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Imine based positional isomers (8E)-N-(4-((E)-(perfluorophenylimino)methyl)benzylidene)-2,3,4,5,6-pentafluorobenzenamine, L and (10E)-N-(3-(E-Perfluorophenylimino)methyl)benzylidene)-2,3,4,5,6-pentafluorobenzenamine, L1 have been designed, and synthesized by functionalizing two electron deficient aromatic moieties at the para-para'/ortho-ortho' positions in the phenyl core of the L and L1 respectively. The responses of L and L1 towards various anionic species are examined. The positional isomers L and L1 differs not only by showing distinguishable color change upon addition of anions but also differentiates themselves by the way of self-assembling together upon binding with cyanide anion. The naked-eye colorimetric experiments, UV-Vis, Nuclear Magnetic Resonance, and Infra-Red spectroscopic analyses reveal that the isomer L binds fluoride anion through 2:1 stoichiometry ratio. Unlike fluoride complex, the isomer L form aggregates while binding with cyanide ion. On the other hand, isomer L1 does not show any instant color change upon additions of any anion. Interestingly, after thirty minutes, only the color of the cyanide complex is turned into dark brown. While analyzing the spectroscopic results of cyanide complex of L1, it is found that the cyanide complex begins to decompose and finally it is completely decomposed within 30 min. This unprecedented phenomenon about the colorimetric sensing of cyanide and destruction of cyanide complex with respect to time has not been reported in the literature yet. To the best of our knowledge this is the first example of study of sensing controlling the selectivity, mode of binding, self-aggregating and degradation properties of anionic complexes under the influence of positional isomeric effects. This present investigation provides simple and effective strategy to construct the sensor molecules with tunable binding properties in terms of easy to prepare as well as easy to use as a colorimetric sensor. _____________________________________________________________________________________________________.

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Three new chromogenic receptors have been synthesized with the primary objective of facilitating the selective recognition of PO43¯and CO32¯ ions in an organo-aqueous medium. R1 and R2 exhibit an extraordinary detection limit aligning with both EPA and WHO guidelines. R1 shows LOD of 0.135 ppm for PO43¯ and 0.175 ppm for CO32¯, while R2 sets forth a LOD of 0.427 ppm for PO43¯ and 0.729 ppm for CO32¯. The binding mechanism involves intramolecular charge transfer (ICT) band are substantiated by comprehensive studies that include UV-Vis titration, 1H-NMR titration, DFT studies and electrochemical studies. Chemosensors were employed in the formulation of logic gate, the fabrication of a paper strip test kit and its application in RGB color sensor device.

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MicroRNAs (miRNAs) play an important role in the process of heart failure (HF) and are emerging biomarkers that can be used for the auxiliary diagnosis of HF. However, it is very challenging to accurately analyze the expression levels of trace miRNAs in complex clinical samples. Here, we developed an enzyme-free colorimetric sensor for the ultrasensitive detection of miRNA-423-5p (HF-associated miRNA) based on three-dimensional DNA walkers constructed from functional nucleic acids and gold nanoparticles (AuNPs). DNAzyme with cleavage activity was specifically activated by miRNA-423-5p to sustainably cleave the substrate, thereby releasing the trigger sequence to initiate the subsequent mismatched catalytic hairpin assembly (MCHA) cycle. Then, as the MCHA cycle proceeded to continuously expose the G-quadruplex (GQ) sequence, the sequence bound with hemin to form a large amount of GQ/hemin DNAzyme on the surface of the AuNPs, which rapidly catalyzed the chromogenic oxidation of 3,3',5,5'-tetramethylbenzidine to yield an amplified colorimetric signal readout. The colorimetric sensor exhibited an ultralow detection limit (32 fM), showed excellent specificity and performed well in serum samples. The sensor was applied to detect miRNA-423-5p in clinical plasma samples from healthy individuals and HF patients, and the results revealed its good clinical application in HF diagnosis. Thus, the developed colorimetric sensor provides a convenient detection tool for early screening and diagnosis of HF, as well as for pathophysiological studies.

