2024 : 11 : 16
Farhad Rahmani Chianeh

Farhad Rahmani Chianeh

Academic rank: Assistant Professor
ORCID:
Education: PhD.
ScopusId: 444
HIndex:
Faculty: Faculty of Engineering
Address: Faculty of Engineering, University of Kurdistan, Sanandaj, Iran
Phone:

Research

Title
Insightful properties-performance study of Ti–Cu–O heterojunction sonochemically embedded in mesoporous silica matrix for efficient tetracycline adsorption and photodegradation: RSM and ANN-based modeling and optimization
Type
JournalPaper
Keywords
Cu-Ti-O heterojunction, Mesoporous silica, Tetracycline photodegradation, Sonication
Year
2024
Journal Chemosphere
DOI
Researchers Morteza Khanmohammadi ، Farhad Rahmani Chianeh ، Javad J. Rahbar Shahrouzi ، Rojiar Akbari Sene

Abstract

This study aims to provide a comprehensive evaluation of the photocatalytic properties and performance of the Cu–Ti–O heterojunction sonochemically embedded in the mesoporous silica matrix. Various characterization analyses and adsorption/photodegradation experiments were performed to assess the potential of the sample for tetracycline (TC) removal. The characterization results indicated that sonication contributes to better dispersion of Ti–Cu–O species, resulting in more uniform particle sizes, stronger semiconductors-silica interaction, and less agglomeration. Furthermore, sonication significantly affected the optical nanocomposite features, leading to an improvement in charge carrier separation and a decrease in the band gap of Ti–Cu–Si (S) by approximately 2.6 eV. Based on the textural results, the ultrasound microjets increased the surface area and pore volume, which facilitate mass transfer and provide suitable adsorption sites for TC molecules. Accordingly, Cu–Ti–Si (S) demonstrated higher adsorption capacity (0.051 g TC/g adsorbent) and eliminated TC significantly faster (0.0054 L.mg−1.min−1) than a non-sonicated sample during 120 min of irradiation, resulting in 2.84 times improvement in the constant rate. In addition, experimental results were accurately modeled using a central composite design in combination with response surface methodology (RSM) and artificial neural networks (ANN) to predict and optimize TC photodegradation. Both RSM and ANN models revealed excellent predictability for TC degradation efficiency, with R2 = 99.47 and 99.71%, respectively. At optimal operational conditions (CTC = 20 ppm, photocatalyst dosage = 1.15 g.L−1, pH = 9, and irradiation time = 100 min), more than 95% and 87% of TC were degraded within the UV (375 W) and simulated solar light (400 W) irradiation periods, respectively. It was observed that the Cu–Ti–Si (S) nanocomposite maintained remarkable stability after four cycles with only a negligible 3% loss of activity, owing to the superior interaction between the bimetallic heterojunction and the silica matrix.