Fluorometric and Colorimetric Hybrid Carbon-Dot Nanosensors for Dual Monitoring of Urea

Urea is an important indicator for health, environmental, and energy applications worldwide. Various analytics have been developed to detect urea rapidly and selectively for real-world interfacing; however, they still suffer from noise fluctuations due to environmental and instrumental conditions because most analytics are based on a single-signal readout system. In this study, we designed and synthesized a dual-signal, fluorometric and colorimetric, and read-out assay that integrates fluorescent carbon dot (CD) nanosensors with pH-responsive plasmonic silver nanoparticles (Ag NPs) for urea detection. The urease enzyme can specifically hydrolyze urea to generate carbon dioxide and ammonia, causing an increase in the pH, which activates the reduction affinity of tannic acid to generate plasmonic Ag NPs in situ. In situ generation of plasmonic Ag NPs is enabled by the reduction affinity of tannic acid, which is activated when the pH rises as a result of the urease enzyme hydrolyzing urea to produce carbon dioxide and ammonia. The absorption spectra of the Ag NPs overlapped closely with the fluorescence spectrum of the CDs, enabling effective quenching of the CD fluorescence upon urea exposure. This fluorogenic and chromogenic dual signal is used to quantify the accurate urea concentrations, showing a limit of detection (LOD) of 18 nM and 1.05 μM for fluorometric and colorimetric sensing within linear ranges between 100 nM–1 mM and 50 μM–1 mM, respectively─the lowest recorded LOD among fluorometric or colorimetric sensors. In addition, the dual sensor showed reliable detection of urea in real urine samples with (96–102.5%) recoveries. Finally, the dual-signal nanosensor was successfully implanted in the hydrogel matrix to facilitate a solid-state stable signal readout with an LOD of 287 nM. This dual-sensor construct provides fundamental solutions for nanomaterials in reliable and accurate urea detection applications that accelerate real-world interfacing.