Detection Range Research Articles

Highly scalable solid-core inhibited-coupling fiber-based plasmonic refractive index sensor.

Advancements in plasmonic sensing require simultaneous detection capability that ensures large-scale detection with reduced losses. In this work, we propose a new solid-core fiber-based refractive index (RI) sensor with an ultra-broad detection range. The proposed fiber consists of a relatively simple single-ring cladding with six circular tubes in which the light is guided in the core based on the inhibited-coupling (IC) mechanism. The sensing performance is investigated using extensive finite-element modeling (FEM) through the combination of IC and surface plasmon resonance (SPR) sensing technology. Our results show a low loss of <3 dB/cm across the RI detection range from 1 to 1.60, peaking the wavelength sensitivity (WS) of 3000 nm/RIU and figure of merit (FOM) of 120 RIU-1. Our study also includes the investigation of the fabrication tolerance, fiber bending, and the use of alternative plasmonic materials, providing insights into the practical implementation capability of the proposed sensor. Our findings highlight the potential of the proposed sensor in emerging applications such as detecting air pollutants, biochemical substances, and DNA, paving the way towards bio-sensing within a lab-on-a-chip platform.

Integrating Metal-Organic Framework Hybrid into Nucleic Acid-Based Hydrogel for Highly Selective Recognition and Sensitive Detection of Sarafloxacin.

Metal-organic framework-based hybrids (MOFzyme) have promising applications in colorimetric aptasensors due to their highly efficient and stable catalytic activity. However, their efficient application in biosensors remains a challenging issue due to the limited reaction site and amorphous structure. Herein, we encapsulated catalase inside MOF cavities to prepare an MOFzyme with many functional groups on its surface, and the functional groups were utilized for the subsequent integration of MOFzyme into the hyaluronic acid-DNA hydrogel. Moreover, the accurate and flexible synthesis unit of the hydrogel enabled the prepared DNA hydrogel to adjust the shape to suit and encapsulate MOFzyme. Subsequently, a novel colorimetric sensing strategy for detecting Sarafloxacin (Sar) was developed based on the excellent catalytic ability mediated by MOFzyme and the stimulus responsiveness of the DNA hydrogel. In addition, an evolved aptamer with a higher affinity for Sar was obtained via a semirational design strategy and elaborately designed into a synthetic unit of DNA hydrogel, significantly improving the response sensitivity and specificity of the aptasensor. The constructed aptasensor exhibited a wide linear detection range of 0.003 and 200 ng/mL with a low detection limit of 2.06 pg/mL. Above all, this work provides a novel and sensitive way to determine hazardous substances in food and environments.

Deep Learning-Enhanced Portable Chemiluminescence Biosensor: 3D-Printed, Smartphone-Integrated Platform for Glucose Detection

A novel, portable chemiluminescence (CL) sensing platform powered by deep learning and smartphone integration has been developed for cost-effective and selective glucose detection. This platform features low-cost, wax-printed micro-pads (WPµ-pads) on paper-based substrates used to construct a miniaturized CL sensor. A 3D-printed black box serves as a compact WPµ-pad sensing chamber, replacing traditional bulky equipment, such as charge coupled device (CCD) cameras and optical sensors. Smartphone integration enables a seamless and user-friendly diagnostic experience, making this platform highly suitable for point-of-care (PoC) applications. Deep learning models significantly enhance the platform’s performance, offering superior accuracy and efficiency in CL image analysis. A dataset of 600 experimental CL images was utilized, out of which 80% were used for model training, with 20% of the images reserved for testing. Comparative analysis was conducted using multiple deep learning models, including Random Forest, the Support Vector Machine (SVM), InceptionV3, VGG16, and ResNet-50, to identify the optimal architecture for accurate glucose detection. The CL sensor demonstrates a linear detection range of 10–1000 µM, with a low detection limit of 8.68 µM. Extensive evaluations confirmed its stability, repeatability, and reliability under real-world conditions. This deep learning-powered platform not only improves the accuracy of analyte detection, but also democratizes access to advanced diagnostics through cost-effective and portable technology. This work paves the way for next-generation biosensing, offering transformative potential in healthcare and other domains requiring rapid and reliable analyte detection.

