Fluorescent Sensor Array Research Articles

Rapid and accurate identification of multiple metal ions using a bispyrene‐based fluorescent sensor array with aggregation‐induced enhanced emission property

AbstractMultiple metal ions are traditionally detected using inductively coupled plasma mass spectrometry (ICP‐MS) and atomic fluorescence spectrometry. Although these methods are sensitive and accurate, they depend on complex instruments and require highly trained operators, making low costly rapid detection challenging. It is urgent to develop a convenient, rapid and sensitive method to detect multiple metal ions. Herein, we designed a bispyrene derivative (BP) with aggregation‐induced enhanced emission (AIEE) property to construct a high fluorescent sensor array to realize the effective identification of four metal ions (Fe3+, Cu2+, Co2+ and Cd2+). The differential coordination capability between metal ions and BP with the aid of acetate ions resulted the possibility of array‐based sensing. The four heavy metal ions could be immediately classified in the concentration of 100 nM. The limit of detection (LOD) of Fe3+, Cu2+, Co2+, and Cd2+ were as low as 16.2, 21.8, 51.4, and 25.9 nM, respectively. Furthermore, the sensor array was applied for identification multiple heavy metal ions in environmental samples and iron ion in rat serums with identified of 100%. The sample consumption as low as 2 µL for each detection and the results could be extracted by smartphones under ultraviolet lamps. It provided a rapid, sensitive, low‐cost, and on‐site multiple metal ions detection method.

Multichannel sensor array based on carbon dots and metal ions system for physiological phosphates sensing

The detection of physiological phosphates is crucial for elucidating metabolic processes and related diagnoses of diseases. Herein, a carbon dots (CDs) modulated multichannel fluorescent sensor array was proposed for detecting and distinguishing physiological phosphates. In this sensor, three metal ions (Nd3+, Ag+, and Fe3+) with significantly different binding forces with phosphate ions were selected to trigger fluorescence quenching of three CDs (BCDs, GCDs, and RCDs). Upon adding physiological phosphates, the fluorescence intensity of CDs changed. Depending on the discrepancy in the content of phosphate units in different physiological phosphates, the sensor array realized the detection and differentiation of five physiological phosphates related to adenosine triphosphate (ATP) hydrolysis, and has good anti-interference ability, which can realize the differentiation of physiological phosphates in complex serum samples.

Luminescent Metal-Organic Framework-Based Fluorescent Sensor Array for Screening and Discrimination of Bisphenols.

Extensive applications of bisphenols in industrial products have led to their release into aquatic environments, causing a great threat to human health due to their endocrine-disrupting effects, whereas existing methods are difficult to implement the rapid and high-throughput detection of multiple bisphenols. To circumvent this issue, we constructed a sensor array using two luminescent metal-organic frameworks (LMOFs) (Zr-BUT-12 and Ga-MIL-61) for the rapid discrimination of six bisphenol contaminants (BPA, BPS, BPB, BPF, BPAF, and TBBPA). Wherein, Zr-BUT-12 and Ga-MIL-61 exhibited different fluorescence-emission properties and good luminescent stability. Interestingly, bisphenols with different structures had diverse quenching effects on the fluorescence intensity of Zr-BUT-12 and Ga-MIL-61 via the adsorptive interaction, resulting in unique fluorescent fingerprints. Based on pattern recognition methods, different bisphenols were successfully identified, with the limit of detection in the range of 1.59-16.7 ng/mL for six bisphenols. More importantly, the developed sensor array could be effectively utilized for distinguishing different ratios of mixed bisphenols, which was further applied for bisphenol discrimination in real water samples. Consequently, our finding provides a promising strategy for the simultaneous recognition of multiple bisphenols, which encourages the development of a sensor array for the detection of multiple contaminants in environmental monitoring and food safety.

A Diboronic Acid-Based Fluorescent Sensor Array for Rapid Identification of Lonicerae Japonicae Flos and Lonicerae Flos.

