Photodegradation of ciprofloxacin by tannin-barium titanate catalysts and evaluation via artificial neural network modeling approaches

The visible-light-driven removal of ciprofloxacin (CIP) remains a challenge due to its persistence and contribution to antibiotic resistance. In this study, tannin-modified barium titanate (BaTiO₃) composites were synthesized using three different tannin forms (formaldehyde tannin, calcined tannin, and calcined formaldehyde tannin) to enhance photocatalytic performance. UV-DRS analysis confirmed that tannin modification effectively reduced the band gap of BaTiO₃ from ~ 3.4 eV to 3.15 eV (FTB) and ~ 2.6 eV (C-TB and C-FTB), enabling efficient visible-light activity. Under optimal operating conditions (pH 3, 5 ppm CIP, 20 mg catalyst), formaldehyde tannin-modified BaTiO₃ (FTB) achieved a maximum degradation efficiency of ~ 95% within 180 min. Kinetic evaluation showed that CIP degradation followed pseudo-first-order kinetics (k_app = 0.0086 min⁻¹ for FTB), and isotherm modelling indicated the best fit to the Freundlich model, confirming multilayer adsorption on heterogeneous surfaces. The artificial neural network (ANN) model demonstrated high predictive accuracy (R² > 0.99), identifying catalyst type and initial CIP concentration as the most influential parameters. These results highlight tannin-modified BaTiO₃ composites as promising, low-cost, and eco-friendly visible-light photocatalysts for antibiotic removal. The innovative aspect of this study is the modification of BaTiO₃ with bio-derived tannin derivatives. Tannin addition offers a sustainable and low-cost approach while also accelerating CIP degradation by reducing electron recombination. Additionally, the experimental data were integrated with an advanced ANN model, providing a powerful and interpretable hybrid approach for predicting catalyst performance.