A fluorescent sensor array based on silver nanoclusters for identifying heavy metal ions

Harnessing Silver Nanoclusters to Combat Staphylococcus aureus in the Era of Antibiotic Resistance

Background/Objectives: In the race to develop new antibiotics to combat multidrug-resistant bacteria, particularly the ESKAPE pathogens which pose a significant threat to public health, silver nanoclusters (AgNCs) have emerged as a promising alternative. This article focuses on the potential of novel silver nanoclusters as an antimicrobial agent against Staphylococcus aureus, a high-priority pathogen known for its ability to cause persistent nosocomial infections and develop protective biofilms. Methods: In this study, we successfully synthesized AgNCs at pH 7 using an eco-friendly photoreduction method with poly acrylic acid (PAA) and poly methacrylic acid (PMAA) as stabilizers. This methodology produced fluorescent AgNCs, demonstrating their stability in aqueous solutions for at least three months and highlighting the effectiveness of PAA and PMAA as stabilizing agents. The AgNCs were incubated with S. aureus suspension, and the antimicrobial capability at different concentrations and times of incubation were determined. Also, the AgNCs hemocompatibility was studied by exposing the clusters to rat blood cells. Results: The in vitro assays revealed that AgNCs capping with PAA or PMAA has antimicrobial activity in low doses (the determination of minimum inhibitory concentration (MIC): 0.2 µg/mL, and the determination of minimum bactericidal concentration (MBC): 2 µg/mL) and without cytotoxicity (hemolysis less than 10%) to rat blood cells until 1 µg/mL. In the presence of both AgNCs (5 µg/mL), bacterial growth was completely inhibited within just 3 h. Conclusions: The findings of this study highlight the potential of silver nanoclusters as effective antimicrobial agents against S. aureus. Their stability, low toxicity, and rapid bactericidal activity make them promising candidates for further development in antimicrobial applications.

A double probe-based fluorescence sensor array to detect rare earth element ions

There is a persistent need for effective sensors to detect rare earth element ions (REEIs) due to their effects on human health and the environment. Thus, a simple and efficient fluorescence-based detection method for REEIs that offers convenience, flexibility, versatility, and efficiency is essential for ensuring environmental safety, food quality, and biomedical applications. In this study, 6-aza-2-thiothymine-gold nanoclusters (ATT-AuNCs) and bovine serum albumin/3-mercaptopropionic acid-AuNCs (BSA/MPA-AuNCs) were utilized to detect 14 REEIs (Sc3+, Gd3+, Lu3+, Y3+, Ce3+, Pr3+, Yb3+, Dy3+, Tm3+, Sm3+, Ho3+, Tb3+, La3+, and Eu3+), resulting in the creation of a simple, sensitive, and multi-target fluorescence sensor array detection platform. We observed that REEIs exert various enhancement or quenching effects on ATT-AuNCs and BSA/MPA-AuNCs. Thus, these two probes function as double signal channels, with the different effects of REEIs serving as signal inputs. Pattern recognition methods, including hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA), were used to assess the recognition performance of the constructed sensing system. Beyond the excellent ability to recognize individual REEIs, the platform is also capable of distinguishing mixed REEIs. Also, this approach was validated by applying it to detect REEIs in purified water samples. This method not only minimizes the need for synthesizing and optimizing new probes but also offers a novel approach for the determination and identification of diverse analytes, filling a gap in the detection of a large number of REEIs simultaneously.

A quenched fluorescence sensor array based on bis-lanthanide metal-organic framework for acetaldehyde detection and Baijiu discrimination

Discrimination of segmented Baijiu contributes to stabilizing the quality of products, improving revenue-generating effects. A fluorescence sensor array is constructed based on four fluorescence characteristic peaks of terbium@lanthanum metal-organic framework (Tb@La-MOF). Its fluorescence signal is specifically quenched, when Tb@La-MOF encounters acetaldehyde. Acetaldehyde may inhibit the absorption of energy by the organic ligands in MOF, or/and hydrogen bonding with -COOH on the organic ligand, resulting in energy transfer to Tb(Ⅲ). According to this, the quantitative detection of acetaldehyde is completed with a range of 10-300 μM and the detection limit of 5.5 μM. At the same time, it has been successfully applied to the discrimination of segmented Baijiu. Fifteen segmented from three wine cellars are 100 % discriminated with the combined processing of sensor arrays and analytical methods. Accuracy, simplicity, and low-cost are highlights of this fluorescence sensor array, which has considerable potential for application in detection, production, and food field.

