• 文献标题:   Fenton-like degradation of carmine dyes based on artificial intelligence modeling and optimization of reduced graphene oxide loaded iron-cobalt-nickel trimetallic nanocomposites
  • 文献类型:   Article
  • 作  者:   XIN L, HU JW, WU XL, HUANG KW, HUANG XF
  • 作者关键词:   fentonlike, degradation, trimetallic nanocomposite, artificial intelligence, regeneration
  • 出版物名称:   MATERIALS TODAY COMMUNICATIONS
  • ISSN:  
  • 通讯作者地址:  
  • 被引频次:   2
  • DOI:   10.1016/j.mtcomm.2022.103463 EA APR 2022
  • 出版年:   2022

▎ 摘  要

In this experiment, reduced graphene oxide loaded iron-cobalt-nickel trimetallic nano compounds were prepared by co-precipitation method and coadministered with oxidant hydrogen peroxide to form Fenton-like reagents. The degradation of carmine dye simulated industrial wastewater by this type of fenton catalyst in combination with ultrasound was investigated and it can be identified that ultrasound is synergistic when combined with this type of fenton process. In this experiment, the synthesized nanocomposites were characterized by X-ray diffraction, scanning electron microscopy, energy dispersive spectroscopy, fourier transform infrared spectroscopy, raman spectroscopy, N-2 adsorption, and superconducting quantum interferometry, and the results demonstrated that the materials have a typical graphite porous structure and excellent magnetic properties. The influences of four factors (V(H2O2), reaction time, initial concentration and catalyst dosage) on the degradation of carmine dye were further analyzed. The experiment was then modeled and optimized with response surfaces and artificial intelligence. Through the comparative analysis of the experimental value and the predicted value, it is found that the absolute error of the artificial neural network-particle swarm optimization model is the smallest, which indicates that the model makes a better prediction of the experimental results. The importance of influencing factors in the dye removal process was ranked according to F-test, random forest and Garson's formula, and it was discovered that V(H2O2) played the most dominant role. Finally, by a simple magnetic separation, the rGO/Fe/Co/Ni trimetallic nano compound was still retained 47% of its catalytic capacity after five consecutive recoveries using this catalyst and applying it to the next degradation experiment, which indicates its excellent reusability and reflects the outstanding degradation ability of this compounds.