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The development of pressure sensors with high sensitivity and a low detection limit for subtle mechanical force monitoring and the understanding of the sensing mechanism behind subtle mechanical force monitoring are of great significance for intelligent technology. Here, we proposed a graphene-based two-stage enhancement pressure sensor (GTEPS), and we analyzed the difference between subtle mechanical force monitoring and conventional mechanical force monitoring. The GTEPS exhibited a high sensitivity of 62.2 kPa-1 and a low detection limit of 0.1 Pa. Leveraging its excellent performance, the GTEPS was successfully applied in various subtle mechanical force monitoring applications, including acoustic wave detection, voice-print recognition, and pulse wave monitoring. In acoustic wave detection, the GTEPS achieved a 100% recognition accuracy for six words. In voiceprint recognition, the sensor exhibited accurate identification of distinct voiceprints among individuals. Furthermore, in pulse wave monitoring, GTEPS demonstrated effective detection of pulse waves. By combination of the pulse wave signals with electrocardiogram (ECG) signals, it enabled the assessment of blood pressure. These results demonstrate the excellent performance of GTEPS and highlight its great potential for subtle mechanical force monitoring and its various applications. The current results indicate that GTEPS shows great potential for applications in subtle mechanical force monitoring.
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In this study, reduced graphene oxide (rGO) was electrochemically deposited on the surface of screen-printed carbon electrodes (SPCE) to prepare a disposable sensor for fast detection of Pb2+ in foods. The SEM images showed that the rGO was homogeneously deposited onto the electrode surface with a wrinkled nanostructure, which provided 2D bridges for electron transport and a larger active area for Pb2+ adsorption. Results showed that rGO modification enhanced the activity of the electrode surface, and significantly improved the electrochemical properties of SPCE. The rGO modified SPCE (rGO-SPCE) was applied to detect Pb2+ in standard aqueous solution, showing a sharp stripping peak and a relatively constant peak potential in square wave anodic stripping voltammetry (SWASV). The linear range for Pb2+ detection was 5~200 ppb (R2 = 0.9923) with a low detection limit of 1 ppb (S/N = 3). The interference of Cd2+ and Cu2+ at low concentrations was effectively avoided. Finally, the rGO-SPCE was used for determination of lead in real tap water, juice, preserved eggs and tea samples. Compared with results from graphite furnace atomic absorption spectroscopy (GFAAS), the results based on rGO-SPCE were both accurate and reliable, suggesting that the disposable sensor has great potential in application for fast, sensitive and low-cost detection of Pb2+ in foods.
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Conductometría/instrumentación , Equipos Desechables , Electrodos , Análisis de los Alimentos/instrumentación , Contaminación de Alimentos/análisis , Grafito/química , Plomo/análisis , Diseño de Equipo , Análisis de Falla de Equipo , Oxidación-Reducción , Óxidos/química , Reproducibilidad de los Resultados , Sensibilidad y EspecificidadRESUMEN
Continuous blood pressure (BP) monitoring is of great significance for the real-time monitoring and early prevention of cardiovascular diseases. Recently, wearable BP monitoring devices have made great progress in the development of daily BP monitoring because they adapt to long-term and high-comfort wear requirements. However, the research and development of wearable continuous BP monitoring devices still face great challenges such as obvious motion noise and slow dynamic response speeds. The pulse wave transit time method which is combined with photoplethysmography (PPG) waves and electrocardiogram (ECG) waves for continuous BP monitoring has received wide attention due to its advantages in terms of excellent dynamic response characteristics and high accuracy. Here, we review the recent state-of-art wearable continuous BP monitoring devices and related technology based on the pulse wave transit time; their measuring principles, design methods, preparation processes, and properties are analyzed in detail. In addition, the potential development directions and challenges of wearable continuous BP monitoring devices based on the pulse wave transit time method are discussed.
