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

Abstract

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.

Machine-Learning-Enhanced Fluorescent Nanosensor Based on Carbon Quantum Dots for Heavy Metal Detection

“…When CQD nanosensors interact with heavy metal ions, electrons are transferred from the excited state of the CQD to the metal ions, leading to the quenching of fluorescence (Figure b) . Transmission electron microscopy (TEM) shows that the CQD nanosensor was well synthesized (Figure c) . A high-resolution TEM (HR-TEM) image of the single CQD nanosensor is shown in Figure S1.…”

Carbon Nanomaterial Fluorescent Probes and Their Biological Applications

“…1114 For urea sensing, which is important for health monitoring, an integrated fluorescent CD nanosensors with pH-responsive plasmonic silver nanoparticles have been reported. 1115 The urea increases the pH and generates plasmonic Ag NPs in situ, which quenches the CD fluorescence with a linear range of detection between 100 nM and 1 mM.…”

“…Besides disease markers, CNMs have been used to sense a broad range of analytes in vivo or in biological fluids ex vivo. , CNM-based optical recognition strategies for various important classes of metabolites, such as sugars, − lipids, − ascorbic acid, − uric acid and urea, − and mycotoxins have been developed and improved over the past decade. Below, we discuss some of the pioneering and recent advances that have been achieved on this topic.…”

Ratiometric Dual-Mode Optical Sensor Array for the Identification and Differentiation of Pesticides in Vegetables with Mixed Plasmonic and Fluorescent Nanostructures

“…Compared to single-dimensional sensors, multichannel sensor arrays exhibit superior resolving power, which escalates with the addition of more sensor elements . Moreover, while a single-mode sensor array consists of multiple sensor elements to enhance discrimination capacity, recording a signal from each element can be costly, time-intensive, and often unreliable. , The multimode sensor array, by recording multiple signals simultaneously from each sensor element and employing appropriate statistical methods for data processing, , achieves greater accuracy and repeatability. Multimode sensor arrays present a potent strategy for rapid, sensitive, and high-throughput detection because they acquire information from an analytical system in multiple dimensions.…”