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This study focuses on optimizing polyethylene terephthalate-derived fluorescent carbon quantum dots (PET-FCQDs) for the removal of fluoxetine and ciprofloxacin from water, achieving removal efficiencies of 95.19% and 97.85%, respectively, using Box-Behnken design and machine learning models. The research integrates experimental and computational methods, including molecular dynamics and docking studies, to evaluate the therapeutic potential of PET-FCQDs as antidepressants and antibiotics, while also assessi

Author

Ghita

Language

EN