Microalgae-based CuO nanoflowers and CuO/ZnO nanoflower composites for photocatalytic degradation of ciprofloxacin antibiotic residue in water

Microalgae have recently been explored for the green synthesis of metal oxide nanoparticles, offering a cost-effective alternative to conventional methods. Although effective for azo dye removal, their application in antibiotic degradation remains underexplored. In this study, microalgae-based CuO nanoflowers (NFs) were synthesised using Chlorella vulgaris extract and combined with ZnO to enhance the photocatalytic degradation of ciprofloxacin (CIP). Addressing the weak charge separation of CuO, the wide bandgap of ZnO via formation of strong p-CuO/n-ZnO heterojunctions. Microalgae-based CuO NF were produced by varying the volume ratio between CuSO 4 and Chlorella vulgaris extract at 1:1 [CuO (1Cu:1MA)], 2:1 [CuO (2Cu:1MA)], and 1:2 [CuO (1Cu:2MA)] ratios. pH edges and kinetic experiments were conducted. The most effective CuO NF was combined with ZnO to form a composite, and a central composite design with response surface methodology was used to identify optimal conditions for maximum CIP degradation efficiency. CuO (2Cu:1MA) NF exhibited the highest CIP degradation at pH 7, while CuO (1Cu:1MA) and CuO (1Cu:2MA) showed optimal performance at pH 8. The superior performance of CuO (2Cu:1MA) NF was attributed to its low bandgap, high BET surface area, and abundant surface functional groups. Kinetic data followed a pseudo-second-order model. Maximum CIP degradation of 88.3% was achieved at pH 9, a catalyst dose of 1.0 g/L, and an initial CIP concentration of 10 mg/L for CuO/ZnO (2Cu:1MA) NF. After four cycles, degradation efficiency decreased by ~10%. Overall, microalgae-based CuO nanoflowers and CuO/ZnO composites show strong potential as sustainable and effective photocatalysts for mitigating antibiotic pollution. • Organic functional groups on algae-based NFs help degradation via surface adsorption • Kinetic results reveal that adsorption plays a key role in photocatalytic degradation • RSM-CCD optimisation showed that pH and initial CIP level strongly affect degradation