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A facile and efficient detection method is required to address the potential health risks of ketoprofen (KP) in animal-derived foods. Herein, we integrated molecularly imprinted polymers (MIPs) with Cu-doped Fe3O4 nanozymes (Fe3O4-Cu) to develop a selective colorimetric sensor for KP detection. Chitosan and glutaraldehyde were used as functional monomers and cross-linkers to fabricate proposed the MIPs@Fe3O4-Cu. On KP addition, it was specifically captured by the imprinted cavities, thereby blocking the channels between chromogenic substrates and Fe3O4-Cu. Based on this rationale, a selective colorimetric sensor utilizing MIPs@Fe3O4-Cu was established, exhibiting a linear range of 0.25-100 µM and a detection limit of 0.073 µM. The developed method was validated through its application in milk samples, yielding satisfactory recoveries with low relative standard deviations. This efficient and selective colorimetric sensor holds immense significance for KP detection in complex samples.

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Lu'an Gua Pian (LAGP) tea is one of the most famous green teas in China. The quality of green tea is related to its picking periods, especially the green tea before Qingming Festival (usually April 6th) is highly praised as precious in the market. In this work, a simple and cheap indicator displacement colorimetric sensor array combined with smartphone was developed to rapidly identify LAGP picked during different picking periods. First, the chemical component contents of LAGP picked before and after Qingming Festival were analyzed. Second, a well-designed colorimetric sensor array was proposed based on the tea component contents differences. Finally, machine learning was used to process the array data taken by a smartphone. By comparison, the accuracy of the best model for the prediction set was 97%. Meanwhile, the multi-channel advantages of the sensing array were demonstrated by an ablation experiment. In addition, the method achieved an AGREE analysis score of 0.88, indicating that it was environmental-friendly.

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Chinese oolong tea is famous for its rich and diverse aromas, which is an important indicator for sensor quality evaluation. To accurately and rapidly evaluate sensory quality, a novel colorimetric sensor array (CSA) was developed to detect volatile organic compounds (VOCs) in oolong tea. We further explored the binding mechanism between colorimetric dyes that trigger changes in charge transfer and visible color changes. Based on this, we modified and optimized the CSA to improve the sensitivity by 17.1-234.9% and the stability by 8.7-33.3%. The study also assessed the effectiveness of this method by comparing two linear and two non-linear classification models, with the support vector machine (SVM) model achieving the highest accuracy, identifying different flavor intensity and grades with rates of 100% and 95.83%, respectively. These findings sufficiently demonstrated that the novel CSA, integrated with the SVM model, has promising potential for predicting the sensory quality of oolong tea.

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Per- and polyfluoroalkyl substances (PFASs) are emerging contaminants detected ubiquitously and have negative impacts on human health and ecosystem; thus, developing in-situ sensing technique is important to ensure safety. Herein, we report a novel colorimetric-based sensor with perfluoroalkyl receptor attached to citrate coated gold nanoparticles (Citrate-Au NPs) that can detect several PFASs including perfluorocarboxylates with different chain lengths (PFHxA, PFOA, PFNA, PFDA), perfluorooctanoic sulfonate (PFOS), and perfluorooctanoic phosphonate (PFOPA). The sensor detects PFASs utilizing fluorous interaction between PFASs and the perfluoroalkyl receptor of Citrate-Au NPs in a solution at a fixed salt concentration, inducing changes in nanoparticle dispersity and the solution color. The rate of spectrum shift was linearly dependent on PFASs concentrations. Citrate-Au NPs with size between 29 - 109 nm were synthesized by adjusting citrate/Au molar ratios, and 78 nm showed the best sensitivity to PFOA concentration (with level of detection of 4.96 µM). Citrate-Au NPs only interacted with PFASs with perfluoroalkyl length > 4 and not with non-fluorinated alkyl compound (nonanoic acid). The performance of Citrate-Au NP based sensor was strongly dependent on the chain length of the perfluoroalkyl group and the head functional group; higher sensitivity was observed with longer chain over shorter chain, and with sulfonate functional group over carboxylate and phosphonate. The sensor was tested using real water samples (i.e., tap water, filtered river water), and it was found that the sensor is capable of detecting PFASs in these conditions if calibrated with the corresponding water matrix. While further optimization is needed, this study demonstrated new capability of Citrate-Au NPs based sensor for detection of PFASs in water.