Lonicerae japonicae flos (LJF) and Lonicerae flos (LF) are traditional Chinese herbs that are commonly used and widely known for their medicinal properties and edibility. Although they may have a similar appearance and vary slightly in chemical composition, their effectiveness as medicine and their use in clinical settings vary significantly, making them unsuitable for substitution. In this study, a novel 2 × 3 six-channel fluorescent sensor array is proposed that uses machine learning algorithms in combination with the indicator displacement assay (IDA) method to quickly identify LJF and LF. This array comprises two coumarin-based fluorescent indicators (ES and MS) and three diboronic acid-substituted 4,4'-bipyridinium cation quenchers (Q1-Q3), forming six dynamic complexes (C1-C6). When these complexes react with the ortho-dihydroxy groups of phenolic acid compounds in LJF and LF, they release different fluorescent indicators, which in turn causes distinct fluorescence recovery. By optimizing eight machine learning algorithms, the model achieved 100% and 98.21% accuracy rates in the testing set and the cross-validation predictions, respectively, in distinguishing between LJF and LF using Linear Discriminant Analysis (LDA). The integration of machine learning with this fluorescent sensor array shows great potential in analyzing and detecting foods and pharmaceuticals that contain polyphenols.

A Supramolecular Fluorescent Sensor Array Composed of Conjugated Fluorophores and Cucurbit[7]uril for Bacterial Recognition.

Bacterial infections have emerged as a significant contributor to global mortality and morbidity rates. Herein, we introduce a dual fluorescence "turn-on" supramolecular sensor array composed of three assembled complexes (C1-C3), formed from three positively charged fluorophores (A1-A3) and one cucurbit[7]uril (CB[7]). The ability of this three-element array to simultaneously recognize 10 bacterial species within just 30 s was remarkable, boasting an impressive 100% accuracy. Additionally, the array excelled at distinguishing among various bacterial mixtures and enabled the quantitative detection of common bacterial strains. Notably, it has been skillfully applied to differentiate 10 bacterial samples in urine, achieving excellent differentiation and showcasing promising potential for medical diagnostic applications.

A rapid and accurate fluorescent sensor array based on lanthanide metal-organic framework for identification and determination of perfluorinated compounds

Perfluorinated compounds (PFCs), as an important class of environmental pollutants, have chemical and structural similarities that make their detection a great technical challenge. This study synthesized three species of metal-organic frameworks (MOFs) using different lanthanide metal ions or organic ligands, which were integrated into a fluorescent sensor array. This innovative approach offers a straightforward, rapid, and precise detection strategy for PFCs. Different ionization properties and fluorinated hydrophobic tails of PFCs lead to different electrostatic attraction and hydrophobic effects between PFCs and sensing elements, which become the basis for differential sensing. Furthermore, the fluorescence signal is more convenient to collect, making the sensor array simple to complete the identification. Combined with pattern recognition methods, the array successfully identified seven kinds of PFCs and mixtures with a classification accuracy of 100 % and a detection limit as low as 51 nM. Finally, the utility of the sensor array in river water sample analysis was verified. The strategy provides an effective method for identifying and determining PFCs and offers new opportunities for developing sensor arrays based on lanthanide MOFs.

Fluorescence array sensor based on lanthanide complex for pattern recognition detection of fluoroquinolone antibiotics

Fluoroquinolone antibiotics, a class of animal and human useful antibiotics, are widely utilized in numerous fields including biomedical science, animal husbandry, and aquatic finfish farming. Its high demand and wide application have directly or indirectly led to substantial consumption and discharge of antibiotics, affecting not only the environment but also endangering human health through bioaccumulation. Hence, rapid and precise detection of trace antibiotics in water, food, and biological samples is critically important. This research synthesized Tb3+/Eu3+ complexes with dual emission centers, and a fluorescence sensor array was constructed with the fluorescence intensity ratio F1/F2 of the two emission centers as a signal. Different sensitization effect of fluoroquinolone antibiotics towards lanthanide complexes aided in differentiating five fluoroquinolone antibiotics from two others. Additionally, the sensor array can effectively detect fluoroquinolone antibiotics in real samples, suggesting its reliability and practicality of complex sample analysis. The excellent qualitative and quantitative analysis ability of this strategy for fluoroquinolone antibiotics offers a novel perspective for antibiotic residue detection, showcasing a new opportunity for lanthanide complex application in sensor arrays.

