Proficient sonophotocatalytic degradation of organic pollutants using Co3O4/TiO2 nanocomposite immobilized on zeolite: Optimization, and artificial neural network modeling.
Ultrason Sonochem
; 102: 106740, 2024 Jan.
Article
en En
| MEDLINE
| ID: mdl-38171194
ABSTRACT
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 (pHâ¯=â¯5.0, 25⯰C), 0.1â¯g/L of catalyst was able to degrade 100â¯% of methylene blue (MB) with 600⯵M in the presence of 30⯵M H2O2 within 12â¯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 561 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.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Óxidos
/
Cobalto
/
Zeolitas
/
Contaminantes Ambientales
/
Nanocompuestos
Idioma:
En
Revista:
Ultrason Sonochem
Asunto de la revista:
DIAGNOSTICO POR IMAGEM
Año:
2024
Tipo del documento:
Article
País de afiliación:
Irán