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A critical bottleneck in sensor technology is the rapid and precise detection of specific analytes in complex matrices, hindering advancements in environmental monitoring, healthcare, and industrial process control. This study addresses this challenge by introducing a novel composite hydrogel sensor designed for rapid and selective detection of ethanol and barium ions (Ba2+) in aqueous environments. The sensor integrates interpenetrating network (IPN) hydrogels with embedded colloidal photonic crystals (CPCs), synthesized via a solution-based polymerization approach. This innovative configuration allows CPCs to dynamically adjust their photonic bandgap in response to environmental changes, manifesting as a visible, colorimetric shift. This response stems from the synergy between the mechanical properties of the IPN hydrogel and the optical sensitivity of CPCs. Upon exposure to analytes such as ethanol and Ba2+, the sensor exhibits a rapid and reversible color transition that is directly proportional to their concentration. Notably, ethanol (0 vol%-80 vol%) and Ba2+ (5-17.5 mM) induce a distinct blueshift in the photonic bandgap and trigger a color change from red-orange to green due to the alteration in the swelling behavior of the IPN hydrogel, affecting its lattice constant. The IPN hydrogel-CPC composite demonstrates exceptional operational stability and facilitates rapid detection, making it ideal for on-site applications without the need for complex equipment. These characteristics make the composite hydrogel sensor a promising candidate for environmental monitoring, industrial process control, and public health diagnostics, paving the way for the development of next-generation responsive sensor materials.

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Achieving rapid, cost effective, and intelligent identification and quantification of flavonoids is challenging. For fast and uncomplicated flavonoid determination, a sensing platform of smartphone-coupled colorimetric sensor arrays (electronic noses) was developed, relying on the differential competitive inhibition of hesperidin, nobiletin, and tangeretin on the oxidation reactions of nanozymes with a 3,3',5,5'-tetramethylbenzidine substrate. First, density functional theory calculations predicted the enhanced peroxidase-like activities of CeO2 nanozymes after doping with Mn, Co, and Fe, which was then confirmed by experiments. The self-designed mobile application, Quick Viewer, enabled a rapid evaluation of the red, green, and blue values of colorimetric images using a multi-hole parallel acquisition strategy. The sensor array based on three channels of CeMn, CeFe, and CeCo was able to discriminate between different flavonoids from various categories, concentrations, mixtures, and the various storage durations of flavonoid-rich Citri Reticulatae Pericarpium through a linear discriminant analysis. Furthermore, the integration of a "segmentation-extraction-regression" deep learning algorithm enabled single-hole images to be obtained by segmenting from a 3 × 4 sensing array to augment the featured information of array images. The MobileNetV3-small neural network was trained on 37,488 single-well images and achieved an excellent predictive capability for flavonoid concentrations (R2 = 0.97). Finally, MobileNetV3-small was integrated into a smartphone as an application (Intelligent Analysis Master), to achieve the one-click output of three concentrations. This study developed an innovative approach for the qualitative and simultaneous multi-ingredient quantitative analysis of flavonoids.

