With ongoing technological advancements, artificial tactile systems have become a prominent area of research, aiming to replicate human tactile capabilities and enabling machines and devices to interact with their env...
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With ongoing technological advancements, artificial tactile systems have become a prominent area of research, aiming to replicate human tactile capabilities and enabling machines and devices to interact with their environments. Achieving effective artificial tactile sensing relies on the integration of high-performance pressure sensors, precise signal acquisition, robust transmission, and rapid data processing. In this study, we developed a sensor array system based on flexible pressure sensors designed to recognize objects of varying shapes and sizes. The system comprises a multi-channel acquisition circuit and a signal transmission circuit and employs a convolutional neural network (CNN) to classify distinct signal patterns. In a test on an individual, the test results demonstrate that the system achieves a high recognition accuracy of 99.60% across two sphere sizes, three cylinder sizes, a cone, and a rectangular prism. In a group of eight people, it can achieve a recognition accuracy of 93.75%. Furthermore, we applied this sensor array system in an experimental setting involving a ball-throwing action, and it effectively recognized four distinct stages: empty hand, holding the ball, throwing, and catching. In repeated tests by other individuals, it was also able to clearly distinguish each stage. The development of artificial tactile systems allows robots to engage with their environments in a more nuanced and precise manner, enabling complex tasks such as surgical procedures, enhancing the interactive experience of wearable devices, and increasing immersion in virtual reality (VR) and augmented reality (AR). When integrated with deep learning, artificial tactile sensing shows significant potential for creating more intelligent and efficient applications.
Though cholinesterase-based method could detect two types of pesticides (organophosphorus and carbamate), they had weak sensing on sulfonylurea pesticides. In our previous work, the peroxidase-like reaction system of ...
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Though cholinesterase-based method could detect two types of pesticides (organophosphorus and carbamate), they had weak sensing on sulfonylurea pesticides. In our previous work, the peroxidase-like reaction system of nanozyme - H2O2 - TMB showed selective detection of sulfonylurea pesticides, but the single-signal output sensing platform was easily affected by complex matrix background, cross-contamination and human error. Therefore, this work used colorimetric, photothermal, and fluorescent signals of the nanozyme reaction as sensing units for the detection of pesticides. This is the first time that photothermal signals have been used to construct a sensor array. When the concentration of interfering substances was 25 times that of pesticides, the method was still unaffected and had excellent selectivity and anti-interference performance. Meanwhile, a concentration-independent differentiation mode was established based on the K-nearest neighbor (KNN) algorithm. The pesticides were detected and distinguished with 100% accuracy. This work contributed to the detection of sulfonylurea pesticides in complex environmental/food matrices, bridging the gap of existing pesticide detection methods and providing an effective method for food safety detection.
Precise snake venom identification is the prerequisite for clinical treatment, production of antiserum, basic research, and other applications. Unfortunately, it is still a challenging task which mainly originates fro...
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Precise snake venom identification is the prerequisite for clinical treatment, production of antiserum, basic research, and other applications. Unfortunately, it is still a challenging task which mainly originates from their extraordinary complicated protein composition. Differential sensing strategy was applied benefiting from its advantage in discrimination of complex mixtures. Herein, A dual-mode supramolecular fluorescent sensor array based on the heteromultivalent sensing strategy was developed. The heteromultivalent macrocyclic coassemblies with strong and pan-selective binding to proteins were employed to construct sensor units. Fluorescence intensity and anisotropy signals were integrated, which were expected to show multidimensional information of proteins, such as surface groups, protein structures, and molecular weights. Finally, a supramolecular sensor array with the ability of facile, rapid and general species-specific identification and taxonomic classification for snake venom was constructed. The sensor array also demonstrated its advantage in semiquantitative analysis and multi-level identification, suggesting its great potential for practical use.
array-based analysis allows for precise disease diagnosis by simultaneously detecting multiple biomarkers. However, most array sensing platforms rely on non-covalent interactions between sensors and analytes, which li...
