Proficient sonophotocatalytic degradation of organic pollutants using Co3O4/TiO2 nanocomposite immobilized on zeolite: Optimization, and artificial neural network modeling

Rashtbari S., Dehghan G., Marefat A., Khataee S., Khataee A.

Ultrasonics Sonochemistry, vol.102, 2024 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 102
  • Publication Date: 2024
  • Doi Number: 10.1016/j.ultsonch.2023.106740
  • Journal Name: Ultrasonics Sonochemistry
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Applied Science & Technology Source, Chemical Abstracts Core, Chimica, Compendex, INSPEC, MEDLINE, Directory of Open Access Journals
  • Keywords: Artificial neural network, Nanocomposites, Peroxidase-mimic activity, Sonophotocatalysis
  • Istanbul Technical University Affiliated: No


The health of all living organisms is greatly influenced by the quality of the water. Therefore, developing cost-effective, eco-friendly, and easily accessible methods is desperately needed to meet the high global demand for clean water. Recently, nanozyme-based dye degradation methods have been promising for the remediation of water pollution. In this work, peroxidase-mimic Co3O4/TiO2 nanocomposite was synthesized and characterized for its size, morphology, and crystalline structure. Colorimetric assay results showed that the peroxidase-like activity of the Co3O4/TiO2 nanocomposite was considerably enhanced compared to the pure Co3O4 NPs and TiO2 NPs. Besides excellent enzyme-mimic activity, the higher sonophotocatalytic dye degradation capability of the nanocomposite after immobilization on zeolite (Co3O4/TiO2@Ze) was also demonstrated. Under optimal conditions (pH = 5.0, 25 °C), 0.1 g/L of catalyst was able to degrade 100 % of methylene blue (MB) with 600 μM in the presence of 30 μM H2O2 within 12 min. GC/MS analysis and toxicity studies revealed less toxic metabolite production after treatment of MB with sonophotocatalytic Co3O4/TiO2@Ze. Modeling of MB degradation using artificial neural networks (ANN) with a 5:6:1 topology was successfully performed, and the results confirmed the fitness of theoretical and experimental outputs according to the calculated correlation coefficient values. The prepared nanocomposite could thus be used as a promising and highly effective catalyst for the removal of organic dyes from polluted water.