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Smart packaging material capable of real-time monitoring of food freshness is essential for ensuring food safe. At present, colorimetric ammonia-sensing smart film often possesses issues with complicated production, high cost, and inferior long-term colour stability. Herein, Zinc­copper bimetallic organic framework (ZnCu-BTC, BTC = 1,3,5-benzenetricarboxylate acid) nanorods with colorimetric ammonia-responsiveness were synthesized by adopting facile aqueous solution method, which were then explored as nano inclusions in potato starch/polyvinyl alcohol (PS/PVA) composite film towards developing high-performance smart packaging material. The results demonstrated that the introduction of ZnCu-BTC nanorods within PS/PVA brought about remarkable improvement in blend compatibility, accompanied by a boost in tensile strength to 47.2 MPa, as well as enhanced ultraviolet (UV) blocking efficacy (over 95.0 %). Additionally, the barrier properties of PS/PVA film against water vapor and oxygen were fortified due to the addition of ZnCu-BTC. More importantly, the developed PS/PVA/ZnCu-BTC nanocomposite film displayed satisfactory antibacterial activity (over 99 %) against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus), favorable colorimetric ammonia-sensing ability, and long-term colour stability. The ZnCu-BTC incorporated PS/PVA nanocomposite film could grant real-time detection of prawn freshness decline via remarkable colour change, indicating vast promise for smart food packaging applications.

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The detection of ammonia levels in blood is critical for diagnosing and monitoring various medical conditions, including liver dysfunction and metabolic disorders. However, traditional diagnostic methods are slow and cumbersome, often involving multiple contact-based steps such as ammonia separation in alkali conditions followed by distillation or microdiffusion, leading to delays in diagnosis and treatment. Herein, we developed a colorimetric assay capable of rapid detection of ammonia in whole blood or plasma samples, utilizing 2,2,6,6-tetramethylpiperidine 1-oxyl (TEMPO)-oxidized cellulose nanocrystals (TCNC) coupled with gold nanoparticles (AuNPs). The basis of our assay relies on either (i) the interaction between the carboxylate group (-COO) of TEMPO and ammonium ions or (ii) the manipulation of AuNPs surface plasmon resonance (SPR) through the formation of Au(NH3)43+, which displaces a redox mediator, resazurin, resulting in observable multicolor displays at various concentrations of ammonia. The colorimetric assay exhibits a wide linear detection range for dissolved NH4+ (0.1-37 µM) with a low limit of detection (LOD) of 0.1 µM. Additionally, it effectively measures NH3(g) concentrations in the range of 0.5-144 µM. The fabricated electrochemical nose (E-nose) device demonstrates excellent analytical performance for plasma ammonia sensing (0.05-256 µM). Experimental results demonstrate a linear detection range suitable for clinical applications, with excellent correlation to standard laboratory methods, offering a practical solution for point-of-care (PoC) testing. We anticipate that this approach can be applied broadly to improve patient monitoring and treatment by providing immediate and accurate ammonia measurements in a clinical setting.

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Accurate assessment of Total Antioxidant Capacity (TAC) in food is crucial for evaluating nutritional quality and potential health benefits. This study aims to enhance the sensitivity and reliability of TAC detection through a dual-signal method, combining colorimetric and photothermal signals. Gold nanorods (AuNRs) were utilized to establish a dual-signal method duo to the colorimetric and photothermal properties. Fenton reaction can etch the AuNRs from the tips, as a result, a blue shift in the longitudinal LSPR absorption peak was obtained, leading to significant changes in color and photothermal effects, facilitating discrimination through both visual observation and thermometer measurements. In the presence of antioxidants, the Fenton reaction was suppressed or inhibited, protecting the AuNRs from etching. The colorimetric and photothermal signals were therefore positively correlated with TAC levels, enabling dual-signal detection of TAC. The linear range of AA was 4-100 µM in both colorimetry and photothermal modes, with detection limits of 1.60 µM and 1.38 µM, respectively. This dual-signal approach achieves low detection limits, enhancing precision and sensitivity. The method thus has the potential to act as a promising candidate for TAC detection in food samples, contributing to improved food quality and safety assessment.