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We report an artificial eardrum using an acoustic sensor based on two-dimensional MXene (Ti3C2Tx), which mimics the function of a human eardrum for realizing voice detection and recognition. Using MXene with a large interlayer distance and micropyramid polydimethylsiloxane arrays can enable a two-stage amplification of pressure and acoustic sensing. The MXene artificial eardrum shows an extremely high sensitivity of 62 kPa-1 and a very low detection limit of 0.1 Pa. Notably, benefiting from the ultrasensitive MXene eardrum, the machine-learning algorithm for real-time voice classification can be realized with high accuracy. The 280 voice signals are successfully classified for seven categories, and a high accuracy of 96.4 and 95% can be achieved by the training dataset and the test dataset, respectively. The current results indicate that the MXene artificial intelligent eardrum shows great potential for applications in wearable acoustical health care devices.
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Owing to the canonical trade-off between the gauge factor and the working range, there is an emergent need for strain sensors with customizable sensitivity for various applications of different deformation ranges. However, current optimization strategies typically allow possessing either, not both, high-sensing performance or customizable sensing performance. Here, a laser-programmed heterogeneous strain sensor featured locally coupled electrical and mechanical properties (named an LCoup sensor) is developed to access customized sensor performance. Coupled electromechanical properties enable the applied strain to be mainly experienced by the higher sensitivity regions when stretched. By optimizing the parameters of laser processes, the gauge factor can systematically screen within 2 orders of magnitude (from 7.8 to 266.6) while maintaining good stretchability (50%). To prove the potential in human-machine interaction, the real-time monitoring and recognition of set hand gestures (left-click, right-click, and double-click) are demonstrated, representing the traditional input patterns of the computer mouse. Multiscale programming of material properties can further achieve excellent and tailored device performances, offering more opportunities for the design of a broad range of flexible electronics.
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Dispositivos Electrónicos Vestibles , Conductividad Eléctrica , ElectricidadRESUMEN
In this work, a high integrated water detection system comprised a miniaturized and high precision homemade colorimeter, a microfluidic analysis module and a wireless module was reported. A reagent reaction based on the ammonium molybdate spectrophotometric method was recorded for the estimation of phosphate in natural water. A laser self-modulating module of 880â¯nm was used as the radiation source. A microfluidic chip was employed to fit the colorimeter with an optimized micro flow path for low liquid consumption and high precision detection. The wireless module consisted of two parts, using ZigBee and GSM modules to realize short and remote displaying and controlling. Applying a novel optimized algorithm, a wide linear response was obtained ranging from 0.02 up to 9.5â¯mgâ¯L-1. The optimization of colorimeterare mainly in the core detection part, allowing an improvement of the detection limit, achieving a result of 0.009â¯mgâ¯L-1. A low reagent consumption of 0.004â¯mg ascorbic acid and 0.011â¯mg ammonium molybdate for per determination was attained. Experimental results have also shown that the system could maintain good stability among broad room temperature changing from 17⯰C to 35⯰C with less energy consumption. The miniaturized colorimeter-based water detection system opens new avenue for operating in remote distance to get high precision measurements of phosphate in natural water.
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There is a growing demand for flexible electronic devices. In particular, strain sensors with high performance have attracted more and more attention, because they can be attached on clothing or human skin for applications in the real-time monitoring of human activities. However, monitoring human-body motions that include both subtle and intensive motions, and many strain sensors cannot meet the diverse demands simultaneously. In this work, a silver nanoparticles (Ag NPs) bridged graphene strain sensor is developed for simultaneously detecting subtle and intensive human motions. Ag NPs serve as many bridges to connect the self-overlapping graphene sheets, which endows the strain sensor with many excellent performances. Because of the high sensitivity, with a large gauge factor (GF) of 475 and a strain range of >14.5%, high durability of the sensor has been achieved. Besides, the excellent consistency and repeatability of the fabrication process is verified. Furthermore, the model for explaining the working mechanism of the strain sensor is proposed. Most importantly, the designed wearable strain sensor can be applied in human motion detection, including large-scale motions and small-scale motions.