Multi-Analyte Sensitive Fluorophore Cross-Linked Nanofibers Based Antimicrobial Surface Enabling Bacterial Detection and Their Usage as Crystal Growth Template

In situ preparation of bifunctional thiazolo[5,4-d]thiazole (TTz)-based fluorophore cross-linked nanofibers is successfully performed. These multifunctional nanofibers are used as both crystal growth template and antibacterial substrate that makes bacterial detection possible simultaneously. These highly fluorescent nanofibers act as optical sensors toward many analytes. The acid, base, and metal cation-sensitive nature of the 2,5-bis(4-hydroxyphenyl)thiazolo[5,4-d]thiazole (HPhTT) dye makes the prepared PVA nanofibers sensitive against these chemicals. Metal nanoparticles (MNPs) or metal oxide crystal formation occurs on the surface of nanofibers without any reducing agent. The strong interaction between metal cations and fluorophores results in crystal formation on the surface, which is named for the first time as "complexation-triggered crystalization." These dye cross-linked and metal-interacted nanofibers exhibit antibacterial effect against E. coli (ATCC 25922), S. aureus (ATCC 25923), P. aeruginosa (ATCC 27853), and E. faecalis (ATCC 25922) strains. Also, the emission wavelength change of nanofibers in bacterial contamination makes it possible to use smart nanofiber films for optical bacteria detection. These novel materials pave the way for new applications such as smart wound bands, optical sensors, and one-step preparation of surface-enhanced Raman spectroscopy substrate.

Thiazolo[5,4-d]thiazole(TTz)-based fluorophore cross-linked nanofibers are used to prepare metal/metal oxide nanoparticle decorated NFs via complexation-triggered crystallization. CTC phenomenon enables green synthesis of MNPs on surface. Smart NFs exhibit reversible emission wavelength changes toward acid and base, and they are sensitive to metal cations as optic sensors. Moreover, they exhibit antibacterial effects against various strains while simultaneously making bacterial detection possibleimage