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The identification of phosphates holds significant importance in many physiological processes and disease diagnosis, and traditional detection techniques struggle to simultaneously detect and distinguish phosphates. The complexity of synthesizing sensing units restricts the construction of sensor arrays as well. In this study, a bifunctional dicopper chloride trihydroxide (Cu2Cl(OH)3) nanozyme with conspicuous laccase- and peroxidase-like activities has been synthesized in basic deep eutectic solvents (DES). Exploiting the various regulatory impacts of multiple phosphates on the dual-enzyme mimicking activities, the sensor array based on the laccase mimic and peroxidase mimic properties of Cu2Cl(OH)3 was designed, which has been successfully harnessed for the identification of eight phosphates (ATP, ADP, AMP, PPi, Pi, GTP, GDP, and GMP). This approach streamlines the creation of sensor arrays. Besides, the three simulated actual samples (healthy individuals, moderately ill patients, and severely ill patients) have been accurately distinguished. This work makes a substantial contribution to enhancing the highly effective construction of array channels and promoting discrimination of phosphates in intricate samples.

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The small molecule aldehydes are volatile organic compounds (VOCs), possessing cytotoxicity and carcinogenicity. Long-term exposure can pose a serious threat to human health. Based on an in-situ reduction colorimetric method to generate silver nanoparticles and induce colorimetric response, we proposed a silver-loaded paper-based colorimetric sensor array for visually detecting and differentiating five relatively common trace small molecule aldehyde gases. The silver ions are immobilized onto a porous filter paper and stabilized by complexing agents of branched polyethyleneimine, ethylenediamine, and 1,6-diaminohexane, respectively. The as-fabricated sensor array expresses remarkable stability and capacity to resist humidity. The qualitative analysis reveals that the sensor array has excellent selectivity for aldehyde gases and displays remarkable anti-interference ability. The quantitative analysis indicates that the sensor array exhibits superior sensitivity for five aldehyde gases, with limits of detection (LODs) of 9.0 ppb for formaldehyde (FA), 3.1 ppm for acetaldehyde (AA), 3.5 ppm for propionaldehyde (PA), 23.8 ppb for glutaric dialdehyde (GD), and 71.5 ppb for hydroxy formaldehyde (HF), respectively. Importantly, these LODs are all comfortably below their respective permissible exposure limits. A unique colorimetric response fingerprint is observed for each analyte. Standard chemometric methods illustrate that the sensor array has excellent clustering capability for these aldehyde gases. Additionally, the sensor array's response is irreversible and possesses outstanding performance for cumulative monitoring. This colorimetric sensor array based on silver ions reduced to silver nanoparticles offers a novel detection method for the continuous, ultrasensitive, and visual detection of trace airborne pollutants.

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In recent years, nanozymes have been widely used in the field of biosensing and food safety testing due to their advantages of low cost, high stability, easy modification and adjustable catalytic activity. However, how to reduce the signal interference generated by reducing substances, macromolecules and colored substances in the food matrix in nanozymes-based colorimetric sensing is still a major challenge. In this paper, using Listeria monocytogenes as a model analyte, sodium sulfonyl methacrylate (SBMA) polymers were modified onto cotton swabs by photothermal polymerization and combined with Listeria monocytogenes-specific aptamer (Apt1) to prepare swabs that can specifically capture and isolate Listeria monocytogenes from complex matrices (SBMA/Apt1 cotton swab). In addition, in combination with the inhibitory effect of the aptamer (Apt2) on the oxidase activity of Mn3O4 NPs, a colorimetric biosensor based on nanozymes that can quantitatively, sensitively, and specifically identify Listeria monocytogenes in food products was constructed. The results showed that the colorimetric signal of the method was linear with the concentration of Listeria monocytogenes in the range of 2.83-2.83 × 105 CFU/mL, and the limit of detection was 2.64 CFU/mL, which can be used for the detection of Listeria monocytogenes in complex environments and food samples.

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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.

