Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/4948
Title: Synthesis and characterization of MIL-101 (Fe) as efficient catalyst for tetracycline degradation by using NaBH4: Artificial neural network modeling
Authors: Edebali, S.
Keywords: ANN
Catalyst
Degradation
MOF
Tetracycline
Publisher: Elsevier B.V.
Abstract: In this work, Fe-based metal organic framework (MIL-101 (Fe) MOF) was synthesized to use it as a catalyst for the catalytic degradation of tetracycline antibiotic with NaBH4. The synthesized MOF were characterized by Fourier Transform Infrared Spectroscopy, X-ray Diffraction, Scanning Electron Microscopy/Electron Dispersive X-ray and point of zero charge pH analysis. The effects of parameters such as contact time, pH, NaBH4 concentration and the amount of catalyst on the removal process were investigated and optimum parameters were determined. According to this, tetracycline removal efficiency was determined as 0.180 in terms of Ct/C0 at the end of 60-min contact time under determined optimum conditions for 60 ppm tetracycline solution. Moreover, the process was modeled with Artificial Neural Networks approach by using empirical results obtained from where process parameters were investigated. Finally, it was revealed with HPLC analysis that tetracycline was converted into different products as a result of applied process. © 2023
URI: https://doi.org/10.1016/j.apsadv.2023.100496
https://hdl.handle.net/20.500.13091/4948
ISSN: 2666-5239
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

Show full item record



CORE Recommender

Page view(s)

34
checked on Apr 22, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.