Formaldehyde is ubiquitously found in the environment, meaning that real-time monitoring of formaldehyde, particularly indoors, can have a significant impact on human health. However, the performance of commercially a...
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Formaldehyde is ubiquitously found in the environment, meaning that real-time monitoring of formaldehyde, particularly indoors, can have a significant impact on human health. However, the performance of commercially available interdigital electrode-based sensors is a compromise between active material loading and steric hindrance. In this work, a spaced TiO2 nanotube array (NTA) was exploited as a scaffold and electron collector in a formaldehyde sensor for the first time. A Sn-based metal-organic framework was successfully decorated on the inside and outside of TiO2 nanotube walls by a facile solvothermal decoration strategy. This was followed by regulated calcination, which successfully integrated the preconcentration effect of a porous Sn-based metal-organic framework (SnMOF) structure and highly active SnO2 nanocrystals into the spaced TiO2 NTA to form a Schottky heterojunction-type gas sensor. This SnMOF/SnO2@TiO2 NTA sensor achieved a high room-temperature formaldehyde response (1.7 at 6 ppm) with a fast response (4.0 s) and recovery (2.5 s) times. This work provides a new platform for preparing alternatives to interdigital electrode-based sensors and offers an effective strategy for achieving target preconcentrations for gas sensing processes. The as-prepared SnMOF/SnO2@TiO2 NTA sensor demonstrated excellent sensitivity, stability, reproducibility, flexibility, and convenience, showing excellent potential as a miniaturized device for medical diagnosis, environmental monitoring, and other intelligent sensing systems.
This work introduces a novel microwave sensor leveraging a perfect metamaterial absorber (PMA) based on transmission-line metamaterials, marking a significant step toward enhancing sensing capabilities. Unique design ...
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This work introduces a novel microwave sensor leveraging a perfect metamaterial absorber (PMA) based on transmission-line metamaterials, marking a significant step toward enhancing sensing capabilities. Unique design choices, including the integration of lumped inductors and series capacitors within the unit cell to synthesize a negative and near-zero permittivity, elevate the sensor's resolution and lower the absorption frequency. These modifications enhance sensitivity and precision for detecting small material quantities, with the sensor achieving an absorption efficiency exceeding 98%. The design also ensures robust performance against changes in incident angles and polarization due to its compact profile, rendering it versatile for diverse sensing applications. Experimental validation confirms the sensor's performance, highlighting its efficacy in material detection with a notable frequency shift sensitivity of 500 MHz for permittivity changes from 3 to 18, establishing it as a transformative structure for metamaterial-based microwave sensing technologies. Furthermore, the sensor demonstrates a resolution of 5.01 MHz per percentage increase in soil moisture content, offering a new benchmark in the precision of environmental sensing. This breakthrough in design and functionality establishes the sensor as a pivotal tool in the advancement of metamaterial-based microwave sensing technologies, promising widespread applicability, and impact.
Biochemical sensors have become indispensable tools for real-time, on -site monitoring and analysis in diverse domains such as healthcare, environmental protection, and food safety. The rapid evolution of artificial i...
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Biochemical sensors have become indispensable tools for real-time, on -site monitoring and analysis in diverse domains such as healthcare, environmental protection, and food safety. The rapid evolution of artificial intelligence (AI) has opened new frontiers for enhancing the capabilities of these sensors across a spectrum of detection modalities. This paper delves into the recent integration of AI algorithms into biochemical sensors, examining this advancement from a functional standpoint and focusing on the empowerments it brings to electrochemical, electrochemiluminescence, colorimetric, and Raman sensors. AI techniques aim to enhance the capabilities of biochemical sensors beyond traditional techniques and have enabled improved selectivity, drift correction, efficiency, resolution, assisted diagnosis, and biomarker screening from complex multidimensional data. In the end, we provide a personal perspective on future development and address the remaining challenges in the commercialization of AI -based biochemical sensors.
A high-performance sensor is crucial for the integration of optical biosensors, enabling the precise and rapid identification of target analytes. We present the correlation between feedback-coupled microring resonator...