Raman measurements using an acousto-optic tunable filter spatial heterodyne Raman spectrometer with an echelle-mirror structure

This study presents an acousto-optic tunable filter technology-based echelle-mirror spatial heterodyne Raman spectrometer (AOTF-EMSHRS) that integrates echelle gratings with mirror spatial heterodyne detection. The instrument uses the grating’s high resolution and the AOTF’s rapid wavelength selection capability to optimize the optical path through a mirror design. This results in a high signal-to-noise ratio (SNR), high spectral resolution, and broad wavelength range measurements. After calibration, the theoretical resolution reached 1.53 cm−1, with a single-order spectral detection range of 1574.3 cm−1. The spectral detection range spans from 100 cm−1 to 4397 cm−1. Experimentally, we detected and analyzed various organic and inorganic substances and solutions. We compared EMSHRS performances with and without the AOTF and found that the SNR of the AOTF-EMSHRS system has improved by at least twofold. Additionally, we measured solutions with different molar concentrations, various sulfate mixtures, and mixtures in transparent containers made from different materials, obtained comprehensive spectral information, and conducted detailed analyses. The AOTF-EMSHRS demonstrated excellent measurement performance during complex sample detection and analysis.

Synthesis of Janus Polydiacetylene Sensor Particles with Thermochromism and Solvatochromism Properties

The first report is presented on the fabrication of anisotropic Janus polydiacetylene (PDA) microparticles with dual colorimetric properties. Spherical proto‐PDA particles are initially created by drying an emulsion containing 10,12‐pentacosadiynoic acid (PCDA) monomers, followed by UV polymerization. By heating an aqueous dispersion of these PDA particles, the unpolymerized PCDA within the PDA particles is liquefied, inducing partial phase separation and eventually leading to the formation of a Janus morphology composed of proto‐PDA and deriv‐PDA bulbs. Notably, each bulb of the Janus particles undergoes a blue‐to‐red transition under thermal stress during the Janus formation process, with subsequent UV irradiation triggering a reversible red‐to‐blue transition. This reversibility is attributed to the formation of new self‐assembled PCDA domains from residual PCDA monomers within the particles. Interestingly, each bulb of the Janus PDA particles exhibits distinct solvatochromic properties. These findings suggest significant potential for Janus PDA particles in advanced sensing technologies, particularly as solvent sensors with enhanced sensitivity and an expanded detection range.

A multi-dictionary fusion method based on improved dynamic time warping for moveable rail damage localization

Abstract Traditional structural health monitoring (SHM) of rails relies on a fixed single sensor, limited by detection range and noise interference. Therefore, a multi-dictionary fusion method for movable rail damage localization is proposed based on improved dynamic time warping (DTW). The approach combines onboard acoustic emission sensors with peak detection frames to measure the moving distance of the inspection wheels and monitor a wide range of rails. Aiming to enhance the damage information, an innovative DTW-based multi-dictionary sparse representation algorithm is presented for data fusion. The second-order difference of the Mahalanobis distance is employed to optimize the fusion weights from the global property. A two-feature adaptive threshold is designed to precisely detect and localize damage on rails. The effectiveness of this method is verified at laboratory testing speeds less than 0.75 m s−1. The results demonstrate that it can accurately detect 2 mm deep strip and square damage, providing new inspiration for rail SHM.

Iron/phosphorus co-doped carbon nanozyme for colorimetric sensing of organophosphorus pesticides in food.

