCIENCE OF THE TOTAL ENVIRONMENT
  • ISSN:   0048-9697 EI 1879-1026
  • 通讯作者地址:   Clemson Univ
  • 被引频次:   6
  • DOI:   10.1016/j.scitotenv.2018.11.029
  • 出版年:   2019

▎ 摘  要

The Linear Solvation Energy Relationships (LSER) technique was applied in the present study for predicting models of organic compounds (OCs) adsorption by Graphene and Graphene oxide (GO), and the results were compared with those of multi-walled carbon nanotube (MWCNT) and single-walled carbon nanotube (SWCNT). Adsorption database of 38 OCs (28 aromatic and 10 aliphatic) for Graphene and 69 OCs (59 aromatic and 10 aliphatic) for GO were collected from the literature and our laboratory. The r(2) of the LSER models on the adsorption of aromatic OCs by Graphene and GO at three different equilibrium concentrations gradually increased up to OC molecular weight of 400 g/mol, after which a declining trend was observed for GO, while there was no visible change for Graphene. Among descriptors for all LSER models, V (molecular volume) and B (hydrogen bond accepting) for Graphene nanosheets (GNS) and carbon nanotubes (CNT) were the most significant descriptors (p values