Covalent Organic Frameworks-Based Fluorescence Sensor Array and QSAR Study for Identification of Energetic Heterocyclic Compounds.

The accurate identification of energetic heterocyclic compounds (EHCs) is of great significance in munition assessment, environmental monitoring, and biosafety but remains largely underexplored. Herein, a covalent organic frameworks-based fluorescence sensor array (COFx sensor array) for efficient screening of EHCs is reported. The topologies of the COFs were rationally designed by modulating the pore sizes and linkage strategies to achieve the simplified sensor array. Eighteen EHC representatives, including single-, dual-, and three-ring EHCs with multivariate substructures, were successfully discriminated ranging from 10 μM to 1 mM. The sensor array showed robust selectivity against a wide range of interferences. The quantitative structure-activity relationship (QSAR) analysis has been conducted for the mechanistic study of the sensor array. Three multiple linear regression models have been established using molecular descriptors to evaluate and predict Stern-Volmer coefficient values, achieving explicit correlation between EHC structures and the signal outputs of the sensor array. Five molecular descriptors are retained to reveal the governing factors of the sensor array resolution. The QSAR analysis facilitates the design and development of the COFx sensor array, offering a new approach for customized multivariate analysis.

A Label-Free Sensor Array Based on Carbon Quantum Dots for Detection of α-Synuclein Oligomers in Saliva.

Salivary oligomeric α-synuclein (α-Syn) has been introduced as a promising biomarker for the diagnosis of Parkinson's disease. Herein, a fluorescence sensor array based on three carbon quantum dots (CQDs) with different surface functional groups was developed for the identification and quantification of salivary α-Syn oligomers. Each of the CQDs generated a different fluorescence response to the target analyte, and the responses were analyzed by NPLS-DA to create a unique response pattern for the target analyte. The developed three-element sensor array showed a linear response to α-Syn oligomers in the range of 0.5-32 μg/mL and a detection limit (LOD) of 0.5 μg/mL, with a cross-validation accuracy of 92% in aqueous solution. The sensor array could detect the analyte in a mixture of different proteins and in the complex medium of saliva, with the LOD of 0.3 μg/mL indicating the massive potential of CQD arrays for developing sensitive, simple, inexpensive, and label-free sensing platforms.

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 single-component sensor array to detect multiple antibiotics via dual-emission chlorophyll carbon dots

In this study, dual-emission carbon dots (DE-CDs) were fabricated using a straightforward one-step hydrothermal synthesis with natural chlorophyll as the carbon precursor. These DE-CDs not only preserve the porphyrin structure of chlorophyll, exhibiting notable fluorescence at 682 nm, but they also display the characteristic fluorescence emission of conventional CDs at 450 nm. Leveraging the unique dual-emission properties of DE-CDs, we have engineered a single-component fluorescent sensor array for the high-throughput detection of antibiotics, which are emerging contaminants in water. The fluorescence responses (F450, F682, and the F450/F682 ratio) of the DE-CDs toward various antibiotics were analyzed using principal component analysis (PCA), enabling the facile differentiation of multiple antibiotics with good reproducibility achieved in real water samples. This innovative DE-CDs approach eliminates the need for multiple sensing probes and offers a practical concept for the creation of single-component sensing platforms.

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.

A fluorescent sensor array based on a single cucurbit[5]uril-truxene probe for simultaneous identification of five heavy metal ions.