In this work, a peroxidase-like (POD-like) nanozyme of Fe/P-NC was synthesized by doping phosphorus (P) and nitrogen (N) to manipulate iron (Fe) activity centers, which showed catalytic activity and kinetics comparable to those of natural HRP. Based on the efficient POD-like activity of the Fe/P-NC nanozyme and cascaded catalytic reactions with acetylcholinesterase (AChE), we constructed a colorimetric, affordable and sensitive sensing platform to detect organophosphorus pesticides (OPs). In the presence of AChE, the POD-like activity of the prepared Fe/P-NC was suppressed, which weakened the Fe/P-NC-catalyzed oxidation of TMB. After the introduction of OPs, the catalytic activity of the Fe/P-NC nanozyme was restored, resulting in efficient oxidation of TMB and an increasing blue color. By monitoring the variation in UV-vis absorbance, OPs could be quantitatively analyzed. The proposed colorimetric method exhibited superior analytical performance, with a wide detection range of 0.5-100 ng mL-1 and a low detection limit of 0.13 ng mL-1 for OPs. The assay was successfully employed to detect methyl parathion in fruit and vegetable samples. This work provides new insights into the design of new efficient nanozymes for the rapid and low-cost detection of OPs in real samples.

High-Sensitivity Fluorescent Sensing Platform for Rapid and Selective Detection of Chlorpyrifos Pesticide in Water Samples Using Terbium-Isatin-3-allyl Complex.

The detection of organophosphorus pesticides, particularly chlorpyrifos, in environmental samples is essential due to their widespread use and associated health risks. In this study, we developed a high-sensitivity fluorescent sensing platform utilizing an Isatin-3-allyl-terbium (IS-Tb) complex in solution for the rapid and selective detection of chlorpyrifos in various water samples. The proposed chemical structure of the complex in solution was evaluated using molar ratio method. The IS-Tb complex was characterized in solution, as it was not isolated in the solid state. To assess its structural and optical properties, several characterization techniques were employed. UV-Vis spectrophotometry was used to evaluate the absorption characteristics, and spectrofluorimetry was applied to assess the fluorescence properties. Additionally, the stoichiometry of the complex was determined using the molar ratio method, which confirmed a 1:1 ligand-to-metal ratio and provided the optimal conditions for sensing chlorpyrifos. The IS-Tb complex exhibited weak intrinsic fluorescence, which was significantly enhanced upon interaction with chlorpyrifos, enabling sensitive and quantitative analysis. Methanol was identified as the best solvent for maximizing the sensitivity of chlorpyrifos detection. The sensor demonstrated a wide linear detection range from 0.006 to 28µg/L, with a low limit of detection (LOD) of 2 ng/L. The sensor's selectivity for chlorpyrifos over other commonly encountered pesticides (13 organophosphorus) and environmental contaminants was high, ensuring minimal interference. The performance of the sensor was validated using spiked water samples, yielding an average recovery of 101% with a relative standard deviation (RSD) of less than 5%. These results suggest that the proposed sensing platform is a powerful tool for the environmental monitoring of chlorpyrifos, with significant implications for public health protection and regulatory compliance.

A Smartphone‐Integrated Coated Microneedle Sensor for In‐Situ Extraction and Rapid Detection of Total Phenols in Fruits and Vegetables

As interest in monitoring the nutritional and antioxidant levels in fruits and vegetables grows, the need for efficient, non‐invasive detection methods increases. In this work, a novel coated microneedle colorimetric sensing platform is designed to rapidly and sensitively detect total phenolic compounds (TPC) in fruits and vegetables, which is the key indicator of their nutritional and antioxidant properties. The platform utilizes a swollen microneedle structure to efficiently collect juice samples, enhancing detection efficiency through colorimetric analysis and eliminating the complexity of traditional methods. The microneedles are fabricated from a composite material consisting of 10,12‐pentacosadiynoic acid (PCDA) and methacrylated gelatin (GelMA), with a secondary layer containing α‐cyclodextrin to selectively bind polyphenols, thereby inducing a visible color change for the specific detection of TPC. The colorimetric response is directly correlated with the concentration of TPC, facilitating on‐site analysis. Using phenol as a model molecule, the detection range of the system for phenol is 10‐60 mM, with an LOD of 0.5 mM. Furthermore, a mobile application enables portable detection and analysis, reducing detection time from several hours to just 30 min. This technology offers a promising approach for the rapid, reliable monitoring of phenolic content in fresh produce, with potential applications in food quality control, nutritional analysis, and agricultural monitoring.

