ZnO Nanoflowers as Photosensitive Materials for Antibacterial Photodynamic Therapy: Experimental and Neural Network Modeling Approaches

Zinc oxide (ZnO) nanoflowers (NFs) are potential nanomaterials for antibacterial applications due to their unique morphology and tunable properties. ZnO nanoflowers have an ultrasmall size with a huge surface area to volume ratio due to their hexagonal petal structures, which makes them potential nanostructures for biomedical applications compared to the nanoparticles of other shapes. Zinc oxide (NFs) were synthesized by a chemical method and evaluated their optical, chemical, and biological characteristics were evaluated, with a particular focus on their antibacterial efficacy and cytotoxic effects on Hep-2 cell lines. Investigative methods such as dynamic light scattering (DLS), UV–Visible spectroscopy, scanning electron microscopy (SEM), and fluorescence confirmed their nanoscale architecture and uniform dispersion in aqueous media, with an approximate hydrodynamic diameter of 400 nm. The ZnO NFs established dose supported antibacterial, action anti Escherichia coli, creating inhibition zones of 14.12 mm at maximum concentration, 500 µg/ml and 4.23 mm at 32.25 µg/ml. Exposure to 418 nm light resulted in a decline in fluorescence intensity, thereby amplifying the antimicrobial response. Furthermore, a neural network (ANN) built on the Levenberg–Marquardt algorithm was implemented to model fluorescence behavior over time. The ANN exhibited high predictive accuracy and showed excellent correlation with experimental fluorescence data.