This work reports a supramolecular cryptophane-A-coated surface acoustic wave (SAW) gas sensor for methane gas detection. Two two-port SAW resonators with low insertion loss, single resonation, and high Q-value was fabricated on a same ST-X quartz substrate, and acted as the feedback element of the oscillators. A Supramolecular cryptophane-A was synthesized from vanillyl alcohol using a double trimerisation method and deposited onto one of SAW resonators via spinning method. The present gas sensor was exposed to various concentrations of CH 4 gas at room temperatures. Larger sensor response and good repeatability were observed in the sensor experiment.
Effective detection of isopropyl methylfluorophosphonate (GB, sarin), a type of organophosphine poisoning agent, is an urgent issue to be addressed in maintaining public safety. In this research, a gas-sensitive film material defined as poly (4-hydroxy-4,4-bis trifluoromethyl) - butyl-1-enyl) - si-loxane (SXFA) with the structure of hexafluoroisopropyl (HFIP) functional group was synthesized by using methyl vinylpropyl dichlorosilane and hexafluoroacetone trihydrate as initial materials. Synthesis process products were characterized by FTIR. SXFA was prepared on a 200 MHz shear surface wave delay line with spin coating method for GB detected. Detection limit of ＜ 0.1 mg/m3 was obtained through conditional experiments. Meanwhile, we also obtained the maximum re-sponse of 2.168 mV at 0.1 mg/m3 concentration, which indicting a much lower detection limit of SAW-SXFA sensor. Additionally, the maximum response standard deviation of 0.11 mV with a co-efficient of variation of 0.01, as well as the maximum recovery standard deviation of 0.22 mV with a coefficient of variation of 0.02 were also obtained through 5 repeated experiments. Results showed that the SAW-SXFA sensor has strong selectivity and reproducibility, good selectivity, positive detection ability, high sensitivity, and fast alarm performance for sarin detection.
A set of small-scale flame spread experiments was conducted to explore the effects of sample orientation on the flame spread characteristics of extruded polystyrene (XPS) insulation material. The obtained data were employed to show the variation law of flame angle, pool fire zone length and flame spread rate when the tilt angle of XPS material changes from -90° to 90°. The flame angle decreased when the inclined angle increased from -90° to 90° and there are two different variation trends of flame angle in different inclined angle ranges. Meanwhile, both pool fire length and flame spread rate of the inclined XPS material depend on gravity controlled flow of flammable and molten drops produced by heating XPS material. Furthermore, the fitting relationship between flame spread rate and tilt angle was put forward when the tilt angle was less than or equal to 0°. This work is a supplement to the fire risk study on the XPS insulation materials and system.
Rapid and sensitive detection methods are in urgent demand for the screening of extensively used organophosphorus pesticides and highly toxic nerve agents for their neurotoxicity. In this study, we developed a novel Fe(3)O(4) magnetic nanoparticle (MNP) peroxidase mimetic-based colorimetric method for the rapid detection of organophosphorus pesticides and nerve agents. The detection assay is composed of MNPs, acetylcholinesterase (AChE), and choline oxidase (CHO). The enzymes AChE and CHO catalyze the formation of H(2)O(2) in the presence of acetylcholine, which then activates MNPs to catalyze the oxidation of colorimetric substrates to produce a color reaction. After incubation with the organophosphorus neurotoxins, the enzymatic activity of AChE was inhibited and produced less H(2)O(2), resulting in a decreased catalytic oxidation of colorimetric substrates over MNP peroxidase mimetics, accompanied by a drop in color intensity. Three organophosphorus compounds were tested on the assay: acephate and methyl-paraoxon as representative organophosphorus pesticides and the nerve agent Sarin. The novel assay displayed substantial color change after incubation in organophosphorus neurotoxins in a concentration-dependent manner. As low as 1 nM Sarin, 10 nM methyl-paraoxon, and 5 μM acephate are easily detected by the novel assay. In conclusion, by employing the peroxidase-mimicking activity of MNPs, the developed colorimetric assay has the potential of becoming a screening tool for the rapid and sensitive assessment of the neurotoxicity of an overwhelming number of organophosphate compounds.