Meta-YOLOv8: Meta-Learning-Enhanced YOLOv8 for Precise Traffic Light Color Detection in ADAS

The ability to accurately detect traffic light color is critical for the functioning of Advanced Driver Assistance Systems (ADAS), as it directly impacts a vehicle’s safety and operational efficiency. This paper introduces Meta-YOLOv8, an improvement over YOLOv8 based on meta-learning, designed explicitly for traffic light color detection focusing on color recognition. In contrast to conventional models, Meta-YOLOv8 focuses on the illuminated portion of traffic signals, enhancing accuracy and extending the detection range in challenging conditions. Furthermore, this approach reduces the computational load by filtering out irrelevant data. An innovative labeling technique has been implemented to address real-time weather-related detection issues, although other bright objects may occasionally confound it. Our model employs meta-learning principles to mitigate confusion and boost confidence in detections. Leveraging task similarity and prior knowledge enhances detection performance across diverse lighting and weather conditions. Meta-learning also reduces the necessity for extensive datasets while maintaining consistent performance and adaptability to novel categories. The optimized feature weighting for precise color differentiation, coupled with reduced latency and computational demands, enables a faster response from the driver and reduces the risk of accidents. This represents a significant advancement for resource-constrained ADAS. A comparative assessment of Meta-YOLOv8 with traditional models, including SSD, Faster R-CNN, and Detection Transformers (DETR), reveals that it outperforms these models, achieving an F1 score, accuracy of 93% and a precision rate of 97%.

Vernier Effect-Enhanced Temperature Sensing Based on On-Chip Spiral Resonant Cavities

The optical Vernier effect has been widely studied due to its remarkable effect in improving the sensitivity and resolution of optical sensors. This effect relies on the overlapping envelope of two signals with slightly detuned frequencies. In the application of on-chip optical waveguide resonant cavities with whispering gallery modes, due to the on-chip space limitations, the length of the resonant cavity is restricted, resulting in an increased free spectral range. In the case of a small Vernier effect detuning, the required large Vernier envelope period often exceeds the available wavelength range of the detection system. To address this issue, we propose a novel on-chip waveguide structure to optimize the detection range of the cascaded Vernier effect. The proposed spiral resonant cavity extends the cavity length to 7.50 m within a limited area. The free spectral width (27.46 MHz) is comparable in size to the resonant linewidth (9.41 MHz), shrinking the envelope free spectral width to 371.29 MHz, which greatly facilitates the reading of the Vernier effect. Finally, by connecting two resonant cavities with similar cavity lengths in series and utilizing the Vernier effect, temperature sensing was verified. The results show that compared with a single resonant cavity, the sensitivity was improved by a factor of 14.19. This achievement provides a new direction for the development of wide-range and high-sensitivity Vernier sensing technologies.

Enhancing Dynamic Range in Low-Noise 2D-Integrated Organic Photodiodes by Mitigating Langevin Recombination.

Organic photodiodes (OPDs) are a significant focus for the next-generation of light-detection technologies. However, organic semiconductors in OPDs still face key challenges, such as low carrier mobilities and limited efficiency in generating photon-induced signals, which affect the detectable resolution and dynamic range. In this study, the characterization of the interaction between organic polymeric bulk heterojunctions and two-dimensional (2D) transition metal dichalcogenides (MoS2) reveals an enhancement in photocurrent due to improved photogeneration dynamics (e.g., reduction of bimolecular recombination and enhancing charge carrier transfer). Consequently, the optimized 2D MoS2-additive OPD achieved an exceptionally high linear dynamic range (LDR) exceeding 174 dB and an outstanding specific detectivity (D*) of 3.21 × 1012 Jones, while reaching femto-scale noise levels. This presents the potential of state-of-the-art OPDs for various light signal applications.

