Photophysical and quenching principles governing advanced materials for fluorescence-based biosensing: mechanisms and analytical performance.

Optical fluorescence biosensing has emerged as one of the most powerful strategies for ultrasensitive molecular detection, driven by rapid advances in fluorophore engineering, nanomaterial design, and signal-transduction architectures. At the core of these technologies lie fundamental excited-state processes, including fluorescence emission, Förster resonance energy transfer (FRET), photoinduced electron transfer (PET), and intramolecular charge transfer (ICT), that govern the generation, modulation, and detection of optical signals. In this review, we present a photophysics-centered framework for understanding and designing fluorescence-based biosensing processes, systematically correlating excited-state dynamics with analytical sensing performance. We examine a broad range of fluorescent materials, including organic dyes, semiconductor and metal quantum dots, perovskite nanocrystals, transition-metal complexes, lanthanide emitters, and emerging carbon-based nanodots, highlighting how their emission characteristics, quantum yields, photostability, and surface chemistry influence sensing capabilities. Particular emphasis is placed on fluorescence quenching mechanisms and the role of advanced quenching platforms including graphene derivatives, metal oxides, metal-organic frameworks (MOFs), covalent organic frameworks (COFs), and hybrid nanostructures in tuning sensitivity, selectivity, and detection limits. Beyond material systems, we discuss recent progress in device integration and analytical methodologies, including microfluidic architectures, smartphone-enabled sensing platforms, nanophotonic metasurfaces, and artificial-intelligence-assisted spectral analysis, which are accelerating the translation of fluorescence biosensing toward portable and high-throughput applications. Despite these advances, challenges such as photobleaching, spectral interference, surface heterogeneity, and manufacturing reproducibility continue to affect analytical reliability. Emerging strategies based on defect-engineered two-dimensional materials, hybrid optical modalities, and machine-learning-driven signal interpretation are therefore highlighted as promising routes toward improved robustness and accuracy. By integrating photophysical principles, nanomaterial design, and analytical performance metrics into a unified perspective, this review provides a conceptual roadmap for the rational development of next-generation fluorescence-based biosensing technologies.