The integration of dual-mesoporous structures, the construction of heterojunctions, and the incorporation of highly concentrated oxygen vacancies are pivotal for advancing metal oxide-based gas sensors. Nonetheless, achieving an optimal design that simultaneously combines mesoporous structures, precise heterojunction modulation, and controlled oxygen vacancies through a one-step process remains challenging. This study proposes an innovative method for fabricating zinc stannate semiconductors featuring dual-mesoporous structures and tunable oxygen vacancies via a direct solution precursor plasma spray technique. As a proof of concept, the resulting zinc stannate-based coatings are applied to detect 2-undecanone, a key biomarker for rice aging. Remarkably, the zinc oxide/zinc stannate heterojunctions with a well-defined secondary pore structure exhibit exceptional gas-sensing performance for 2-undecanone at room temperature. Furthermore, practical experiments indicate that the developed sensor effectively identifies adulteration in various rice varieties. These results underscore the potential of this method for designing metal oxides with tailored properties for high-performance gas sensors. The enhanced adsorption capacity and dual-mesoporous features of this semiconductor make it a promising candidate for sensing applications in agricultural food safety inspections.
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http://dx.doi.org/10.1007/s40820-024-01645-5 | DOI Listing |
Sensors (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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January 2025
School of Oceanography and Spatial Information, China University of Petroleum East China-Qingdao Campus, Qingdao 266580, China.
Salt marsh vegetation in the Yellow River Delta, including (), (), and (), is essential for the stability of wetland ecosystems. In recent years, salt marsh vegetation has experienced severe degradation, which is primarily due to invasive species and human activities. Therefore, the accurate monitoring of the spatial distribution of these vegetation types is critical for the ecological protection and restoration of the Yellow River Delta.
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