A machine learning-assisted fluorescent sensor array utilizing silver nanoclusters for coffee discrimination

Coffee is a globally consumed commodity of substantial commercial significance. In this study, we constructed a fluorescent sensor array based on two types of polymer templated silver nanoclusters (AgNCs) for the detection of organic acids and coffees. The nanoclusters exhibited different interactions with organic acids and generated unique fluorescence response patterns. By employing principal component analysis (PCA) and random forest (RF) algorithms, the sensor array exhibited good qualitative and quantitative capabilities for organic acids. Then the sensor array was used to distinguish coffees with different processing methods or roast degrees and the recognition accuracy achieved 100%. It could also successfully identify 40 coffee samples from 12 geographical origins. Moreover, it demonstrated another satisfactory performance for the classification of pure coffee samples with their binary and ternary mixtures or other beverages. In summary, we present a novel method for detecting and identifying multiple coffees, which has considerable potential in applications such as quality control and identification of fake blended coffees.

Gold Nanocluster-Based Self-Assembly Fluorescence Microbeads for Sensor Array Discrimination of Multicomponent Metal Ions

Benefiting from easy visualization and simultaneous detection of multiple targets, fluorescence microbeads are commonly used as fluorescence-sensing elements to detect pollutants in the environment. However, the application of fluorescence microbead-based sensor arrays is still limited because fluorescence dyes always suffer from self-quenching, photobleaching, and spectral overlap. Herein, three kinds of gold nanoclusters (Au NCs) were assembled with polystyrene microspheres (PS NPs) by electrostatic interaction to prepare fluorescence microbeads (PS-Au NCs), developing a sensor array for the simultaneous analysis of multiple metal ions. In this work, different PS-Au NCs showed an enhancing or quenching fluorescence response to various metal ions, owing to distinct binding capacities. Combined with the recognition algorithm from linear discriminant analysis (LDA) and hierarchical cluster analysis (HCA), this sensor assay could realize single-component and multicomponent qualitative detection for 8 kinds of heavy metal ions (HMIs) including Cu2+, Co2+, Pb2+, Hg2+, and Ce3+. Particularly, the large surface area of PS NPs could provide a direct reaction microenvironment to improve the efficiency of the detection process. Meanwhile, the fluorescence property of Au NCs could also be enhanced by a partially effective aggregation-induced emission (AIE) effect to give better fluorescence signal output. Under optimal conditions, 8 kinds of heavy metals and their multicomponent mixtures could be identified at concentrations as low as 0.62 μM. Meanwhile, the analytical performance of this sensor assay in water samples was also verified, meeting the requirement of actual analysis. This study provides a great potential and practical example of single-batch, multicomponent identification for HMIs.

Nanotechnology-based optical sensors for Baijiu quality and safety control

Baijiu quality and safety have received considerable attention owing to the gradual increase in its consumption. However, owing to the unique and complex process of Baijiu production, issues leading to quality and safety concerns may occur during the manufacturing process. Therefore, establishing appropriate analytical methods is necessary for Baijiu quality assurance and process control. Nanomaterial (NM)-based optical sensing techniques have garnered widespread interest because of their unique advantages. However, comprehensive studies on nano-optical sensing technology for quality and safety control of Baijiu are lacking. In this review, we systematically summarize NM-based optical sensor applications for the accurate detection and quantification of analytes closely related to Baijiu quality and safety. Furthermore, we evaluate the sensing mechanisms for each application. Finally, we discuss the challenges nanotechnology poses for Baijiu analysis and future trends. Overall, nanotechnological approaches provide a potentially useful alternative for simplifying Baijiu analysis and improving final product quality and safety.