Thalassemia genetic screening of pregnant women with anemia in Northern China through comprehensive analysis of thalassemia alleles (CATSA).

Thalassemia is an inherited blood disorder and traditionally considered more prevalent in Southern China. However, with increased migration and intermarriage, more and more thalassemia carriers had been reported in Northern China. The lack of screening for thalassemia carriers may also result in missed diagnosis in Northern China. Additionally, thalassemia carriers are usually asymptomatic or mild anemia, but their anemia can get worse during pregnancy. Iron deficiency anemia (IDA) is also one of the causes of anemia during pregnancy. In particular, both IDA and thalassemia are characterized by microcytic hypochromic anemia. The overlap of symptoms and the presence of thalassemia carriers with IDA may lead to misdiagnosis. In this study, long-read sequencing based approach termed comprehensive analysis of thalassemia alleles (CATSA) had been performed for 244 pregnant women in Northern China whose results of routine blood examinations were abnormal. As a result, 16.39 % (40/244) of the anemic pregnant women carried at least one mutation of thalassemia. One Hb H patient and a rare α-globin gene triplication combined with β-thalassemia were also identified. Of the 44 thalassemia variants detected, the -α3.7, -SEA and HBB:c.316-197C > T were the most common variants. CATSA is of great significance for determining exact genotype of 22.50 % (9/40) thalassemia carriers because 8 variants they carried were outside the detection range of routine genetic tests. It is noted that 2 novel deletions of HBA gene were identified, expanding the genotype spectrum of α-thalassemia. Our findings demonstrate the importance of thalassemia screening in Northern China. Future research should focus on expanding screening to include more diverse populations.

Fast forward modeling and response analysis of extra-deep azimuthal resistivity measurements in complex model

The Extra-Deep Azimuthal Resistivity Measurements (EDARM) tool, as an emerging technology, can effectively identify geological interfaces within a range of several tens of meters around the borehole, providing geological structures for directional drilling, and effectively improving reservoir encounter rates and enhancing oil and gas recovery rates. However, the signal is jointly affected by interfaces located both ahead of the drill bit and around the borehole, making it impossible to directly obtain the interface position from the signal. Considering the increased detection range of EDARM and the requirements for computational efficiency, this paper presents a 2.5-dimensional (2.5D) finite element method (FEM). By leveraging the symmetry of simulated signals in the spectral domain, the algorithm reduces computation time by 50%, significantly enhancing computational efficiency while preserving accuracy. During the geosteering process, fault and wedge models were simulated, and various feature parameters were extracted to assess their impact on the simulation outcomes of EDARM. The results show that both Look-around and Look-ahead modes exhibit sensitivity to changes in the angle of the geological interface. Crossplot analysis allows for effective identification of interface inclinations and the distances between the instrument and the geological interface. This recognition method is quick, intuitive, and yields reliable results.

Ultrasensitive Electrochemical Detection of Paracetamol with a Polypyrrole-Cobalt Oxide Nanocomposite Modified Sensor

Abstract We present the development of an ultrasensitive electrochemical sensor for detecting paracetamol, utilizing nanomaterial modified electrode. Cobalt oxide (Co₃O₄) nanoparticles were synthesized via a hydrothermal method using cobalt (II) nitrate hexahydrate. This was followed by the polymerization of pyrrole with ferric chloride serving as the oxidizing agent. Equal ratios of polypyrrole (PPy) and Co₃O₄ were then subjected to sonication. The structural and compositional characteristics of the resulting nanocomposite were analyzed using various techniques. XRD confirmed the crystalline structure of the PPy/Co₃O₄ composite, while UV-Vis spectroscopy identified distinct absorption peaks corresponding to both PPy and Co₃O₄. FT-IR analysis revealed specific functional groups present in the nanocomposite, and FE-SEM provided visual confirmation of the successful integration of PPy and Co₃O₄. Additionally, EDAX offered insights into the elemental composition of the composite. Cyclic voltammetry showed that the PPy/Co₃O₄ modified electrode generated significantly enhanced current responses and well-defined redox peaks compared to the individual components. The PPy/Co₃O₄ modified sensor demonstrated excellent stability, high catalytic current for paracetamol (200 µM), highlighting its increased sensitivity and selectivity. This new sensor showed a detection limit of 0.49 µM and supported a linear detection range from 0 µM to 200 µM, allowing for precise quantification of paracetamol concentrations.