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array-based analysis allows for precise disease diagnosis by simultaneously detecting multiple biomarkers. However, most array sensing platforms rely on non-covalent interactions between sensors and analytes, which limits their sensitivity. This study enhances the sensitivity of array analysis for thiol biomarkers by incorporating polyion complex micelles into the sensor array design. Polyion complex micelles are formed through the selfassembly of carbon dots (CDs) and anionic diblock copolymers. The sensing detection process can occur inside the core of the micelle, the confined space and ionic environment within the core reduce the interaction distance between CDs, metal ions, and analytes, thereby significantly improving detection sensitivity while minimizing metal ions consumption. The developed array system can accurately identify multiple thiols across a broad concentration range (0.5-1000 mu M) with 100% accuracy. Additionally, support vector machine (SVM) analysis reveals a detection limit of approximately 0.1 mu M for individual thiol systems. Compared to non-micellar approaches, this micelle-based array reduces the detection limit for thiol biomarkers by 20-fold and decreases Ag+ usage by 40-fold. The system is suitable for both qualitative and quantitative analysis of thiol biomarkers, offering a powerful tool for the accurate diagnosis of thiol-related diseases.
Antioxidant detection is highly significant in practical applications. This study establishes an optical sensor array capable of simultaneous and convenient detection of multiple antioxidants in real samples. CaxMn1-x...
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Antioxidant detection is highly significant in practical applications. This study establishes an optical sensor array capable of simultaneous and convenient detection of multiple antioxidants in real samples. CaxMn1-xWO4 (CMW) synthesized via hydrothermal method with abundant surface oxygen vacancies and high internal electron transfer efficiency exhibits strong oxidase-like activity, which can oxidize TMB to blue product oxTMB using oxygen as reaction substrate. The presence of antioxidants weakens TMB oxidation, leading to a lighter blue color in the system. Therefore, CMW can be employed for colorimetric detection of antioxidants. Then CMW samples with varying Ca to Mn ratios were prepared, followed by the establishment of an optical sensor array. The detection systems were photographed, and PCA analysis of the RGB parameters was performed, enabling simultaneous qualitative and quantitative detection of nine kinds of antioxidants.
Flexible magnetic sensors, which have advantages such as deformability, vector field sensing, and noncontact detection, are an important branch of flexible electronics and have significant applications in fields such ...
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Flexible magnetic sensors, which have advantages such as deformability, vector field sensing, and noncontact detection, are an important branch of flexible electronics and have significant applications in fields such as magnetosensitive electronic skin. Human skin surfaces have complicated deformations, which pose a demand for magnetic sensors that can withstand omnidirectional strain while maintaining stable performance. However, existing flexible magnetic sensor arrays can only withstand stretching along specific directions and are prone to failure under complicated deformations. Here, we demonstrate an omnidirectionally stretchable spin-valve sensor array with high stretchability and excellent performance. By integrating the modulus-distributed structure with liquid metal, the sensor can maintain its performance under complex deformations, enabling the overall system with omnidirectional stretchability. The fabricated spin-valve sensor exhibits a nearly unchanged giant magnetoresistance ratio of 8% and a maximum sensitivity of 0.93%/Oe upon omnidirectional strain up to 86% and can maintain stable performance without fatigue for over 1000 stretching cycles. Furthermore, this spin-valve sensor array is characterized by stable sensing performance for magnetic fields under complicated deformations and can be applied as a magnetosensitive electronic skin. Our results provide insights into the development of next-generation stretchable and wearable magnetoelectronics.
Perovskite-based image sensors are widely explored and recognized as the technology of choice for future optoelectronics. Suffering from the incompatibility between perovskite and conventional lithography technology, ...
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Perovskite-based image sensors are widely explored and recognized as the technology of choice for future optoelectronics. Suffering from the incompatibility between perovskite and conventional lithography technology, the challenges of developing high-resolution image sensors come from how to pattern the perovskite film with high precision and integrate it with pixel circuits. Recently, a four-mask technique for manufacturing perovskite-on-silicon sensor arrays, which are composed of a pixeled perovskite film and a planar crossbar circuit is demonstrated. Patterning precision for perovskite films attained 2 mu m, ranking top among the previous research. The circuit is also proven to have the highest level of integration, theoretically. A proof-of-concept image sensor showing the first demonstration of monolithic integration of patterned perovskite film with the bottom pixel circuit is successfully made public. Electro-optical performance of its pixels is further characterized and showed high uniformity, benefitting the image sensor in capturing the input light distribution with good spatial resolution. This work has thus set a milestone for perovskite-based image sensors and showed the potential of perovskites in micro-nanoelectronics.