Elevating nanomaterial optical sensor arrays through the integration of advanced machine learning techniques for enhancing visual inspection of food quality and safety

Food quality and safety problems caused by inefficient control in the food chain have significant implications for human health, social stability, and economic progress and optical sensor arrays (OSAs) can effectively address these challenges. This review aims to summarize the recent applications of nanomaterials-based OSA for food quality and safety visual monitoring, including colourimetric sensor array (CSA) and fluorescent sensor array (FSA). First, the fundamental properties of various advanced nanomaterials, mainly including metal nanoparticles (MNPs) and nanoclusters (MNCs), quantum dots (QDs), upconversion nanoparticles (UCNPs), and others, were described. Besides, the diverse machine learning (ML) and deep learning (DL) methods of high-dimensional data obtained from the responses between different sensing elements and analytes were presented. Moreover, the recent and representative applications in pesticide residues, heavy metal ions, bacterial contamination, antioxidants, flavor matters, and food freshness detection were comprehensively summarized. Finally, the challenges and future perspectives for nanomaterials-based OSAs are discussed. It is believed that with the advancements in artificial intelligence (AI) techniques and integrated technology, nanomaterials-based OSAs are expected to be an intelligent, effective, and rapid tool for food quality assessment and safety control.

Role of silver nanoparticles and silver nanoclusters for the detection and removal of Hg(ii)

Silver metal, being a 3d transition metal in group 11 in the periodic table, is widely used in material science for its distinguished plasmonic properties. Nanoparticles (NPs) and nanoclusters (NCs) are widely used in sensing applications having a surface plasmon band and emissive properties, respectively. Mercury is one of the detrimental toxins and threats to various ecosystems. The distinction between nanoparticles and nanoclusters, the utility and toxicity of heavy metal mercury, fluorometric and colorimetric approaches to the recognition of mercury ions with NPs and NCs, the mechanism of detection, spot detection, and natural water sample analyses were illustrated in detail in this review article. Moreover, the sensing platform and analyte (Hg2+) fate were described for substantiating the mechanism. It was observed that NCs are mostly utilized for fluorometric approaches, while NPs are mostly employed for colorimetric approaches. Fluorometric detection is mainly quenching-based. However, sensing with enhancement was found in a few reports. Adulteration of other metals with silver particles often modifies the sensing platform.

Ensuring food safety by artificial intelligence-enhanced nanosensor arrays

Current analytical methods utilized for food safety inspection requires improvement in terms of their cost-efficiency, speed of detection, and ease of use. Sensor array technology has emerged as a food safety assessment method that applies multiple cross-reactive sensors to identify specific targets via pattern recognition. When the sensor arrays are fabricated with nanomaterials, the binding affinity of analytes to the sensors and the response of sensor arrays can be remarkably enhanced, thereby making the detection process more rapid, sensitive, and accurate. Data analysis is vital in converting the signals from sensor arrays into meaningful information regarding the analytes. As the sensor arrays can generate complex, high-dimensional data in response to analytes, they require the use of machine learning algorithms to reduce the dimensionality of the data to gain more reliable outcomes. Moreover, the advances in handheld smart devices have made it easier to read and analyze the sensor array signals, with the advantages of convenience, portability, and efficiency. While facing some challenges, the integration of artificial intelligence with nanosensor arrays holds promise for enhancing food safety monitoring.

Evaluation of AgNCs@PEI and their integrated hydrogel for colorimetric and fluorometric detection of ascorbic acid

A dual-mode colorimetric and fluorometric sensor based on water soluble silver nanoclusters (AgNCs@PEI) is developed for quantitative and visual detection of ascorbic acid (Asc A). The detection method relies on the Asc A induced aggregation of AgNCs@PEI, which resulted in fluorecsence quenching of the sensor. The clusters exhibited a unique combination of static and collisional quenching with a wide range of dynamic detection (1-105 µM) Linear relationship was observed in the concentration range 102-103 µM using fluorescence and 0.2 × 102-5 × 103 μM using absorbance spectroscopy with respective detection limits of 10.65 μM and 2.49 μM. The corresponding colorimetric and fluorometric changes can be easily monitored by the naked eye with a visual detection limit of 103 μM. AgNCs@PEI were further integrated within a hydrogel for developing a solid-state visual detection platform. Notably, the sensing response of the clusters towards Asc A remained unaltered even after hydrogel integration. Additionally, digital image analysis was adopted, which improved the sensitivity of instrument-free fluorescence detection of Asc A. Analysis by the developed sensor showed excellent recovery percentages of Asc A in spiked urine samples, which further underscores the practical applicability of the sensor.