Rapid Detection of Alpha-Fetoprotein (AFP) with Lateral Flow Aptasensor

We present a lateral flow aptasensor for the visual detection of alpha-fetoprotein (AFP) in human serum. Leveraging the precise molecular recognition capabilities of aptamers and the distinct optical features of gold nanoparticles, a model system utilizing AFP as the target analyte, along with a pair of aptamer probes, is implemented to establish proof-of-concept on standard lateral flow test strips. It is the first report of an antibody-free lateral flow assay using aptamers as recognition probes for the detection of AFP. The analysis circumvents the numerous incubation and washing steps that are typically involved in most current aptamer-based protein assays. Qualitative analysis involves observing color changes in the test area, while quantitative data are obtained by measuring the optical response in the test zone using a portable strip reader. The biosensor exhibits a linear detection range for AFP concentrations between 10 and 100 ng/mL, with a minimum detection limit of 10 ng/mL. Additionally, it has been successfully applied to detect AFP in human serum samples. The use of aptamer-functionalized gold nanoparticle probes in a lateral flow assay offers great promise for point-of-care applications and fast, on-site detection.

Efficient and sensitive detection of absorptive defects in fused silica optics based on laser thermal pumping combined with micro-interferometric imaging

A novel, efficient, and sensitive method for detecting absorptive defects in fused silica optics, called laser thermal pumping combined with micro-interferometric imaging (LTP-MII), is proposed. First, the thermal deformation simulation of fused silica optics under a 355-nm LTP was calculated using a multiphysics field approach. Even with ppm-level absorption on the surface, a 600-W/mm2 LTP power density could induce a 2.1-nm deformation within the detection range of the MII. Subsequently, an LTP-MII system was constructed, comprising a 355-nm LTP spot with a 0.45-mm diameter and a white-light MII. Results from different fused silica samples showed that, at the same LTP power density of 19.5 W/mm2, the induced thermal deformation followed this order: 5% absorption thin film (75.3 nm) &gt; a full brittle fracture pit defect (27.8 nm) &gt; a scratch defect (5.2 nm). However, no thermal deformation was observed for the super-smooth polishing low-absorption substrate under these conditions, though it exhibited a deformation of 13.31 nm when the LTP power density reached 110.7 W/mm2. In addition, thermal deformation was positively correlated with the LTP power densities. These results demonstrate that LTP-MII is an efficient and sensitive method for reflecting the photo-thermal absorption characteristics of surface defects in fused silica optics.

Electrochemiluminescence Resonance Energy Transfer Biosensor for the Human-Associated Clade of Streptococcus suis Based on Prereduction-Enhanced Yttrium MOFs.

