Fluorescent Nano-sensors at the Nano–Bio Interface: Mechanistic Convergence of FRET, Nanomaterials and AI-Enabled Diagnostics

Abstract

Fluorescent nano-sensors at the nano–bio interface has undergone a mechanistic convergence in which fluorescence resonance energy transfer (FRET) based transduction, nanomaterial enabled signal control and artificial intelligence driven analytics are increasingly integrated to enable intelligent diagnostic applications. This study provides a comprehensive bibliometric synthesis that clarifies how fluorescent nano-sensor research has structurally evolved over the past two decades with particular emphasis on translational relevance. By integrating temporal growth analysis, intellectual structure mapping, collaboration networks and thematic evolution the study demonstrates increasing shift from early mechanism-driven FRET systems toward mature application-oriented platforms increasingly augmented by artificial intelligence. The results reveal strong thematic convergence between fluorescence mechanisms, nanomaterials and AI-assisted analytics supported by globally networked yet institutionally concentrated collaboration hubs. Importantly, this work identifies emerging diagnostic trajectories characterized by automated signal interpretation enhanced sensitivity and adaptive analytical performance. These insights provide strategic evidence base for guiding methodological standardization, interdisciplinary collaboration and validation-focused research. Finally, the findings support the accelerated development and real-world translation of intelligent fluorescent nano-sensors for clinical diagnostics, environmental monitoring and point-of-care applications.