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A high-performance sensor is crucial for the integration of optical biosensors, enabling the precise and rapid identification of target analytes. We present the correlation between feedback-coupled microring resonator (FBCMR) and variations in Mach-Zehnder interferometer (MZI) and microring resonator (MRR) phases. By introducing an asymmetric MZI into FBCMR, we have successfully achieved ultra-high sensitivity integrated photonic sensor whose refractive index sensitivity and limit of detection are 5752.5 nm/RIU and 1.6514 x 10-5, respectively. The photonic sensor is packaged with a PDMS microfluidic layer, forming an integrated optofluidic chip, which is applied to detect human alpha-fetoprotein (AFP). Such an integrated photonic sensor has no suspended or subwavelength grating (SWG) structure so that no need to challenge manufacturing processes which paves the way for application in high-resolution biochemical sensing and environmental monitoring.
An array of sensors generating a collection of correlated signals can benefit from integration with a "smart" system for autonomous inferencing. Mimicking their biological counterparts, smart sensor systems ...
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An array of sensors generating a collection of correlated signals can benefit from integration with a "smart" system for autonomous inferencing. Mimicking their biological counterparts, smart sensor systems shall possess the capabilities of sensing, memory, and neuromorphic computation. However, state-of-the-art biomimetic systems either do not employ a full set of devices to cover the complete range of capabilities or incorporate devices that are capable of all but appropriate only for a limited range of sensing applications. Presently proposed is a smart sensor architecture that combines an array of sensing elements with an overlapping array of computing and memory elements, thus emulating an innervated peripheral sensing system (IPSS) capable of local and autonomous neuromorphic in-sensor data pre-processing. Compatibility of the proposed architecture with functionally distinct elements for sensing, memory, and computing removes the restrictive demand for a single element simultaneously capable of all, thus making this architecture more generally applicable to a wider range of sensors and usage scenarios. An artificial synapse as a computing element is implemented using dual-gate (DG) thin-film transistors (TFTs) and the low-leakage current of transistors based on metal-oxide semiconductors allows the deployment of capacitors as memory elements. The outputs of the IPSS are passed on to an adjacent artificial neural network (ANN) for near-sensor inferencing. Monolithic integration of the IPSS and the ANN is made possible by the deployment of the same memory and computing elements in their construction. A smart tactile sensing system based on the proposed architecture is constructed and characterized. The functionality of the system is demonstrated by its application to the classification of a set of tactile images of 3-dimensionally printed alphabet stamps.
NO2 seriously threatens human health and the ecological environment. However, the fabrication of highly sensitive NO2 sensors with rapid response/recovery rates, low detection limits, and ease of integration remains a...
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NO2 seriously threatens human health and the ecological environment. However, the fabrication of highly sensitive NO2 sensors with rapid response/recovery rates, low detection limits, and ease of integration remains a challenge. Herein, benefiting from the fast carrier transfer and rich active sites, holey graphene oxide (HGO) was adopted to functionalize the In2O3 nanosheet to construct NO2 gas sensors. Characterization and theoretical calculations established the merits of HGO decoration in the NO2 sensing. The optimal sample, 0.5 wt % HGO/In2O3-sheet, exhibited superior sensing properties, resulting in a 1.37-fold improvement in response to 1 ppm of NO2 compared to the GO/In2O3 counterpart. Gas-sensing kinetics analysis revealed its lower activation energy and higher kinetic rate constants. Importantly, pulsed-temperature modulation was employed to decouple the gas adsorption from surface activation processes, achieving an ultrahigh response of 2776 to 1 ppm of NO2 for the 0.5 wt % HGO/In2O3-sheet sensor. Compared to the isothermal mode, this strategy enhanced the response value by 1.6 times, reduced the response/recovery time by 33%/70%, and enabled the detection of NO2 concentrations as low as 1 ppb. Finally, an NO2 monitoring alarm system based on the 0.5 wt % HGO/In2O3-sheet sensor with pulsed-temperature modulation was demonstrated for hazard warnings.
This study presents a comprehensive investigation into the design and optimization of capacitive pressure sensors (CPSs) for their integration into capacitive touch buttons in electronic applications. Using the Finite...