Machine learning-assisted photoluminescent sensor array based on gold nanoclusters for the discrimination of antibiotics with test paper

Antibiotic residues accumulation in the environment endangers ecosystems and human health. There is an urgent need for a facile and efficient strategy to detect antibiotics. Here, we report a photoluminescent sensor array based on protein-stabilized gold nanoclusters (AuNCs) for the detection of two families of antibiotics, tetracyclines and quinolones. The nanoclusters were synthesized with bovine serum albumin (BSA) and ovalbumin (OVA), respectively. They had different interactions with seven kinds of antibiotics and exhibited diverse photoluminescence (PL) responses, which were analyzed by linear discriminant analysis and ExtraTrees algorithms. The sensor array performed well in both classification and quantification of seven antibiotics. And the quantitative results of all antibiotics obtained R2 of no less than 0.99 at 0-100 μM when using suitable regression models. Additionally, the sensor array was able to distinguish antibiotic mixtures and multiple interfering substances, and it also kept 100% classification accuracy in river water samples. Moreover, test paper assisted by a smartphone was applied for quick detection of antibiotics, with good performance in both HEPES buffer and river water. These studies reveal great potential for the point-of-use analysis of antibiotics in environmental monitoring.

A novel polyhedral oligomeric silsesquioxane nanohybrid fluorescent sensor designed based on an osmotic mechanism for specific detection and intelligent scavenging of magnesium ions

BACKGROUND

Mg2+ has long been recognized as one of the most vital cations due to its diverse physiological and pathological roles, making it indispensable in both biomedical and biological research. Organic fluorescent sensors are commonly employed for Mg2+ detection, but they often lack high selectivity and exhibit poor hydrophilicity, limiting their biomedical applications.

RESULTS

Herein, we introduced a novel organic-inorganic hybrid fluorescence sensor, PFHBS, constructed on the POSS nanoplatforms. The efficient connection between PEGylated POSS and the small molecule sensor FHBS through Click chemistry enhances the selectivity and reduces interference, making this chemical sensor ideal for the accurate detection of Mg2+. Furthermore, the incorporation of POSS amplifies the ligand field effect of FHBS, making it more conducive to Mg2+ capture. The modification of PEG chains enhances the sensor's amphiphilicity, facilitating efficient cell penetration and effective Mg2+ detection at the biological level.

SIGNIFICANCE

Finally, relying on spontaneous permeation, coupled with its strong ligand field effect and excellent cell permeability, the chemosensor demonstrates the capability to intelligently remove excess Mg2+ from the body. It has been successfully applied to mitigate renal overload resulting from acute Mg2+ poisoning.

Semiquantitative and visual detection of ferric ions in real samples using a fluorescent paper-based analytical device constructed with green emitting carbon dots

A simple and portable paper-based analytical device was developed for visual and semiquantitative detection of ferric ion in real samples using green emitting carbon dots (CDs), which were prepared via microwave method using sodium citrate, urea and sodium hydroxide as raw materials and then loaded on the surface of paper substrate. When Fe3+ exists, the green fluorescence of CDs was quenched and significant color change from green to dark blue were observed, resulting the visual detection of Fe3+ with a minimum distinguishable concentration of 100 μM. By analyzing the intensity changes of green channels of test paper with the help of smartphone, the semiquantitative detection was realized within the range of 100 μM to 1200 μM. The proposed paper-based analytical devices have great application prospects in on site detection of Fe3+ in real samples.