This paper presents a new effective approach for the sensitive film deposition of surface acoustic wave (SAW) chemical sensors for detecting organophosphorus compounds such as O-ethyl-S-2-diisopropylaminoethyl methylphosphonothiolate (VX) containing sulfur at extremely low concentrations. To improve the adsorptive efficiency, a two-step technology is proposed for the sensitive film preparation on the SAW delay line utilizing gold electrodes. First, mono[6-deoxy-6-[(mercaptodecamethylene)thio]]-β-cyclodextrin is chosen as the sensitive material for VX detection, and a ~2 nm-thick monolayer is formed on the SAW delay line by the binding of Au-S. This material is then analyzed by atomic force microscopy (AFM). Second, the VX molecule is used as the template for molecular imprinting. The template is then removed by washing the delay line with ethanol and distilled water, thereby producing the sensitive and selective material for VX detection. The performance of the developed SAW sensor is evaluated, and results show high sensitivity, low detection limit, and good linearity within the VX concentration of 0.15–5.8 mg/m3. The possible interactions between the film and VX are further discussed.
We present a 300 MHz surface acoustic wave (SAW) oscillator for gas sensor application. As the oscillator element, SAW delay lines on an ST-X quartz substrate with low insertion loss and single-mode-selection capability were developed. And they were structured by Electrode Width Control Single Phase Unidirectional Transducer (EWC/SPUDT) configuration and comb transducer. The coupling of modes (COM) model was used to predict device performance prior to fabrication. The measured frequency response S12 showed a good agreement with simulated results; a low insertion loss of less than 9 dB and a linear phase in the 3 dB bandwidth were observed. The experimental results show that the baseline noise of the fabricated oscillators was typically up to ∼0.7×10−7 in a laboratory environment with temperature control. The oscillator was successfully applied to a gas sensor coated with fluoroalcoholpolysiloxane (SXFA) as the sensor material for O-isopropyl methyphosphonofluoridate (GB) detection, and a superior threshold detection limit was obtained (<<0.4 mg/m3).
A novel noise suppression method is proposed for the pressure surveillance of heavy oil thermal recovery well using white light extrinsic Fabry-Perot interferometric (EFPI) fiber-optic sensor. The moving grey model GM(1, 1) algorithm is applied to suppress the non-stationary noise and disturbance in downhole environment. Both theoretical analysis and field test results show that there exists a threshold effect for the moving window length selection, the optimized value of window length occurs at the threshold point which best removes the high frequency disturbance as well as retaining the fast change of actual pressure signal. Field test results show that the proposed method can increase the signal to noise ratio (SNR) of pressure profile with 10.4dB, and then can effectively suppress the large deviation in the forecasting result of daily oil production by combining temperature information.
In this work, the major methods for implementing flexible sensing technology—flexible surface acoustic wave (SAW) sensors—are summarized; the working principles and device characteristics of the flexible SAW sensors are introduced; and the latest achievements of the flexible SAW sensors in the selection of the substrate materials, the development of the piezoelectric thin films, and the structural design of the interdigital transducers are discussed. This paper focuses on analyzing the research status of physical flexible SAW sensors such as temperature, humidity, and ultraviolet radiation, including the sensing mechanism, bending strain performance, device performance parameters, advantages and disadvantages, etc. It also looks forward to the development of future chemical flexible SAW sensors for gases, the optimization of the direction of the overall device design, and systematic research on acoustic sensing theory under strain. This will enable the manufacturing of multifunctional and diverse sensors that better meet human needs.
Introduction:: Cracks are one of the major problems in modern concrete buildings, especially in locations that are difficult to map manually, such as bridges and high-rise buildings. Accurate analysis of unmanned aerial vehicle (UAV) images has become the key to determining whether a building needs maintenance. Methods:: Traditional image processing methods are easily interfered by high-frequency background. Neural network methods need fine datasets, which increase labor costs. Therefore, this paper proposes a segmentation algorithm based on UNet3+ network. After obtaining the UAV image, the rough location of the crack can be obtained by only rough labeling. And then, the sample balance can be carried out by clipping the target area. The UNet3+ network is used to train the processed datasets and extract the region of interest to ignore the non-target texture. Finally, the region of interest is further segmented by color clustering and edge detection methods. Results:: The proposed method can detect the cracks accurately. In all test images, the relative errors are less than 13%. Especially in test images whose width is less than 0.2mm, the maximum absolute error is only 0.0237mm, which is completely acceptable in actual production. The proposed method has higher practicability in the detection of concrete crack images taken by UAV. The results show that the proposed method outperforms the cutting-edge method published in the journal "Sensor", when the background is complex. Conclusion:: The proposed method can segment and detect cracks effectively, which can remove the high-frequency interference region from the images.
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