Modelling and optimization of dye removal by Fe/Cu bimetallic nanoparticles coated with different Cu ratios

Ulucan-Altuntas K., Kuzu S. L.

MATERIALS RESEARCH EXPRESS, vol.6, no.11, 2019 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 6 Issue: 11
  • Publication Date: 2019
  • Doi Number: 10.1088/2053-1591/ab4bb5
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Keywords: bimetallic nanoparticle, nano zero valent iron, Fe/Cu, dye, textile wastewater, TEXTILE WASTE-WATER, PHOTOCATALYTIC DEGRADATION, FENTON OXIDATION, RHODAMINE-B, ELECTROCOAGULATION, ADSORPTION, AZO, COST, CARBON
  • Yıldız Technical University Affiliated: Yes


As the pollution from textile wastewater amount increases each year, discharge threshold values are reduced by regulations in order to limit receptor mass loading. This situation reveals the necessity of introducing innovative solutions instead of traditional systems in the treatment of textile wastewater. In the present study, we implemented dye removal by synthesized Fe/Cu bimetallic nanoparticles. Then, a multiple fuzzy-based model was applied in order to estimate colour removal. Initial colour concentration, pH, reaction time, Cu ratio on Fe/Cu nanoparticle, and Fe/Cu nanoparticle concentrations were selected as independent variables and fuzzified in an artificial intelligence-based approach. A mamdani-type fuzzy interface system was used. Input and output variables were designed with Gaussian membership functions. The predicted results gathered from fuzzy-logic system and the experimental results were compared with multiple regression approach. The regression coefficient was obtained as 0.992. According to multiple regression results, the most effective input variable was determined as the Cu ratio on Fe/Cu nanoparticle. The optimum conditions were also concluded via MathCad program. The highest removal efficiency was attained with 5% Cu ratio on Fe/Cu nanoparticle at 200 mg L-1 concentration. Furthermore, the prepared fuzzy-logic modelling demonstrated that the removal of dye by Fe/Cu nanoparticles is suitable for modelling.