• 文献标题:   Molecular dynamic simulation and artificial neural network (ANN) modeling of the functionalized graphene oxide membranes on Cr (VI) ion removal through electrodialysis method
  • 文献类型:   Article
  • 作  者:   HASANZADEH A, ALIZADEH M, AJALLI N, AZAMAT J, JAHANSHAHI M
  • 作者关键词:   graphene oxide, functionalized pore, heavy metal, cr vi, ann
  • 出版物名称:   JOURNAL OF MOLECULAR LIQUIDS
  • ISSN:   0167-7322 EI 1873-3166
  • 通讯作者地址:  
  • 被引频次:   0
  • DOI:   10.1016/j.molliq.2023.122083 EA MAY 2023
  • 出版年:   2023

▎ 摘  要

In this study, the separation of chromium (VI) ion as a dangerous heavy metal material from water by graphene oxide (GO) membrane was investigated using molecular simulation method. Pores were created in the middle of GO membrane and then the membrane pores were functionalized by adding -F, -H, and -OH chemical groups. The external voltages were applied to the studied system to improve the efficiency of Cr (VI) and water separation process. To study the functionalized GO membrane performance under applied voltage in the separation process, analyzes were performed, which include permeation, artificial neural network (ANN), radial distribution function, hydrogen bond, ion tracking path, water density map and diffusion coefficient of ion. The outcomes demonstrate that the GO membrane can be constructed with an adequate functional porosity and a sufficient applied voltage, and that it performs well throughout the heavy metal separation procedure.