An enzymatic activity regulation-based clusterzyme sensor array for high-throughput identification of heavy metal ions

The accurate identification and sensitive quantification of heavy metal ions are of great significance, considering that pose a serious threat to environment and human health. Most array-based sensing platforms, to date, utilize nanozymes as sensing elements, but few studies have explored the application of the peroxidase-like activity of clusterzymes in identification of multiple analytes. Herein, for the first time, we developed a clusterzyme sensor array utilizing gold nanoclusters (AuNCs) as sensing elements for five heavy metal ions identification including Hg²⁺, Pb²⁺, Cu²⁺, Cd²⁺ and Co²⁺. The heavy metal ions can differentially regulate the peroxidase-like activity of AuNCs, and that can be converted into colorimetric signals with 3,3',5,5'-tetramethylbenzidine (TMB) as the chromogenic substrate. Subsequently, the generated composite responses can be interpreted by combining pattern recognition algorithms. The developed clusterzyme sensor array can identify five heavy metal ions at concentrations as low as 0.5 μM and their multi-component mixtures. Especially, we demonstrated the successful identification of multiple heavy metal ions in tap water and traditional Chinese medicine, with an accuracy of 100% in blind test. This study provided a simple and effective method for identification and quantification of heavy metal ions, rendering a promising technique for environmental monitoring and drug safety assurance.

Identification of multi-component metal ion mixtures in complex systems using fluorescence sensor arrays

The growing co-contamination of multiple metal ions seriously influences human health due to their synergistic and additive toxicological effects, whereas the rapid discrimination of multiple heavy metal ions in complex aquatic systems remains a major challenge. Herein, a high- throughput fluorescence sensor array was fabricated based on three gold nanoclusters (GSH-Au NCs, OVA-Au NCs, and BSA-Au NCs) for the direct identification and quantification of seven heavy metal ions (Pb²⁺, Fe³⁺, Cu²⁺, Co²⁺, Ag⁺, Hg²⁺ and As³⁺) from environmental waters without sample pretreatment other than filtration. At the detection system, three gold nanoclusters with various ligands possessed distinct binding capacities against metal ions and induced aggregation-induced fluorescence enhancement and quenching, resulting in a unique pattern of fluorescence variations. Meanwhile, integrated the collected fluorescence fingerprints with linear discriminant analysis (LDA) and hierarchical cluster analysis (HCA), a discrete database was obtained for the accurate recognition and sensitive detection of metal ions. Under the optimized conditions, the limit of detection (LOD) of the proposed fluorescence sensor array for metal ions detection at nM concentration level along with a satisfactory accuracy. Importantly, our study indicated that the fluorescence sensor array could be widely used as a general platform in environmental monitoring against multiple targets at low concentrations.

Fluorescent paper-based sensor integrated with headspace thin-film microextraction for the detection of acyclic N-nitrosamines following in situ photocatalytic decomposition

BACKGROUND

In this work, a novel analytical approach based on the photocatalytic decomposition of N-nitrosamines combined with headspace thin-film microextraction of the generated nitrogen oxides such as NO has been developed for the determination of the acyclic N-nitrosamine fraction in drinking water samples. A hydrophilic cellulose substrate modified with fluorescent silver nanoclusters (Ag NCs) was used both as extractant and sensing platform. A quenching effect of Ag NCs fluorescence occurs as the concentration of N-nitrosamines increases. Front-face fluorescence spectroscopy with a solid sample holder was employed for directly measuring the fluorescence quenching onto the cellulose substrate.

RESULTS

In order to achieve an optimal analytical response, different parameters involved in the photocatalytic reaction as well as those concerning the microextraction step were fully investigated. It is demonstrated that the photodegradation rate of cyclic N-nitrosamines at acidic pH is much lower than that of acyclic ones, which can be the basis for the determination of the later fraction in waters. Under optimal conditions, a detection limit for the acyclic N-nitrosamine fraction around 0.08 μg L^-1 using N-nitrosodimethylamine (NDMA) as model compound for calibration was obtained. Several drinking waters were spiked with acyclic N-nitrosamines showing recoveries in the range of 98-102% with a relative standard deviation of 3-4% (N = 3).

SIGNIFICANCE AND NOVELTY

N-nitrosamines generated as by-products during disinfection processes applied to water cause multiple adverse effects on human health being classified as potential human carcinogens. This study highlights the suitability of a fluorescent paper-based sensor for the rapid analysis of the acyclic N-nitrosamine fraction (i.e. the most abundant fraction) as a total index in drinking water, being useful as screening tool before exhaustive chromatographic analysis, which saves costs, time and reduces waste generation.