There is a need to develop simple and effective strategies for the rapid detection of heavy metal ions (HMIs) in order to protect the environment and human health. A simple fluorescent sensor array based on a single cucurbit[5]uril-truxene probe was proposed to simultaneously identify five HMIs (Pb2+, Cu2+, Ag+, Fe2+ and Fe3+). This probe was synthesized using monohydroxyl cucurbit[5]uril and monobromohexyl truxene by a substitution reaction between them. It could be observed that the fluorescence response of this synthesized probe to HMIs was closely related to the pH of the aqueous solution, exhibiting different fluorescence intensities at pH 3.0, 7.0, and 9.0. Based on this phenomenon, a fluorescent sensor array based on a single cucurbit[5]uril-truxene probe was then constructed by simply altering the pH in the sensor element. These unique fluorescence responses were analyzed using linear discriminant analysis (LDA) to identify metal ions. A concentration limit classification of 0.1 μM was applied to the above five HMIs. Moreover, the quantification of metal ions was implemented even at low concentrations of 48-121 nM. This array showed good results in the recognition of metal ions in real water samples (lake water and tap water samples), which shows its broad application prospects in many fields, including monitoring of the environmental water quality and so on.

A supramolecular fluorescence sensor array for the differentiation of multiple anions and prediction of iodine in artificial urine using machine learning.

The simultaneous discrimination and detection of multiple anions in an aqueous solution has been a major challenge due to their structural similarity and low charge radii. In this study, we have constructed a supramolecular fluorescence sensor array based on three host-guest complexes to distinguish five anions (F-, Cl-, Br-, I-, and ClO-) in an aqueous solution using anionic-induced fluorescence quenching combined with linear discriminant analysis. Due to the different affinities of the three host-guest complexes for each anion the anion quenching efficiency for each host-guest complex was likewise different, and the five anions were well recognized. The fluorescence sensor array not only distinguished anions at different concentrations (0.5, 10, and 50 µM) with 100% accuracy but also showed good linearity within a certain concentration range. The limit of detection (LOD) was < 0.5 µM. Our interference study showed that the developed sensor array had good anti-interference ability. The practicability of the developed sensor array was also verified by the identification and differentiation of toothpaste brands with different fluoride content and the prediction of the iodine concentration in urine combined with machine learning.

Calixarene-Based Supramolecular Sensor Array for Pesticide Discrimination.

The identification and detection of pesticides is crucial to protecting both the environment and human health. However, it can be challenging to conveniently and rapidly differentiate between different types of pesticides. We developed a supramolecular fluorescent sensor array, in which calixarenes with broad-spectrum encapsulation capacity served as recognition receptors. The sensor array exhibits distinct fluorescence change patterns for seven tested pesticides, encompassing herbicides, insecticides, and fungicides. With a reaction time of just three minutes, the sensor array proves to be a rapid and efficient tool for the discrimination of pesticides. Furthermore, this supramolecular sensing approach can be easily extended to enable real-time and on-site visual detection of varying concentrations of imazalil using a smartphone with a color scanning application. This work not only provides a simple and effective method for pesticide identification and quantification, but also offers a versatile and advantageous platform for the recognition of other analytes in relevant fields.

Design of microfluidic fluorescent sensor arrays for real-time and synchronously visualized detection of multi-component heavy metal ions

The majority of the environmental heavy metal ions exist in the form of multi-components, and the current single-to-single rapid detection methods are unable to meet the needs of simultaneous multi-component detection. Here, we have designed a microfluidic fluorescence sensor array by combining microfluidic sensing and organic fluorescent switches for the real-time and simultaneous visual detection of multi-component heavy metal ions. A series of “light-up” organic molecular probes was designed and synthesized, exhibiting a strong ability to bind heavy metal ions and resulting in the opening of probe fluorescence. Meanwhile, we design microfluidic sensor plate, the patterned path of the microfluidic plate has drainage channel wall and 2.70° downward slope, which can enable the samples to quickly reach the detection area. By loading organic molecular probes into the detection area, the microfluidic sensor array achieves simultaneous detection of four heavy metal ions. Combined with intelligent terminal, read and analyze the RGB color mode (RGB) results of detection, obtain quantitative information. The microfluidic fluorescence sensor array developed here can meet the requirements for in situ and semi-quantitative detection of a range of heavy metal ions with a low detection limit, fast reaction speed, and without the need for pretreatment. It represents a novel engineering technology approach for real-time detection of multi-components in the environment.

A General Strategy for Food Traceability and Authentication Based on Assembly-Tunable Fluorescence Sensor Arrays.

