An optical sensing approach that balances portability with cost efficiency has been designed for the reliable monitoring of fugitive methane (CH) emissions. Employing a LiTaO-based pyroelectric detector integrated with micro-electro-mechanical systems and a broad infrared source, the developed gas sensor adeptly measured CH concentrations with a low limit of detection of about 5.6 ppm and showed rapid response times with consistently under 3 s. Notably, the novelty of our method lies in its precise control and reduction of CH levels, enhanced by wavelet denoising. This technique, optimized through meticulous grid search, effectively mitigated noise interference noticeable at CH levels below 10 ppm. Postdenoising, nonlinear regression analyses based on the modified Beer-Lambert equation returned values of 0.985 and 0.982 for the training and validation sets, respectively. In conclusion, this gas sensor has been shown to be able to meet the requirements for early warning of CH leakage on the surface in various carbon capture, utilization, and storage projects such as enhanced oil or gas recovery projects using CO injection.
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http://dx.doi.org/10.1021/acsomega.3c09769 | DOI Listing |
Spectrochim Acta A Mol Biomol Spectrosc
January 2025
Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control, Department of Environmental Science and Engineering, North China Electric Power University, Baoding 071003, China; Guangdong Provincial Key Laboratory for Green Agricultural Production and Intelligent Equipment, School of Environmental Science and Engineering, Guangdong University of Petrochemical Technology, Maoming 525000, China. Electronic address:
The concentration of S is a vital environmental indicator for evaluating the quality of source water, surface water, and wastewater, and it has a significant impact on biological systems, particularly human health. Therefore, it is crucial to detect S selectively and sensitively. In this study, we developed a simple and rapid one-pot method to prepare a gold nanocluster (BSA-AuNCs) probe for fluorescence-enhanced detection of S toxemia and analyzed the morphological characteristics of BSA-AuNCs and its complex with S using various characterization techniques.
View Article and Find Full Text PDFSensors (Basel)
January 2025
College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, China.
According to the physical characteristics of cotton and the work characteristics of cotton pickers in the field, during the picking process, there is a risk of cotton combustion. The cotton picker working environment is complex, cotton ignition can be hidden, and fire is difficult to detect. Therefore, in this study, we designed an improved algorithm for multi-sensor data fusion; built a cotton picker fire detection system by using infrared temperature sensors, CO sensors, and the upper computer; and proposed a BP neural network model based on improved mutation operator hybrid gray wolf optimizer and particle swarm optimization (MGWO-PSO) algorithm based on the BP neural network model.
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January 2025
Graduate Institute of Precision Engineering, National Chung Hsing University, No. 145, Xingda Road, Taichung 40227, Taiwan.
This study investigates the surface energies and work function changes in ZnGaO(111) surfaces with different atomic terminations using ab initio density functional theory. It explores the interactions of gas molecules such as NO, NO, and CHCOCH with Ga-terminated, O-terminated, and Ga-Zn-O-terminated surfaces. This study reveals previously unreported insights into how O-terminated surfaces exhibit enhanced reactivity with NO, resulting in significant work function changes of +6.
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January 2025
Department of Optical Engineering, Utsunomiya University, 7-2-1 Yoto, Utsunomiya 321-8585, Japan.
We describe the various steps of a gas imaging algorithm developed for detecting, identifying, and quantifying gas leaks using data from a snapshot infrared spectral imager. The spectral video stream delivered by the hardware allows the system to combine spatial, spectral, and temporal correlations into the gas detection algorithm, which significantly improves its measurement sensitivity in comparison to non-spectral video, and also in comparison to scanning spectral imaging. After describing the special calibration needs of the hardware, we show how to regularize the gas detection/identification for optimal performance, provide example SNR spectral images, and discuss the effects of humidity and absorption nonlinearity on detection and quantification.
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January 2025
Institute of NBC Defence, Beijing 102205, China.
Insufficient selectivity is a major constraint to the further development of metal oxide semiconductor (MOS) sensors for chemical warfare agents, and this paper proposed an improved scheme combining catalytic layer/gas-sensitive layer laminated structure with temperature dynamic modulation for the Mustard gas (HD) MOS sensor. Mustard gas simulant 2-Chloroethyl ethyl sulfide (2-CEES) was used as the target gas, (Pt + Pd + Rh)@AlO as the catalytic layer material, (Pt + Rh)@WO as the gas-sensitive layer material, the (Pt + Pd + Rh)@AlO/(Pt + Rh)@WO sensor was prepared, and the sensor was tested for 2-CEES and 12 battlefield environment simulation gases under temperature dynamic modulation. The results showed that the sensor only showed obvious characteristic peaks in the resistance response curves to HD under certain conditions (100-400 °C, the highest temperature was held for 1 s and the lowest temperature was held for 2 s), and its peak height reached 6.
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