A novel fluorescent sensor array to identify Baijiu based on the single gold nanocluster probe

Baijiu occupies a vital position in Chinese food and China's market. Strict evaluation of Baijiu is highly demanded. In this study, we constructed a novel fluorescent sensor array based on the single glutathione-protected gold nanoclusters (AuNCs) probe for the detection of organic acids and Baijiu. The fluorescence of AuNCs was simply modulated by three metal ions (Cu²⁺, Mn²⁺, and Ag⁺), and formed new complexes as sensing elements. These four sensing elements responded variously to nine organic acids, and further chemometric analysis results allowed for the classification and quantification of acids. Moreover, the sensor array successfully identified 21 Baijiu samples of different brands among 11 aroma types. It could also distinguish Baijiu of different qualities as well as pure Baijiu from its adulterations and showed high selectivity among multiple interfering drinks. The results demonstrated that the AuNCs-based sensor array has considerable potential for quality monitoring of Baijiu.

Selective detection of manganese(II) ions based on the fluorescence turn-on response via histidine functionalized carbon quantum dots

Herein, water-soluble emissive carbon quantum dots (His-CQDs) were synthesized from pyrolysis of sodium citrate in the presence of histidine under hydrothermal conditions. The as-synthesized His-CQDs were characterized using Fourier transform infrared (FT-IR), fluorescence spectroscopy, dynamic light scattering (DLS), and transmission electron microscopy (TEM) techniques. The obtained His-CQDs display a strong emission peak at 534 nm when excited at 476 nm with a high quantum yield (61.8 %). The as-synthesized His-CQDs were applied as a new platform for highly selective determination of Mn(II) based on the fluorescence "turn-on" response with a limit of detection of 1.85 µg L^-1 (at 3σ) and a linear range of 3.50-35.5 µg L^-1 in aqueous solution. The sensing mechanism of the His-CQDs probe for the detection of Mn(II) was studied via density functional theory (DFT), FT-IR, and EDTA complexation methodology. In addition, His-CQDs were successfully applied to determine the accurate amounts of Mn(II) in whole blood control material. More importantly, the integrating such an efficient sensor with point-of-care technology can enable portable, easy-to-use, and rapid sensing systems for better biological and clinical applications.

Copper nanoclusters-based fluorescent sensor array to identify metal ions and dissolved organic matter

In recent years, the prevention and control of water pollution has received extensive attention. There is a need to develop simple and effective strategies for the rapid detection of metal ions and dissolved organic matter (DOM) in order to improve water quality. To this end, the first copper nanoclusters (CuNCs)-based fluorescent sensor array was done to identify 12 metal ions (Pb²⁺, Fe³⁺, Cu²⁺, Cd²⁺, Cr³⁺, Co²⁺, Ni²⁺, Zn²⁺, Ag⁺, Fe²⁺, Hg²⁺, and Al³⁺) and DOM (humic substances, lipids, fatty acids, amino acids, and lignans). The results revealed that CuNCs that were synthesized with polyethyleneimine (PEI), histidine (His), and glutathione (GSH) exhibited different binding abilities to metal ions and DOM. These unique fluorescence responses were analyzed using principal component analysis (PCA) and linear discriminant analysis (LDA) to identify metal ions and DOM in the buffer. The aforementioned 12 metal ions were classified at a limit concentration of 1.5 μM. Moreover, quantification of metal ions was achieved even at a low concentration of 0.83 μM (Zn²⁺). This array also worked well in the recognition of metal ions in tap water as well as distinguishing riverine and seawater samples of different regions, which was of great significance in environmental monitoring.

Ligand-protected nanoclusters and their role in agriculture, sensing and allied applications

Nano biotechnology, when coupled with green chemistry, can revolutionize human life because of the vast opportunities and benefits it can offer to the quality of human life. Luminescent metal nanoclusters (NCs) have recently developed as a potential research area with applications in different areas like medical, imaging, sensing etc. Recently these new candidates have proved to be beneficial in the food supply chain enabling controlled release of nutrients, pesticides and as nanosensors for the detection of contaminants and play roles in healthy food storage and maintaining food quality. An assortment of nanomaterials has been employed for these applications and reviews have been published on the use of nanotechnology in agriculture. Ligand-protected metal nanoclusters are a distinctive class of small organic-inorganic nanostructures that garnered immense research interest in recent years owing to their stability at specific "magic size" compositions along with tunable properties that make them promising candidates for a wide range of nanotechnology-based applications. This review tries to consolidate the recent developments in the area of ligand-protected nanoclusters in connection with the detection of pesticides, food contaminants, heavy metal ions and plant growth monitoring for healthy agricultural practices. Its antimicrobial activity to manage the microbial contamination is highlighted. The review also throws light on the various perspectives by which food production and allied areas will be transformed in future.