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This study presents a comprehensive investigation into the design and optimization of capacitive pressure sensors (CPSs) for their integration into capacitive touch buttons in electronic applications. Using the Finite Element Method (FEM), various geometries of dielectric layers were meticulously modeled and analyzed for their capacitive and sensitivity parameters. The flexible elastomer polydimethylsiloxane (PDMS) is used as a diaphragm, and polyvinylidene fluoride (PVDF) is a flexible material that acts as a dielectric medium. The Design of Experiment (DoE) techniques, aided by statistical analysis, were employed to identify the optimal geometric shapes of the CPS model. From the prediction using the DoE approach, it is observed that the cylindrical-shaped dielectric medium has better sensitivity. Using this optimal configuration, the CPS was further examined across a range of dielectric layer thicknesses to determine the capacitance, stored electrical energy, displacement, and stress levels at uniform pressures ranging from 0 to 200 kPa. Employing a 0.1 mm dielectric layer thickness yields heightened sensitivity and capacitance values, which is consistent with theoretical efforts. At a pressure of 200 kPa, the sensor achieves a maximum capacitance of 33.3 pF, with a total stored electric energy of 15.9 x 10-12 J and 0.468 pF/Pa of sensitivity for 0.1 dielectric thickness. These findings underscore the efficacy of the proposed CPS model for integration into capacitive touch buttons in electronic devices and e-skin applications, thereby offering promising advancements in sensor technology.
Integrating sensors within a complete readout system on a single die has become essential to the More-than-Moore philosophy. Mechanical stress, as one of the physical quantities of potential interest, provides various...
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Integrating sensors within a complete readout system on a single die has become essential to the More-than-Moore philosophy. Mechanical stress, as one of the physical quantities of potential interest, provides various information from simple static to dynamic load. integration of piezoresistive elements within a complete CMOS system has been achieved in many ways, and ground-laying effects have been studied and described in detail. To bring the mechanical and electrical domains closer together, a new concept is presented that allows an analytical and simulation-based approximation of the sensors' behavior due to applied mechanical stress as part of established concepts in electronics. It is evaluated based on measured state-of-the-art sensor implementations and used to bring up an alternative architecture with enhanced and on-the-fly adaptive sensitivity. Simulations are used to then further evaluate any model errors due to second-order effects that have been neglected within the design process.
This study proposed the application of microwave resonators embedded with carbon nanotube (CNT) sensing films fabricated using inkjet printing technology as gas sensors. The density and uniformity of CNTs dominated re...
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This study proposed the application of microwave resonators embedded with carbon nanotube (CNT) sensing films fabricated using inkjet printing technology as gas sensors. The density and uniformity of CNTs dominated resistance, which was related to inkjet printing droplet spacing (DS), layer numbers, and electrode patterns. Although the high-density resistive-type CNT (DS = 20 mu m and 20 layers) sensor with the regular electrode (RE) pattern had a lower response than the low-density CNT (DS = 30 mu m) sensor, its response presented a narrow repeatability distribution. The response of the high-density CNT sensor with interdigital electrode (IDE) pattern can be improved and was even higher than that of the low-density CNT sensor with the RE pattern. Based on the results of resistive-type sensors, the frequency responses of the CNT films with DS = 20 and 30 mu m, 20 layers, and the IDE pattern embedded into transmission-type resonators were studied. During NH3 absorption, the insertion and return losses of the resonator embedded with the sensing film with DS = 20 mu m and 20 layers increased, whereas those of the resonator embedded with the sensing film with DS = 30 mu m and 20 layers decreased. The resonator frequency of both films increased because the CNT resistance increased during NH3 absorption. These results indicated that the frequency response of the microwave sensors was related to the resistance of CNT films. A transmission-type microwave resonator can provide multidimensional frequency responses and high repeatability and has the potential for integration with the IoT and RFID for wireless gas-sensing applications.
Existing sensors for measuring dissolved methane in situ suffer from excessively slow response times or large size and complexity. The technology reported here realizes improvements by utilizing a hollow core optical ...
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Existing sensors for measuring dissolved methane in situ suffer from excessively slow response times or large size and complexity. The technology reported here realizes improvements by utilizing a hollow core optical fiber (HFC) as the detection cell in an underwater infrared laser spectrometer. The sensor operates by using a polymer membrane inlet to continuously extract dissolved gas from water. Once inside the sensor, the gas passes through an HCF, within which tunable diode laser spectroscopy is used to quantify methane. The use of an HCF for the optical cell enables advantages of sensitivity, selectivity, compactness, response time, and ease of integration. A submersible prototype has been developed, characterized in the laboratory, and tested in the ocean to a depth of 2000 m. Initial laboratory environmental testing showed a pCH4 detection range up to 10,000 mu atm, an uncertainty of 5.6 mu atm or +/- 1.4% (whichever is greater) and a response time of 4.6 min over a range of controlled operating conditions. Operation at sea demonstrated its utility in generating dissolved methane maps, targeted point sampling, and water column profiling.
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