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In recent years, nanozymes have attracted particular interest and attention as catalysts because of their high catalytic efficiency and stability compared with natural enzymes, whereas how to use simple methods to further improve the catalytic activity of nanozymes is still challenging. In this work, we report a trimetallic metal-organic framework (MOF) based on Fe, Co and Ni, which was prepared by replacing partial original Fe nodes of the Fe-MOF with Co and Ni nodes. The obtained FeCoNi-MOF shows both oxidase-like activity and peroxidase-like activity. FeCoNi-MOF can not only oxidize the chromogenic substrate 3,3,5,5-tetramethylbenzidine (TMB) to its blue oxidation product oxTMB directly, but also catalyze the activation of H2O2 to oxidize the TMB. Compared with corresponding monometallic/bimetallic MOFs, the FeCoNi-MOF with equimolar metals hereby prepared exhibited higher peroxidase-like activity, faster colorimetric reaction speed (1.26-2.57 folds), shorter reaction time (20 min) and stronger affinity with TMB (2.50-5.89 folds) and H2O2 (1.73-3.94 folds), owing to the splendid synergistic electron transfer effect between Fe, Co and Ni. Considering its outstanding advantages, a promising FeCoNi-MOF-based sensing platform has been designated for the colorimetric detection of the biomarker H2O2 and environmental pollutant TP, and lower limits of detection (LODs) (1.75 µM for H2O2 and 0.045 µM for TP) and wider linear ranges (6-800 µM for H2O2 and 0.5-80 µM for TP) were obtained. In addition, the newly constructed colorimetric platform for TP has been applied successfully for the determination of TP in real water samples with average recoveries ranging from 94.6% to 112.1%. Finally, the colorimetric sensing platform based on FeCoNi-MOF is converted to a cost-effective paper strip sensor, which renders the detection of TP more rapid and convenient.

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An anti-interference colorimetric sensor array (CSA) technique was developed for the qualitative and quantitative detection of target heavy metals in corn oil. This method involves a binding mechanism that triggers changes in atomic energy levels and visible color changes. A custom-built olfactory visualization device was employed to gather spectral data, revealing distinct CSA color difference patterns. Subsequently, three pattern recognition algorithms were used to create an identification model for the target heavy metals. The results showed that the ACO-KNN (Ant Colony Optimization-K-Nearest Neighbor) model outperformed the other models, achieving accuracy rates of 90.28% and 89.58% for the calibration and prediction sets, respectively. The ACO-PLS (Partial Least Square) model was more stable with the lowest root mean square error of prediction (RMSEP), which were 0.1730 and 0.1180, respectively. The limit of detection (LOD) and quantification (LOQ) of Pb and Hg were (0.3, 0.6, 1.1 and 2.2) x 10-3 mg/L, respectively.

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Smartphone-assisted analysis has become widely utilized for detecting various species in recent years. In such studies, multiple dyes should be employed to ensure selectivity and analyte discrimination. In our research, we have demonstrated the capability of a specially synthesized dye to selectively detect and discriminate liquid amine vapors. The developed material employs meso-toluene-α,ß,α',ß'-tetrabromoBODIPY immobilized on a thin-layer chromatography plate, exhibiting structure-specific color changes in response to amine vapors. The hue values of these colors, observed under both ambient and UV light, enable discrimination even among closely related amine structures. A mobile application has also been developed for the rapid interpretation of test results.

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Herein, oxidized 3,3',5,5'-tetramethylbenzidine (oxTMB) nanobelts were developed to enhance the colorimetric and paper-based sensing of H2O2. It was found that the minor component of Fe2+ in Na2SO4 reagent could catalyze the oxidization of TMB by H2O2 into positively charged oxTMB, which was further assembled into dark blue oxTMB nanobelts via electrostatic interaction with SO42-. The extinction originating from the absorption and scattering of oxTMB nanobelts was utilized to quantitatively detect H2O2 with a wide linear detection range (1.0-300 µM) and a low limit of detection (0.48 µM). In addition, no coffee-ring effect was observed in the test zone of the paper-based colorimetric array, which was beneficial to judge the color by naked eye. Finally, the colorimetric method was applied to detect H2O2 in contact lens care solution. This work not only proposed a new colorimetric sensing platform for H2O2, but also highlighted the minor component in the reagent might influence the experimental result.

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