Streptococcus suis, a significant zoonotic pathogen, annually caused substantial economic losses in the swine industry and had intensified threat to public health due to the recent emergence of human-associated clade. In this study, we discovered that the rare-earth metal-based metal-organic frameworks (Y-BTC) possessed excellent ECL capabilities. After prereduction at high voltage, its ECL intensity was enhanced by two times. Subsequently, we developed an efficient CRISPR/Cas12a-mediated electrochemiluminescence resonance energy transfer (ECL-RET) biosensor utilizing Y-BTC for the detection of the human-associated S. suis clade. Y-BTC was employed as the ECL-RET donor and ECL emitter, and the spherical nucleic acid Au NP was utilized as the ECL-RET receptor. In the presence of the target, isothermal amplification was triggered to generate a large number of amplicons, which subsequently activated the trans-cleavage activity of Cas12a. Cas12a cleaved the nucleic acid shell on the surface of Au NPs, reducing the spatial distance between Au NPs and Y-BTC due to electrostatic adsorption, thereby quenching the ECL of Y-BTC via ECL-RET. Consequently, the presence of targets can be observed by a reduced ECL signal. The sensor exhibited a detection range of 25 pM to 50 nM, with a detection limit as low as 17 pM. The practical utility was verified through actual sample testing. Our proposed ECL-RET sensing strategy provides a new avenue for the sensitive detection of S. suis. The universality has also been demonstrated using Fusobacterium nucleatum, Salmonella pullorum, and Listeria monocytogenes, holding great promise in the field of food safety and public health.

PCR-Free Self-Calibrated Ratiometric Electrochemical Genosensor Utilizing a Dual-Signal Amplification Approach for Genomic Detection of Mycobacterium tuberculosis

Abstract Tuberculosis (TB) remains a critical global health challenge. While many electrochemical (EC) biosensors have been developed for Mycobacterium detection, most relied on PCR amplification strategies. This study introduced a PCR-free, self-calibrated ratiometric electrochemical (REC) genosensor leveraging dual-signal amplification for the detection of Mycobacterium tuberculosis (MTB). Electroactive silver nanoparticles (AgNPs) were modified onto screen-printed gold electrodes, followed by chemisorption of a methylene blue (MB)-tagged peptide nucleic acid (PNA) probe targeting MTB genomic DNA. MTB presence triggered structural changes in the probe, reducing the MB redox current (IMB) as the detection signal, while the Ag current (IAg) diminished as an internal calibration marker. This ratiometric mechanism minimized system errors, enhancing detection reliability. The genosensor achieved a broad detection range (3.5 fM–35 nM) with a detection limit of 1.59 fM for non-amplified MTB DNA, showing high specificity, reproducibility, and accuracy comparable to standard diagnostic methods. It effectively detected MTB in simulated sputum samples, demonstrating its potential for reliable, rapid, and amplification-free TB diagnostics.

Highly Green Fluorescent Carbon Dots from Gallic Acid: A Turn-On Sensor toward Pb2+ Ions.

Carbon dots (CDs) are emerging novel fluorescent sensing nanomaterials owing to their tunable optical properties, biocompatibility, and eco-friendliness. Herein, we report a facile one-pot hydrothermal route for the synthesis of highly green fluorescent CDs using gallic acid (GA) as a single carbon source in N,N-dimethylformamide (DMF) solvent, which serves as a nitrogen source and reaction medium. The optical properties of the synthesized GA-DMF CDs were systematically characterized by using UV-vis and photoluminescence spectroscopy, revealing strong green fluorescence. Further, to gain insights into their size and structural, elemental, and chemical composition, Fourier transform infrared, dynamic light scattering, high-resolution transmission electron microscopy (HR-TEM), X-ray diffraction, and X-ray photoelectron spectroscopy characterization techniques were performed. HR-TEM analysis confirmed the formation of uniformly spherical GA-DMF CDs with an average particle size of 16 ± 6.1 nm. Notably, the GA-DMF CDs exhibited a highly selective and turn-on fluorescent response to Pb2+ ions in aqueous solutions, which was attributed to a chelation-enhanced fluorescence mechanism. The detection limit for Pb2+ ions was determined to be as low as 7.15 × 10-7 M, with a broad linear detection range of 30-130 μM, underscoring their sensitivity and practical application in water quality monitoring. This study introduces a novel, sustainable approach for synthesizing nitrogen-doped CDs with outstanding optical properties and highlights their unprecedented selectivity toward Pb2+ ions, advancing the development of efficient and eco-friendly sensing platforms for heavy metal detection.