Multi-target detection is a notable development direction in the field of analytical methods, boasting significant potential for breakthroughs in complex sample detection. Herein, an extended gate field-effect transis...
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Multi-target detection is a notable development direction in the field of analytical methods, boasting significant potential for breakthroughs in complex sample detection. Herein, an extended gate field-effect transistor (EGFET) sensor array for ultrasensitive and multi-target detection of antibiotics is developed. To enhance the recognition ability for diverse antibiotics, a dual-recognition strategy based on tailor-made molecularly imprinted polymer (MIP) and aptamer is adopted to fabricate the extended gate electrode (sensing electrode). The dual-recognition strategy-based EGFET exhibits superior sensitivity, selectivity, and stability compared to single recognition probes due to the synergistic effect of the affinities of MIP and specific aptamer. The developed sensor array can detect three types of antibiotics, including ampicillin, amoxicillin, and kanamycin, at the same time with record-low detection limit (fM level) and a detection range spanning six orders of magnitude. The practical detection of antibiotics in various samples (tap water, river water, milk, honey, and artificial urine) further validates the feasibility of the sensor array in practical applications. The key advantages of flexibility, high sensitivity and selectivity, and multifunctionality demonstrate the high potential of EGFET sensor array for simultaneous detection of multiple target molecules.
Background: Discriminating the quality of baijiu is critical for fostering the growth of the China baijiu market and safeguarding customers' rights. However, establishing a small-scale and rapid baijiu discriminat...
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Background: Discriminating the quality of baijiu is critical for fostering the growth of the China baijiu market and safeguarding customers' rights. However, establishing a small-scale and rapid baijiu discriminating sensor assay still remains a challenge. Results: Here, we first introduced ratiometric fluorescence sensor array for the detection of reducing substances in baijiu to achieve baijiu discrimination. A ratiometric fluorescence sensor array is built using 2,3-diaminophenazine (oxidized-state OPD, oxOPD) to quench three distinct fluorescence signals of quantum dots while reducing interference from background signals. The reducing chemicals in baijiu can react with Ag+, weakening the quenching effect and changing the ratio. The discriminating of 12 types of organic small molecules which were presented in baijiu was achieved with 97.2 % accuracy by using machine learning classification methods. Meanwhile, 0.1 mu M limit of detection (LOD) for ascorbic acid shows that our methods have the potential to quantitative detect reducing substances. In real sample detection, our methods can discriminate 10 distinct qualities of baijiu with 100 % accuracy. We also encoded the fingerprints of different varieties of baijiu for quality control and information reading. Significance and novelty: Overall, our easy but robust sensing array not only overcomes the problem of background signal interference but also gives an ideal way for discriminating different qualities of baijiu, food and other areas.
Biothiol analysis is significant to health assessment and early detection of potential diseases. Considering practical requirements, simple and rapid identification and determination of biothiols are still a great cha...
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Biothiol analysis is significant to health assessment and early detection of potential diseases. Considering practical requirements, simple and rapid identification and determination of biothiols are still a great challenge due to the similar structures. Fortunately, the recently emerging colorimetric sensor array technique makes such a task possible. Herein, one-component dual-mode sensor array consisting of carbon dots (CDs) and Ag nanoparticles (AgNPs) system was designed for identification and quantification of biothiols. The identification principle is based on the inner filter effect (IFE) and different binding constants. Due to the IFE between CDs and AgNPs, the fluorescence of CDs was quenched, but recovered again after addition of biothiols because of the binding of biothiols with AgNPs. Significantly, the fluorescence recovered in varying degree due to the different binding constants of biothiols to AgNPs. Meanwhile, the absorbance of the system decreased and the color of the solution deepened. Therefore, the CDs-AgNPs system with fluorescence and absorbance response was used as the single sensing unit and generated the cross-responsive signal for different biothiols. The sensor array achieved 100 % accuracy in identifying biothiols and biothiol mixtures. Moreover, the rapid quantification of biothiols in serum samples was also achieved by RGB-based smartphone colorimetry. The way to construct one component sensor array with dual mode signal outputs tremendously saves cost and time, providing a powerful tool for the identification of different biothiols. In addition, the rapid quantification of biothiols in serum samples based on RGB-based smartphone colorimetry demonstrated its powerful application prospects in disease diagnosis.
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