Food traceability and authentication systems play an important role in ensuring food quality and safety. Current techniques mainly rely on direct measurement by instrumental analysis, which is usually designed for one or a group of specific foods, not available for various food categories. To develop a general strategy for food identification and discrimination, a novel method based on fluorescence sensor arrays is proposed, composed of supramolecular assemblies regulated by non-covalent interactions as an information conversion system. The stimuli-responsiveness and tunability of supramolecular assemblies provided an excellent platform for interacting with various molecules in different foods. In this work, five sensor arrays constructed by supramolecular assemblies composed of pyrene derivatives and perylene derivatives are designed and prepared. Assembly behavior and sensing mechanisms are investigated systematically by spectroscopy techniques. The traceability and authentication effects on several kinds of food from different origins or grades are evaluated and verified by linear discriminant analysis (LDA). It is confirmed that the cross-reactive signals from different sensor units encompassing all molecular interactions can generate a unique fingerprint pattern for each food and can be used for traceability and authentication toward universal food categories with 100% accuracy.

Functionalized carbon quantum dots fluorescent sensor array assisted by a machine learning algorithm for rapid foodborne pathogens identification

Food safety is a global concern, and conventional methods for detecting foodborne bacteria, such as polymerase chain reaction and enzyme-linked immunosorbent assay, often involve time-consuming processes, specialized equipment, or specific recognition of particular bacterial strains. There is an urgent need for more efficient and convenient detection methods for foodborne pathogens. This study addresses this need by introducing an easily constructed fluorescent sensor array for the identification of various foodborne bacteria. The sensor array comprises carbon quantum dots (CQDs) functionalized with ampicillin, polymyxin, and gentamicin, each exhibiting different affinities for binding with specific bacteria. Leveraging machine learning algorithms, the proposed sensor array enables rapid, accurate, and highly sensitive identification of foodborne pathogens. This approach offers a convenient solution for the development of rapid, accurate, and hypersensitive detection methods for multiple bioactive samples. In summary, the fluorescent sensor array in this study holds promise for advancing the field of foodborne bacteria detection.

Enantiopure Corral[4]BINOLs as Ultrastrong Receptors for Recognition and Differential Sensing of Steroids.

The precise recognition and sensing of steroids, a type of vital biomolecules, hold immense practical value across various domains. In this study, we introduced corral[4]BINOLs (C[4]BINOLs), a pair of enantiomeric conjugated deep-cavity hosts, as novel synthetic receptors for binding steroids. Due to the strong hydrophobic effect of their deep nonpolar, chiral cavities, the two enantiomers of C[4]BINOLs demonstrated exceptionally high recognition affinities (up to 1012 M-1) for 16 important steroidal compounds as well as good enantioselectiviy (up to 15.5) in aqueous solutions, establishing them as the most potent known steroid receptors. Harnessing their ultrahigh affinity, remarkable enantioselectivity, and fluorescence emission properties, the two C[4]BINOL enantiomers were employed to compose a fluorescent sensor array which achieved discrimination and sensing of 16 structurally similar steroids at low concentrations.

Enantiopure Corral[4]BINOLs as Ultrastrong Receptors for Recognition and Differential Sensing of Steroids

AbstractThe precise recognition and sensing of steroids, a type of vital biomolecules, hold immense practical value across various domains. In this study, we introduced corral[4]BINOLs (C[4]BINOLs), a pair of enantiomeric conjugated deep‐cavity hosts, as novel synthetic receptors for binding steroids. Due to the strong hydrophobic effect of their deep nonpolar, chiral cavities, the two enantiomers of C[4]BINOLs demonstrated exceptionally high recognition affinities (up to 1012 M−1) for 16 important steroidal compounds as well as good enantioselectiviy (up to 15.5) in aqueous solutions, establishing them as the most potent known steroid receptors. Harnessing their ultrahigh affinity, remarkable enantioselectivity, and fluorescence emission properties, the two C[4]BINOL enantiomers were employed to compose a fluorescent sensor array which achieved discrimination and sensing of 16 structurally similar steroids at low concentrations.