Optimization of methylene blue dye degradation using heterogeneous Fenton-like reaction with Fe3O4 nanoparticles/PVDF macrospheres: A response surface methodology approach / Mohamed Syazwan Osman ... [et al.]
A heterogeneous Fenton-like reaction was investigated in this study using Fe3O4 nanoparticles/polyvinylidene fluoride macrospheres for the degradation of methylene blue (MB). MB dye is one of the most common contaminants found in industrial wastewater, and its degradation is considered critical from...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | en |
| Published: |
Universiti Teknologi MARA Cawangan Pulau Pinang
2024
|
| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/104956/1/104956.pdf https://ir.uitm.edu.my/id/eprint/104956/ https://uppp.uitm.edu.my/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | A heterogeneous Fenton-like reaction was investigated in this study using Fe3O4 nanoparticles/polyvinylidene fluoride macrospheres for the degradation of methylene blue (MB). MB dye is one of the most common contaminants found in industrial wastewater, and its degradation is considered critical from both an environmental and public health perspectives. In this work, using Response Surface Methodology coupled with the Box-Behnken Design, a systematic investigation on the effects of the initial pH, catalyst loading, and H2O2 dosage on degradation efficiency was performed. The obtained optimal conditions were pH 7, catalyst loading of 10 g/L, and dosage of H2O2 at 10 mM, which resulted a maximum degradation efficiency of 99.94%. The results showed that the efficiency of the Fenton-like reaction was obviously favoured by neutral pH, making a good balance between hydroxyl radical generation and catalyst stability. According to the ANOVA results, initial pH, catalyst loading, and H2O2 dosage are significant factors, and among those three, pH is the most critical one. Validation experiments demonstrated the predictive accuracy of the model, showing small percentage errors between experimental and predicted values. |
|---|