A new method for cartap detection with high sensitivity and selectivity based on the inner filter effect between GSH-Cu NCs and Au NPs

Herein, a novel and sensitive fluorescence method for cartap determination is established on the basis of the inner filter effect (IFE) of gold nanoparticles (Au NPs) on the fluorescence of glutathione protected Cu NCs (GSH-Cu NCs). In the presence of Au NPs, the fluorescence of GSH-Cu NCs was strongly quenched by the IFE because the absorption spectra of Au NPs overlap well with the emission spectra of GSH-Cu NCs. Upon addition of cartap, cartap could induce the aggregation of Au NPs whose absorption spectrum does not overlap with the emission spectrum of GSH-Cu NCs. Then, with the increase in cartap concentration, the IFE-decreased fluorescence was gradually recovered, realizing the fluorescence sensing of cartap. Under optimal conditions, the proposed method has a good linear relationship with cartap concentration in the range of 7-100 nM, and the detection limit is 3.34 nM. In addition, satisfactory results were obtained for cartap analysis using tap water and cabbage as real samples, which demonstrated that the method as-developed would have great practical application prospects.

Silver-enhanced fluorescence of bimetallic Au/Ag nanoclusters as ultrasensitive sensing probe for the detection of folic acid

Folic acid (FA) is the natural form of water-soluble vitamins widely found in most plants and animal products and its deficiency leads to several human body abnormalities. The advancements of metal nanoclusters are highly increasing due to their molecule-like optical properties and attractive applications. Because of increasingly demand of noble metal nanoclusters as sensing templates, different synthesis methods have been developed for facile synthesis of noble metal nanoclusters. Herein, red-emitting fluorescent bovine serum albumin (BSA)-capped Au-Ag bimetallic NCs are facilely synthesized through green one-pot synthetic approach. The effect of silver on the fluorescence properties of Au NCs was investigated and it was found that introduction of silver can enhance the fluorescence intensity. The fluorescence intensity of the as-prepared Au-Ag nanoclusters gets quenched in the presence of folic acid in an aqueous medium and it was used as ultrasensitive sensing probe for FA detection. The developed Au-Ag NCs-based sensing probe shows linear response in the wide range of 0-100 μM and the detection limit is as low as 0.47 nM. Its applicability has also been confirmed successfully in real human serum, urine and FA tablet samples. Due to the high stability, sensitivity and selectivity, the developed bimetallic cluster sensing system is highly promising to be applied in the pharmaceutical and clinical laboratories.

Four-channel fluorescent sensor array based on various functionalized CdTe quantum dots for the discrimination of Chinese baijiu

As a special carrier of traditional Chinese culture, baijiu is rich in terms of types and ingredients. Its quality analysis and control are always important and complex issues that urgently need reliable evaluation methods. In this study, four different modified CdTe quantum dots (QDs) were used to characterize their sensing performance to various baijiu. A sensor array was then constructed through the complementary properties of differential fluorescence signals. To achieve an accurate and rapid evaluation of different baijiu types, a linear discriminant analysis (LDA) was introduced to extract and process spectral information. And the array was able to distinguish commercial baijiu samples with different aroma-types, brands, qualities and storage years with a recognition rate of 100%. In addition, according to the heat map, the organic acids in baijiu were shown to be the main components causing the fluorescence change through electron transfer (hydrogen bond) and resonance energy transfer among QDs and acids. Furthermore, using the partial least squares regression (PLSR) model, five representative organic acids were accurately quantified with a quantitative range of 10 μmol/L-80 μmol/L with a high selectivity. This QDs fluorescence sensing strategy provides an accurate, simple, and fast baijiu sensing method, which provides a potential use for on-line baijiu monitoring.